• Animal cells and systems
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• v.16 no.3
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• pp.190-197
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• 2012

Depression is one of the most prevalent diseases of alcohol abuse. Brain-derived neurotrophic factor (BDNF) plays a critical role in cell survival in the hippocampus. Phosphorylation of extracellular signal-regulated kinase 1/2 (p-ERK1/2) is induced by BDNF, and it regulates cell proliferation and differentiation in the brain. We investigated the effects of alcohol intake on depression-like behavior, cell proliferation, expressions of BDNF and its downstream molecules in the hippocampus using Mongolian gerbils. The gerbils were divided into four groups: control group, 0.5 g/kg alcohol-treated group, 1 g/kg alcohol-treated group, 2 g/kg alcohol-treated group. Each dose of alcohol was orally administered for 3 weeks. The present results demonstrated that alcohol intake induced depression-like behavior. Both 5-hydroxytryptamine synthesis and its synthesizing enzyme tryptophan hydroxylase expression in the dorsal raphe and cell proliferation in the hippocampal dentate gyrus were decreased by alcohol intake. Alcohol intake suppressed BDNF expression, and resulted in the decrease of its downstream molecules, pERK1/2 and Bcl-2, in the hippocampus. We showed that alcohol intake may lead to a depressed-like state with reduced hippocampal cell proliferation through inhibition of the BDNF-ERK signaling pathway.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.75-81
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• 2021

The purpose of this research is to derive and evaluate priorities for critical factors that must be determined before an enterprise adopts a cloud computing service. AHP analysis techniques were used to reflect decisions made by experts as research methods. AHP is a decision-making technique that expresses complex decision-making problems hierarchically and derives the best alternatives through pairwise comparison between the items of the hierarchy. Compared to the existing statistical decision making techniques, the decision making process is systematic and simple, making it easy to understand. In addition, the procedure is also reasonable by providing an indicator to determine the consistency of the decision maker in the analysis process. The analysis results of this research showed that security was the first priority, reliability was the second priority, and economic efficiency was the third priority. Among the factors in the first-priority security items, the access control rights and the safety factors of external threats are the most important factors. Research results can be used as a guideline in future practice, and it is necessary to evaluate, compare and analyze the satisfaction of companies that have adopted cloud computing services in the future.

• Herbal Formula Science
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• v.27 no.1
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• pp.31-44
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• 2019

Objective : Herbal dispensaries, where medications are prepared for patients, require specific preparation and operations management for safe herbal medicines. This study aims to propose improvements in the herbal medicine preparation and operation of the herbal dispensaries as series study of the "A Survey on the Management Status of Extramural Herbal Dispensaries" Methods : We first checked current management regulations. In addition, we compared and analyzed related laws which are "State management norm of Traditional Chinese Medicine dispensaries", "Enforcement Rule of Medicinal Product Safety" and " Hazard Analysis and Critical Control Point(HACCP)", to introduce the assessment items of herbal dispenses evaluation and certification system. Results : In this study, we found that the current regulations, "Guideline on Installation and Utilization of Extremal Herbal Pharmaceutical Facility and Shared-use of Herbal Dispensary", are insufficient to ensure the quality and safety of herbal medicines. We suggested articles for the proper management of herbal dispensaries and these were introduced to the Herbal dispensary evaluation and certification system. Conclusion : We recommend evaluation articles in Herbal dispensary evaluation and certification systems need to be popular among herbal dispensaries, then Korean herbal medicine could restore credibility from the people.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.95-108
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• 2011

Smart Grids are intelligent next generating Electric Power System (EPS) that provide environment-friendliness, high-efficiency, and high-trustworthiness by integrating information and communication technology with electric power technology. Smart grids help to supply power more efficiently and safely than past systems by bilaterally exchanging information between the user and power producer. In addition, it alleviates environmental problems by using renewable energy resources. However, smart grids have many cyber security risks because of the bilateral service, the increase of small and medium-sized energy resources, and the installation of multi-sensors or control devices. These cyber risks can cause critical problems within a national grid through even small errors. Therefore, in order to reduce these risks, it is necessary to establish a cyber security strategy and apply it from the developmental stage to the implementation stage. This thesis analyzes and recommends security strategy in order to resolve the security risks. By applying cyber security strategy to a smart grid, it will provide a stepping-stone to creating a safe and dependable smart grid.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.77-87
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• 2023

Applying various association rule mining algorithms to the network intrusion detection task involves two critical issues: too large size of generated rule set which is hard to be utilized for IoT systems and hardness of control of false negative/positive rates. In this research, we propose an association rule mining algorithm based on the newly defined measures called coverage and exclusion. Coverage shows how frequently a pattern is discovered among the transactions of a class and exclusion does how frequently a pattern is not discovered in the transactions of the other classes. We compare our algorithm experimentally with the Apriori algorithm which is the most famous algorithm using the public dataset called KDDcup99. Compared to Apriori, the proposed algorithm reduces the resulting rule set size by up to 93.2 percent while keeping accuracy completely. The proposed algorithm also controls perfectly the false negative/positive rates of the generated rules by parameters. Therefore, network analysts can effectively apply the proposed association rule mining to the network intrusion detection task by solving two issues.

• Transactions of Materials Processing
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• v.32 no.3
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• pp.153-159
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• 2023

This paper presents the optimal design of a heating system using radiant heating elements for application in smart farms. Smart farming, an advanced agricultural technology, is based on artificial intelligence and the internet of things and promotes crop production. Temperature and humidity regulation is critical in smart farms, and thus, a heating system is essential. Radiant heating elements are devices that generate heat using electrical energy. Among other applications, radiant heating elements are used for environmental control and heating in smart farm greenhouses. The performance of these elements is directly related to their electrical energy consumption. Therefore, achieving a balance between efficient electrical energy consumption and maximum heating performance in smart farms is crucial for the optimal design of radiant heating elements. In this study, the size, electrical energy supply, heat generation efficiency, and heating performance of radiant heating elements used in these heating systems were investigated. The effects of the size and electrical energy supply of radiant heating elements on the heating performance were experimentally analyzed. As the radiant heating element size increased, the heat generation efficiency improved, but the electrical energy consumption also increased. In addition, increasing the electrical energy supply improved both the heat generation efficiency and heating performance of the radiant heating elements. Based on these results, a method for determining the optimal size and electrical energy supply of radiant heating elements was proposed, and it reduced the electrical energy consumption while maintaining an appropriate heating performance in smart farms. These research findings are expected to contribute to energy conservation and performance improvement in smart farming.

• Journal of English Language & Literature
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• v.55 no.1
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• pp.3-24
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• 2009

The Harry Potter series is considered to represent the multicultural aspect of contemporary British society and to show critical perspectives of racism. This series, however, also includes many elements of British imperialism. This paper examines the ideas about education and Harry's role in relation to British imperialism. One of the main ideas prevalent in 19th century British boys' public schools was that people's blood origin is the most important element in determining their characteristics, ability and moral qualities. The students' inherited capacity and their family background are more highly regarded than their secondary learning and training. This reflects a 19th century concept that ultimately, inborn quality makes 'a hero', a truth presented in the educational policies of Hogwarts. Hogwarts' educational policies and systems can also be related to 'developmentalism', which defines children as imperfect, in-progress and incomplete, thus needing proper training and discipline. As this concept functioned to justify the control of children while educating them, Hogwarts adopts diverse controlling devices and oppressive policies, which are mainly justified in the name of education. On the one hand, child characters are controlled and oppressed by the school authorities, on the other hand, some of the students such as Harry have remarkable magic powers enough to resist the adult authority and even to save the magic society from the evil power. Harry plays dual roles, which the British boys of the Empire were assigned from their society; they are important heirs to conquer the 'evil' or 'barbarous' world but need to be obedient to a 'good' authority to achieve the mission. Harry's magic power and self-discipline ultimately contribute to fulfilling Dumbledore's mission, which mirrors 19th century British boys' roles as the heirs of the British Empire.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3732-3753
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• 2023

The Real-time Analysis for Particle-transport and In-situ Detection (RAPID) Code System, developed based on the Multi-stage Response-function Transport (MRT) methodology, enables real-time simulation of nuclear systems such as reactor cores, spent nuclear fuel pools and casks, and sub-critical facilities. This paper presents the application of a novel fission matrix-based burnup methodology to the well-characterized JSI TRIGA Mark II research reactor. This methodology allows for calculation of nuclear fuel depletion by combination and interpolation of RAPID's burnup dependent fission matrix (FM) coefficients to take into account core changes due to burnup. The methodology is compared to experimentally validated Serpent-2 Monte Carlo depletion calculations. The results show that the burnup methodology for RAPID (bRAPID) implemented into RAPID is capable of accurately calculating the k_eff burnup changes of the reactor core as the average discrepancies throughout the whole burnup interval are 37 pcm. Furthermore, capability of accurately describing 3D fission source distribution changes with burnup is demonstrated by having less than 1% relative discrepancies compared to Serpent-2. Good agreement is observed for axially and pin-wise dependent fuel burnup and nuclear fuel nuclide composition as a function of burnup. It is demonstrated that bRAPID accurately describes burnup in areas with high gradients of neutron flux (e.g. vicinity of control rods). Observed discrepancies for some isotopes are explained by analyzing the neutron spectrum. This paper presents a powerful depletion calculation tool that is capable of characterization of spent nuclear fuel on the fly while the reactor is in operation.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.67-79
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• 2024

Water balance analysis in heightened reservoirs, which have been raised to ensure a stable supply of irrigation water and secure water against floods and heavy rainfall, is essential for evaluating water supply capacity and reservoir maintenance. The consecutively linked reservoir system, which involves preserving the existing embankment while constructing a new one, affects the water balance between the existing and new reservoirs. This study aims to analyze the linked water balance between reservoirs in a consecutively linked reservoir system using the DIROM (Daily Irrigation Reservoir Operation Model) model. Surveys were conducted to investigate actual water use, and multiple water supply quantities were estimated based on these findings. Methods to supplement missing data and improve the limitations of simulated inflow were proposed and applied, and the performance of the daily storage simulation was evaluated. By supplementing the missing water use data, the NSE (Nash-Sutcliffe Efficiency) of the Sonhang reservoir storage rate simulation improved by approximately 30%. Additionally, result of using inflow coefficients significantly enhanced the simulation performance for the Sonhang2 and Sonhang reservoirs. This study confirms the necessity of incorporating appropriate inflow coefficients in reservoir design to overcome the model's tendency to overestimate inflow, highlighting the critical importance of quality control in observational data. The findings are expected to be useful for the design and analysis of future reservoir systems through embankment heightening.