• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.1
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• pp.127-140
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• 1988

The management of sewage and rainfall runoff becomes an emerging problem with the growth of urban communities. From the uncontrollable excess intensity or amount of rainfall, the conditions of sewer surcharge or manhole overflow could be generated in the combined sewer network where municipal or industrial wastewaters and rainfall runoff flow. The predictive model far the prevention of property and human life losses from this inundation was studied in this research. In the development of a mathematical flow model for the combined sewer surcharge and overflow, the Preissmann Slot concept and the four-point implicit method of finite difference were utilized. For the usage in personal computer, the overlapping segment method that required less memory storage was adopted. Through the simulation of hypothetical sewer network, the conservation of discharge volume was checked, and the usefulness of the Preissmann Slot was assured from the temporal distribution of discharge and depth along the sewer network. Also the possible field application for the correction of sewer diameters and slopes in the design of sewer network which has no surcharge/overflow condition was suggested.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.23-43
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• 2010

This study is to investigate how much highschool students, who have learned functional concepts included in the Middle school math curriculum, understand chapters of the function, to analyze the types of errors which they made in solving the mathematical problems and to look for the proper instructional program to prevent or minimize those ones. On the basis of the result of the above examination, it suggests a classification model for teaching-learning methods and teaching material development The result of this study is as follows. First, Students didn't fully understand the fundamental concept of function and they had tendency to approach the mathematical problems relying on their memory. Second, students got accustomed to conventional math problems too much, so they couldn't distinguish new types of mathematical problems from them sometimes and did faulty reasoning in the problem solving process. Finally, it was very common for students to make errors on calculation and to make technical errors in recognizing mathematical symbols in the problem solving process. When students fully understood the mathematical concepts including a definition of function and learned procedural knowledge of them by themselves, they did not repeat the same errors. Also, explaining the functional concept with a graph related to the function did facilitate their understanding,

• Korean Journal of Food Science and Technology
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• v.52 no.5
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• pp.450-458
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• 2020

The purpose of this study was to conduct a systematic review of the current published research related to improvement in cognitive function. A systematic search was performed in three bibliographic databases (PubMed, Cochrane Library, and EMBASE) using "dementia", "memory", "food", "diet", and "nutrition" as keywords. Meal management intervention, including Dietary Approaches to Stop Hypertension (DASH) diet, Mediterranean (Med) diet, Diet Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet, and other studies, was also included in the analysis. Through extensive screening, 21 articles, out of 2101 papers retrieved, were used for the final systematic review. The methodological quality of the randomized controlled clinical trials (RCTs) was assessed using the Cochrane Risk of Bias tool. These articles recommended vegetables, fruits, whole grains, olive oil, fish, berries, nuts, and beans. In conclusion, this study suggests the potential use of meal management to improve cognitive function.

• Korean Journal of Biological Psychiatry
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• v.8 no.1
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• pp.85-95
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• 2001

This study was designed to examine the effects of two antidepressant drugs on the expression of c-fos mRNA in cultured embryonic rat hippocampal neurons. The drugs used were imipramine and amitriptyline. On the fourth day of culture, hippocampal neurons were treated with variable concentrations of each drug. Competitive RT-PCR(Reverse Transcriptase-PCR) analysis was used to quantify the c-fos mRNA expression induced by each drug. Experimental results showed that acute and direct treatment with imipramine and amitriptyline with relatively low concentrations(imipramine ${\leq}10{\mu}M$, amitriptylne ${\leq}10{\mu}M$) had no inductive effect on the expression of c-fos mRNA in the rat hippocampal neurons. However, after treatment with relatively high concentrations(imipramine ${\geq}100{\mu}M$, amitriptyline ${\geq}100{\mu}M$) c-fos mRNA was not detected. These findings suggest the followings. Firstly, the action mechanisms of these drugs on the hippocampal neurons might not be mediated by c-fos but by other immediate-early genes(IEGs). Secondly, their actions may be mediated indirectly via other areas of the brain. Thirdly, the expression of c-fos might be inhibited by high concentrations of these drugs, or the high concentrations could induce cell death. Finally, though cell death remains to be confirmed, the inhibition of c-fos induction or cell death could play a role in the cognitive impairments known to be adverse effects of some antidepressants. This study is believed to be a first step toward understanding the mechanisms of learning and memory. Further studies are needed to investigate the expression of various IEGs and changes in the hippocampal neurons of rat resulting from chronic treatment with antidepressant drugs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3680-3689
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• 2010

The purpose of this study is to inquire into the changes to the emotional intelligence of young children by giving them pleasure and memory through the program of ecological experience. A survey was made on 40 young children in two classes out of 5-year-old children's classes in nurseries located at Chungcheong-do. They were divided into the experiment group and control group to consist of 20 persons, respectively. For young children of the experiment group, the experiment was conducted while observing and experiencing through the division of the group into 5 persons on fixed days according to the program of ecological experience. Analysis showed that the program of ecological experience in the experiment group relatively higher effect of increase for the emotional intelligence of young children, and the use of self emotion, the cognition and consideration of other's emotion, the cognition and expression of self emotion, the regulation and impulse control of emotion, the relationship with teacher and the relationship with peer by sub-factors than that in the control group. In other words, close relationships with nature and inquiry instruction of ecological experience have provided the attitude-based formation living together with the understanding of natural world and eco-friendly attitude, the cognition of ecological crisis and social cooperation that couldn't feel in indoor education. Consequently, the program of ecological experience should prove useful for the emotional intelligence of young children.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.1-11
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• 2010

Recently, there has been a growing interest in the processing of continuous queries over multiple data streams. When the arrival rates of tuples exceed the memory capacity of the system, a load shedding technique is used to avoid the system becoming overloaded by dropping some subset of input tuples. In this paper, we propose an effective load shedding algorithm for multi-way windowed joins over multiple data streams. Most previous load shedding algorithms estimate the productivity of each tuple, i.e., the number of join output tuples produced by the tuple, based on its "join attribute value" and drop tuples with the lowest productivity. However, the productivity of a tuple cannot be accurately estimated from its join attribute value when the join attribute values are unique and do not repeat, or the distribution of the join attribute values changes over time. For these cases, we estimate the productivity of a tuple based on its "arrival order" on data streams, rather than its join attribute value. The proposed method can effectively estimate the productivity of a tuple even when the productivity of a tuple cannot be accurately estimated from its join attribute value. Through extensive experiments and analysis, we show that our proposed method outperforms the previous methods in terms of effectiveness and efficiency.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.353-360
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• 2006

This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of $1280{\times}960$ images, executed on a 3GHz Pentium4 PC with 512M byte memory.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.99-106
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• 2018

In the process of acquiring information through the cyber ISR (Intelligence Surveillance Reconnaissance) and research into the agent to help decision-making, periodic communication between the C&C (Command and Control) server and the agent may not be possible. In this case, we have studied how to effectively surveillance and reconnaissance. Due to the network configuration, agents planted on infiltrated computers can not communicate seamlessly with C&C servers. In this case, the agent continues to collect data continuously, and in order to analyze the collected data within a short time in When communication is possible with the C&C server, it can utilize limited resources and time to continue its mission without being discovered. This research shows the superiority of incremental learning method over batch method through experiments. At an experiment with the restricted memory of 500 mega bytes, incremental learning method shows 10 times decrease in learning time. But at an experiment with the reuse of incorrectly classified data, the required time for relearn takes twice more.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.9
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• pp.597-604
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• 2016

A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.

• Science of Emotion and Sensibility
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• v.14 no.2
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• pp.207-220
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• 2011

The purpose of this study is to investigate sensibility words related with eco-friendly in the two media fashion magazines and internet newspapers and to analysis their appearance frequency and changes by the year through 1999~2010. Most frequently used words are 'nature, eco, cotton, natural fiber, health, fresh, clear, preservation, harmony, com fiber, and Lohas'. The words are divided in 4 groups: 'Nature/Environment, Material/Fiber, Human, and Adjectives/Micell'. A point of appearing time is analyzed: 'ecology, memory-shape material, organic, spa' were used before 2000, 'nature environment, eco-friendly, stretch material, wellbeing, substitute, recycling' were in 2000-2001, 'smart material, eco material, green' in 2002-2003, 'coolbiz, Lohas, natural dye' in 2004-2005, 'herb medicine, sustainable, warmbiz' in 2006-2007, 'greensumer, greenlife, solar energy, forest bath' in 2008-2009. Looking into their changes, in early 2000, the words of eco-friendly emotion and sensibility had appeared frequently relatively, but later on they decreased, and again recently increased showing highest appearing frequency. 'Nature/Environment' words have appeared recently very much, while 'Human' sensibility words have not changed much or decreased a little. 'Adjective/Micell' words has increased little bit recently. 'Material/Fiber' words showed decrease at fashion magazine, while they increased at the pages of internet news.