• IMMUNE NETWORK
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• v.5 no.4
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• pp.252-257
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• 2005

Background: This study was designed to investigate the effect of exercise training on defense mechanism of chronic degenerative disease, aging, and memory impairments of senescence-accelerated mouse (SAM)P8 under the hypothesis that "Senile dementia may be prevented by regular exercises". Methods: To evaluate the effects of exercise training on the defense mechanism of aging and memory impairment, SAMP8 were divided into two groups, the control group and exercise training groups. the exercise training group were performed with low $(\dot{V}O_2max\;25{\sim}33%)$, middle ($\dot{V}O_2max$ 50%) and high $(\dot{V}O_2max\;66{\sim}75%)$ intensity exercise. All SAMP8 mice were fed experimental diet ad libitum until 4, 8 months, and dead period. Results: Median lifespan in middle exercise group resulted in a significantly increased (23.5% and 18.7%, respectively), whereas these lifespan in high exercise group resulted in an unexpectedly decreased (13.5% and 12.1%, respectively) compared with control group. Body fat levels in 4 and 8 months of age were significantly decreased 43% to 51% in middle exercise group, whereas were remarkably deceased to 57% in high exercise group compared with control group. It is believed that extended median and maximum lifespan may be effected by calory restriction through the exercise training. Acetylcholine (ACh) levels were significantly increased 6.7% and 8.5% in middle and high exercise groups, and also choline acetyltransfease (ChAT) activities were significantly increased 10.3% and 11.9% in middle and high exercise groups. Conclusion: These results suggest that proper and regular exercises such as middle group ($\dot{V}O_2max$ 50%) may play an effective role in attenuating an oxygen radicals and may play an important role in improving a learning and memory impairments of senile dementia.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.290-297
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• 2002

The appearance of web technology has accelerated the role of the application of multimedia technology, computer communication technology and multimedia application contents. Recently WBI model which is based on web has been proposed in the part of the new activity model of teaching-teaming. How to learn and evaluate is required to consider individual learner's learning level. And it is recognized that the needs of the efficient and automated education agents in the web-based instruction is increased But many education systems that had been studied recently did not service fluently the courses which learners had been wanting and could not provide the way for the learners to study the learning weakness which is observed in the continuous feedback of the course. In this paper we propose design of multi-module system for course scheduling of learner-oriented using weakness analysis algorithm. First proposed system monitors learner's behaviors constantly, evaluates them, and calculates his accomplishment and weakness. From this weakness the multi-agent prepares the learner a suitable course environment to strengthen his weakness. Then the learner achieves an active and complete teaming from the repeated and suitable course.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.149-158
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• 2015

The purpose of this paper is to investigate the determinants of new product diffusion. We seek to document and explain systematic features of product diffusion. In this essay, we examine the well-documented empirical regularity that the speed of diffusion has accelerated during the twentieth century. The empirical results show that the main source of acceleration are faster declines in prices. Faster price declines make the product affordable to more consumers within a given period of time. Based on theories of intertemporal price discrimination and learning-by-doing, the association between the speed of adoption and the speed of price decline was explained. Faster price declines are attributed to several product characteristics as well as changes in income distribution. Above all, the introduction of consumer electronic products in more recent years can be regarded as the most important factor in accelerating price declines. Consumer electronic products are technologically different from non-electronic goods, in that semiconductors are important components. As the price of semiconductors has dropped rapidly, the falling production costs can be rapidly incorporated to the price of consumer electronic goods. Furthermore, most of the recently introduced consumer electronic products have network externalities, and many products with network externalities require complementary products. A complementary product becomes more readily or cheaply available as more people have the main product. One major difference between previous studies and this study is that the former focuses only on the factors that operate directly on the speed of adoption, while this study incorporated factors that work through price changes as well as the factors that work directly on the speed of adoption.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.23-37
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• 2024

Digital twin is an M&S (Modeling and Simulation) technology designed to solve or optimize problems in the real world by replicating physical objects in the real world as virtual objects in the digital world and predicting phenomena that may occur in the future through simulation. Digital twins have been elaborately designed and utilized based on data collected to achieve specific purposes in large-scale environments such as cities and industrial facilities. In order to apply this digital twin technology to real life and expand it into user-customized service technology, practical but sensitive issues such as personal information protection and personalization of simulations must be resolved. To solve this problem, this paper proposes a federated learning-based accelerated client training method (FACTS) for personalized digital twins. The basic approach is to use a cluster-driven federated learning training procedure to protect personal information while simultaneously selecting a training model similar to the user and training it adaptively. As a result of experiments under various statistically heterogeneous conditions, FACTS was found to be superior to the existing FL method in terms of training speed and resource efficiency.

• Korean Institute of Interior Design Journal
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• v.27 no.2
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• pp.86-97
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• 2018

In modern times, pluralistic social phenomena in which various values are pursed and recognized appear. The modern society called hyper-connected, intelligence information and zero marginal cost society in which shared value is commonly emphasized faces a paradigm shift to shared society system. In particular, sharing-based activities related with intelligence information sectors more prominently emerge in the high-tech informatization which has been accelerated. The purpose of this study is to understand design factors related with how attribution of the sharing culture is expressed in library spaces and examine how sharing infrastructure is established in users' spaces. As a research method, it initially conducted theoretical consideration of the sharing culture and information spaces, which can be regarded as sociocultural phenomena in modern times. Then, it drew sharing culture-based spatial design factors-access, openness and plurality. It analyzed configuration of spaces for sharing information-Cultural Commons (CC), Information Commons(IC) and Learning Commons (LC) - and infrastructure of information spaces, for library cases-five domestic and foreign public libraries-. The findings show that modern library spaces reflect historical needs for the sharing culture and actively serve their roles through spatial infrastructure including contents (programs) and services for sharing knowledge. The study is determined to be valuable as basic data in establishing the infrastructure of information spaces reflecting modern social trends and cultural phenomena, in expecting spatial structures in which knowledge is reproduced and planning spaces of libraries in the future.

• English Language & Literature Teaching
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• v.12 no.4
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• pp.1-29
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• 2006

The purpose of this paper is to present a qualitative case study on teaching English as an international language in Korean context. The researcher investigated the implementation process of the new elementary English program from the government to local schools to find out to what extent the symbolic value of English as an international language affect the implementation process of the elementary English program. The research result showed that the elementary teachers shared the different views of the status of English from those of government and the parents, and their differing perception of the role of English constantly affected their implementation efforts. The research findings also revealed that the public's concern of English dominance in Korean educational system resulted in the government's 'comprised curriculum' by lowering the learning goals of the English program. The findings also indicated that the introduction of the elementary English program accelerated English dominance in both teacher and student culture. The question of how to resolve the conflict between acquiring English proficiency and its negative influence on Korean culture remains a complex issue in implementing the new elementary English program.

• The Journal of Pediatrics of Korean Medicine
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• v.23 no.3
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• pp.241-262
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• 2009

Objectives This study is designed to investigate the effects of Jujadokseo-hwan on the brain ability and inducing oxidative stresses. Methods We measured the changes of regional cerebral blood flow and mean arterial blood pressure. Then we analyzed histological examination, immunohistochemistric response and anti-oxidant activity of Jujadokseo-hwan. Results 1. Treatment of Jujadokseo-hwan significantly increased regional cerebral blood flow but decreased mean arterial blood pressure. 2. Treatment of Jujadokseo-hwan-induced increase of regional cerebral blood flow was significantly inhibited by pretreatment with indomethacin (1 mg/kg, i.p.), an inhibitor of cyclooxygenase. 3. In histological examination through TTC stain, group I was no change, but group II showed that discolored in the most cortical part. Group III showed that decreased discolor in the cortical part. 4. In immunohistochemistric response of BDNF, group II showed that lower response effect. Group III showed that increase response effect. 5. Treatment of Jujadokseo-hwan increased proliferation rates of Glial cell effectively 6. Treatment of Jujadokseo-hwan accelerated proliferation rates of C6 cells in vitro. In addition, protective effects on cell death induced by paraquat, rotenone and hydrogen peroxide. In addition, activity of SOD were increased by treatment with Jujadokseo-hwan. Conclusions In conclusion, Jujadokseo-hwan can improve of the brain ability, learning ability, memory ability and induce ischemic brain injuries.