• KOREAN JOURNAL OF CROP SCIENCE
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• v.36 no.3
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• pp.266-270
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• 1991

Storage in the form of brown or milled rice saves space and cut cost rather than storage of rough rice, the common way of grain storage in Korea. But, brown or milled rice may be more susceptable to grain aging and sensory change than rough rice. Rice stored in government warehouse for 20 months after harvest was hulled into brown or milled rice and packaged with kraft paper bag (paper package), polyprophylen (PP package), and polyethylene (PE package). Then, after those rice packages were stored under room condition for one year, we investigated germinability, fat acidity, and sensory change to determine milling and packaging effects. Germinability of rough and brown rice was decreased significantly after long-term storge. In germination rate, Chucheong cultivar was lower than Milyang #23, brown rice was lower than rough rice, but there was no differences within packaging materials. TTC test which had a significant correlation with germinability can be used as a handy procedure for predicting grain germination. Fat acidity was increased as the order of rough < milled < brown rice in terms of milling, and PP < paper < PE package in terms of packaging materials. Especially, storage of brown rice increased fat acidity above 30 mg KOH, indicating one of characteristics of grain aging. To prevent from high fat acidity it was necessary to store in forms of rough grain with paper or PP packaging and milled rice with paper, or PP, or PE packaging. In sensory test of stored grain, eating quality in brown rice was the worst because of acidification of fatty acid. Also, eating quality of stored grain became worse as fat acidity increased.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.231-240
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• 2022

This study empirically analyzed the effect of complex commercial facilities on the price of nearby apartments in a Hedonic price model. The spatial range of this study was the walking area of H Department Store located in Pangyo among the second new towns suburb of Seoul, and the time range was 2020. The dependent variable was the real transaction price of the apartment, and independent variable were the characteristics of the housing, the characteristics of the complex, and the characteristics of the region. As a result of the analysis, the area of exclusive use space, the transaction floor, and the highway accessibility had a positive effect on the price of the apartment, and the elapsed year had a negative effect on the price of the apartment. However, the size of the apartment had little effect on apartment prices, and the distance from the complex commercial facilities was shown to be related to apartment prices, indicating that apartment prices declined as it moved away from the complex commercial facilities. Therefore, this is much more influential than the influence of distance from subway stations on apartment price. This confirms that the effect factors of apartment prices and the size of their influence appear differently in the new town area and the existing metropolitan area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.79-89
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• 2023

The inventory of many materials requires a large storage space, and the longer the storage period, the higher the potential maintenance cost. When materials are stored on a construction site, there are also concerns about safety due to the reduction of room for movement and working. On the other hand, construction sites that do not store materials have insufficient inventory, making it difficult to respond to demands such as sudden design changes. Ordering materials is then subject to delays and extra costs. Although securing an appropriate amount of inventory is important, in many cases, material management on a construction site depends on the experience of the site manager, so a reasonable material inventory management plan that reflects the construction conditions of a site is required. This study proposes an economical material management method by reflecting variables such as the status of the preceding and following activities, site size, material delivery cost, timing of an order, and quantity of orders. To this end, we set the appropriate inventory amount while adjusting related activities in the activity network, using float time for each activity, the size of the yard, and the order quantity as the main variables, and applied a genetic algorithm to this process to suggest the optimal order timing and order quantity. The material delivery cost derived from the results is set as a fitness index and the efficiency of inventory management was verified through a case application.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• The Korean Journal of Physiology
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• v.18 no.2
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• pp.151-162
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• 1984

The mechanism of the contractile response of longitudial muscle of rabbit ileum to substance P (SP) has been investigated. The contractions in rabbit ileum under various conditions were recorded isometrically The following results were obtained. 1) The contractions by SP increased according to concentrations. SP·induced contraction was not sustained but faded rapidly at $10^{-7}M$. The response to the commutative addition of SP was decreased in comparison to the response to separate administration of each concentration . 2) The response to $10^{-8}M$ SP after 5 min application cf $10^{-7}M$ SP was increased with increasing the time interval between the administration of $10^{-7}$ and $10^{-8}M$ SP. 3) The treatment of rabbit ileum by $10^{-7}M$ SP for 5 min didn't decrease the response to $10^{-6}M$ acetylcholine. 4) $10^{-6}M$ atropine had no effect of the contractile response to $10^{-7}M$ SP. The response to $10^{-7}M$ SP was normal or subnormal in the presence of 3 mM tetraethylammonium(TEA). 5) 100k solution, $10^{-4}M$ ouabain, and Na-free solution inhibited the response to $10^{-8}M$ SP and 3 mM TEA completely, and to $10^{-7}M$ SP incompletely. 3 mM TEA induced a considerable contraction in K-free solution, but $10^{-8}M$ SP didn't induce the contraction. $10^{-6}M$ norepinephrine decreased the contractile responses to SP and TEA. 6) The contractile response to $10^{-7}M$ SP was dependent on the extracellular $Ca^{2+}$ concentrations to 1.8 mM. 7) The contractile response to $10^{-7}M$ SP remained 15% of the maximal response after bathing the ileum in a Ca-free solution for 2.5 min. 8) The responsiveness to SP was completely lost within 10 min of bathing in Ca-free solution, but was restored by the exposure to $Ca^{2+}$. The restorative effect of $Ca^{2+}$ depended on the concentration of $Ca^{2+}$, and on time for which the tissue exposed to this $Ca^{2+}$ concentration. These results suggest that there are two mechanisms of the action by which the low concentrations of substance P causes the contraction of intestinal smooth muscle: the reduction of K conductance and a mechanism dependent on the extracellular $Ca^{2+}$, and that high concentration of SP may elicit a contraction by releasing $Ca^{2+}$ from an intracellular store, which is not as sensitive to removal of extracellular $Ca^{2+}$ or as easily accessible to EGTA as the extracellular space of the muscle. The location of this store is not known; it may be associated with the internal side of the cell membrane.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.9
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• pp.512-522
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• 2003

For a time-multiplexed FPGA, a circuit is partitioned into several subcircuits, so that they temporally share the same physical FPGA device by hardware reconfiguration. In these architectures, all the hardware reconfiguration information called contexts are generated and downloaded into the chip, and then the pre-scheduled context switches occur properly and timely. Typically, the size of the chip required to implement the circuit depends on both the maximum number of the LUT blocks required to implement the function of each subcircuit and the maximum number of micro-registers to store results over context switches in the same time. Therefore, many partitioning or synthesis methods try to minimize these two factors. In this paper, we present a new estimation technique to find the lower bound on the number of micro-registers which can be obtained by any synthesis methods, respectively, without performing any actual synthesis and/or design space exploration. The lower bound estimation is very important in sense that it greatly helps to evaluate the results of the previous work and even the future work. If the estimated lower bound exactly matches the actual number in the actual design result, we can say that the result is guaranteed to be optimal. In contrast, if they do not match, the following two cases are expected: we might estimate a better (more exact) lower bound or we find a new synthesis result better than those of the previous work. Our experimental results show that there are some differences between the numbers of micro-registers and our estimated lower bounds. One reason for these differences seems that our estimation tries to estimate the result with the minimum micro-registers among all the possible candidates, regardless of usage of other resources such as LUTs, while the previous work takes into account both LUTs and micro-registers. In addition, it implies that our method may have some limitation on exact estimation due to the complexity of the problem itself in sense that it is much more complicated than LUT estimation and thus needs more improvement, and/or there may exist some other synthesis results better than those of the previous work.

• Journal of Distribution Research
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• v.17 no.3
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• pp.115-132
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• 2012

This study empirically examines the impact of SSM market entry on changes in market shares among retailing types. The data is monthly time-series data spanning over the period from January 2000 to December 2010, and the effect of SSM market entry on market shares of retailing types is analyzed by utilizing several key factors such as the number of new SSM monthly entrants, total number of SSMs, the proportion of new SSM entrant that is smaller than $165m^2$ to total new SSM entrants. According to the Korean Standard Industrial Classification codes, the retailing type is classified into 5 groups: department stores, retail sale in other non-specialized large stores(big marts), supermarkets, convenience stores, and retail sale in other non-specialized stores with food or beverages predominating (others). The market shares of retailing types are calculated by the ratio of each retailing type monthly sales to total monthly retailing sales in which total retailing sales is the sum of each retailing type sales. The empirical model controls for the size effects with the number of monthly employees for each retailing type and the macroeconomic effects with M2. The empirical model employed in this study is as follows; $$MS_i=f(NewSSM,\;CumSSM,\;employ_i,\;under165,\;M2)$$ where $MS_i$ is the market share of each retailing type (department stores, big marts), supermarkets, convenience stores, and others), NewSSM is the number of new SSM monthly entrants, CumSSM is total number of SSMs, $employ_i$ is the number of monthly employees for each retailing type, and under165 is the proportion of new SSM entrant that is smaller than $165m^2$ to total new SSM entrants. The correlation among these variables are reported in