• Title/Summary/Keyword: 열-구조 모델

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The Study on the Ultrastructure and Distribution of Dopaminergic Cells in the Brain of Mongolian Gerbil after Water Deprivation (절수에 의한 Mongolain gerbil 뇌 Dopamine성 면역반응세포의 분포와 미세구조의 변화에 관한 연구)

  • Song, Chi-Won;Lee, Kyoung-Youl;Park, Il-Kwon;Kwon, Hyo-Jung;Kim, Moo-Kang;Lee, Kang-Lee
    • Applied Microscopy
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    • v.30 no.2
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    • pp.193-204
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    • 2000
  • Nowadays, mongolian gerbil is widely utilized in the research of brain and water deprivation because of congenitally incomplete Willis' circle, audiogenic seizure in low noise, and special cholesterol metabolism without water absorption for a long time. In this study, we intended to identify the time lapse changes in the general morphoogy and ultrastructure of the catecholaminergic neurons of mongolian gerbil brain in after long-term water deprivation. Fifteen mongolian gerbils were divided into 3 groups (5, 10, and 20-day water deprivation groups), each with 5 mongolian gerbils. Additional 5 mongolian gerbils which received water without limitation were used as a control. The brain sections were immunostained using tyrosine hysroxylase (TH), $ dopamine-\beta-hydroxylase$ (DBH), and phenylethanolamine-N-methyltrasferase (PMNT) antibodies. And immunoreactive cells were observed by electromicroscopy for the ultrastructural changes . The TH-immunoreactive (TH-IR) nerve cells were observed in the para- and peri-ventricular nucleus of the 3 rd ventricle in the hypothalamus and the substantia nigra. The number of TH-IR neurons in these areas was decreased from the 5th day of the water deprivation to the 10 th day and reincreased until 20 th day water deprivation. The shape and density of the dopamine-secreting cells identified by immunohistochemistry showed changes in the continuous water deprivation. Electron microscopy revealed a round nucleus in the neurons of control group but 5-day water deprivation group showed a dense and irregularly shaped nucleus. Also in the 5-day water-deprived group, mitochondria was decreased in number and junctins were disappered. Endoplasmic reticulum, Golgi complex did not show changes after water-deprivation. In this results, we can conclude that dopamine are involved in the water metabolism in mongolian gerbil, and mongolian gerbil could be used as an animal model for the researches of water deprivation.

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Variation and Forecast of Rural Population in Korea: 1960-1985 (농촌인구(農村人口)의 변화(變化)와 예측(豫測))

  • Kwon, Yong Duk;Choi, Kyu Seob
    • Current Research on Agriculture and Life Sciences
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    • v.8
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    • pp.129-138
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    • 1990
  • This study investigated the relationship between the cutflow of rural population and agricultural policy by using time series method. For the analytical tools, decomposition time series methods and regression technique were employed in computing seasonal fluctuation and cyclical fluctuation of population migration. Also, this study predicted farmhouse, rural population till the 2000's by means of the mathematical methods. The analytical forms employed in forecasting farmhouse, rural population were Exponential curve, Gompertz curve and Transcendental form. The major findings of this study were identified as follows: 1) Rural population and farmhouse population began to decrease from 1965 and hastily went down since 1975. Rural population which accounted for 36.4 percent, 35.6 percent of national population respectively in 1960 diminished about two times: 17.5 percent, 17.1 percent respectively. 2) The rapid decreasing of the rural population was caused because of the outflow of rural people to the urban regions. Of course, that was also caused from the natural decreases but the main reason was heavily affected more the former than the latter. In the outflowing course shaped from rural to the urban regions, rural people concentrated on such metropolis as Seoul, Pusan, Keanggi. But these trends were diminishing slowly. On the other hand, compared with that of the 1970's the migration to Keanggi was still increasing in the 1980's. That is, people altered the way of migration from the migration to Seoul, Pusan to the migration to the out-skirts of Seoul. 3) The seasonal fluctuation index of population migration has gone down since the June which the request of agricultural labor force increases and has turned to be greatly wanted in the March as result of decomposition time series method. As result of cyclical analysis, the cyclical patterns of migration have greatly 7 cycle. 4) As result of forecasting the rural and farmhouse population, rural and farmhouse population in the 2000 will be about 9,655(thousand/people) and 4,429(thousand/people) respectively. Thus, it is important to analyze the probloms that rural and farmhouse population will decrease or increase by the degree. But fairly defining the agricultural into a industry that supply the food, this problem - how much our nation need the rural and farmhouse population - is greatly significant too. Therefore, the basic problems of the agricultural including the outflows of rural people are the earning differentials between rural and urban regions. And we should regard the problems of the gap of relative incomes between rural and urban regions as the main task of the agricultural policy and treat the agricultural policy in the viewpoint of developing economic equilibrium than efficiency by using actively the natural resources of the rural regions.

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Popping Mechanism and Shape Moulding Factor of Popcorn (튀김옥수수의 파열방향 및 튀김형태 결정요인)

  • Kim, Sun-Lim;Park, Seung-Ue;Kim, E-Hun
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.40 no.1
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    • pp.98-102
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    • 1995
  • Popped popcorn generally have a regular popping direction and typical shape. But the reason and mechanism are not clear yet. This experiment was carried out to investigate the shape moulding factor of popped popcorn. Pericarp thickness of tip-cap section of kernels is slightly thicker than that of top section and this fact provides the important information to the reason. Popping starts when the moisture pressure of heated popcorn is increased and reaches at the critical pressure. Therefore, in the same moisture pressure conditions, top sections are bursted first because their pericarp section is thinner than that of tip-cap section. At the very moment tip-cap sections pull down the top sections of peri carp as bi-metal does. So kernels which removed tip-cap section showed the irregular popping shape because they lost the tip-cap pericarp function. How-ever, kernels which removed embryo showed the typical popping shape but their popping volume was small due to emition and shortage of critical moisture pressure. But kernels which removed the whole pericarp and top pericarp were not popped at all because moisture was entirely emitting out of kernels. These results suggest that the shape moulding factor of popped popcorn is the pericarp thickness differences between the top and tip-cap section of kernels.

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Studies on Changes in the Hydrography and Circulation of the Deep East Sea (Japan Sea) in a Changing Climate: Status and Prospectus (기후변화에 따른 동해 심층 해수의 물리적 특성 및 순환 변화 연구 : 현황과 전망)

  • HOJUN LEE;SUNGHYUN NAM
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.28 no.1
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    • pp.1-18
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    • 2023
  • The East Sea, one of the regions where the most rapid warming is occurring, is known to have important implications for the response of the ocean to future climate changes because it not only reacts sensitively to climate change but also has a much shorter turnover time (hundreds of years) than the ocean (thousands of years). However, the processes underlying changes in seawater characteristics at the sea's deep and abyssal layers, and meridional overturning circulation have recently been examined only after international cooperative observation programs for the entire sea allowed in-situ data in a necessary resolution and accuracy along with recent improvement in numerical modeling. In this review, previous studies on the physical characteristics of seawater at deeper parts of the East Sea, and meridional overturning circulation are summarized to identify any remaining issues. The seawater below a depth of several hundreds of meters in the East Sea has been identified as the Japan Sea Proper Water (East Sea Proper Water) due to its homogeneous physical properties of a water temperature below 1℃ and practical salinity values ranging from 34.0 to 34.1. However, vertically high-resolution salinity and dissolved oxygen observations since the 1990s enabled us to separate the water into at least three different water masses (central water, CW; deep water, DW; bottom water, BW). Recent studies have shown that the physical characteristics and boundaries between the three water masses are not constant over time, but have significantly varied over the last few decades in association with time-varying water formation processes, such as convection processes (deep slope convection and open-ocean deep convection) that are linked to the re-circulation of the Tsushima Warm Current, ocean-atmosphere heat and freshwater exchanges, and sea-ice formation in the northern part of the East Sea. The CW, DW, and BW were found to be transported horizontally from the Japan Basin to the Ulleung Basin, from the Ulleung Basin to the Yamato Basin, and from the Yamato Basin to the Japan Basin, respectively, rotating counterclockwise with a shallow depth on the right of its path (consistent with the bottom topographic control of fluid in a rotating Earth). This horizontal deep circulation is a part of the sea's meridional overturning circulation that has undergone changes in the path and intensity. Yet, the linkages between upper and deeper circulation and between the horizontal and meridional overturning circulation are not well understood. Through this review, the remaining issues to be addressed in the future were identified. These issues included a connection between the changing properties of CW, DW, and BW, and their horizontal and overturning circulations; the linkage of deep and abyssal circulations to the upper circulation, including upper water transport from and into the Western Pacific Ocean; and processes underlying the temporal variability in the path and intensity of CW, DW, and BW.

Development of a complex failure prediction system using Hierarchical Attention Network (Hierarchical Attention Network를 이용한 복합 장애 발생 예측 시스템 개발)

  • Park, Youngchan;An, Sangjun;Kim, Mintae;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.127-148
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    • 2020
  • The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.