• Advances in Traditional Medicine
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• v.7 no.5
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• pp.556-563
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• 2008

Peripheral nerve injuries are a commonly encountered clinical problem and often result in a chronic pain and severe functional deficits. The expression of c-Fos is sometimes used as a marker of increased neuronal activity. We have prepared the aqueous extract of amygdalin from Armeniacae semen for pain control. In the present study, we investigated the effects of amygdalin on the recovery rate of the locomotor function and on the expression of c-Fos in the ventrolateral periaqueductal gray (vlPAG) region following sciatic crushed nerve injury in rats. Walking track analysis for the evaluation of functional recovery and immunohistochemistry for the c-Fos expression were used in this study. In the present results, characteristic gait change with dropping of the sciatic function index (SFI) was observed and c-Fos expression in the vlPAG was suppressed following sciatic crushed nerve injury in rats. Amygdalin enhanced SFI value and restored c-Fos expression in the vlPAG to the control value. The present our study indicated that amygdalin activates neurons in the vlPAG, and it facilitates functional recovery following peripheral nerve injury.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.385-395
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• 2005

Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.6
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• pp.296-305
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• 2005

TCP/IP, the most popular communication protocol, is processed on a host CPU in traditional computer systems and this imposes enormous loads on the host CPU. Recently TCP/IP Offload Engine (TOE) technology, which processes TCP/IP on a network adapter instead of the host CPU, becomes an important way to solve the problem. In this paper we analysed the structure of a TCP/IP protocol stack in the Linux operating system and important factors, which cause a lot of loads on the host CPU, by measuring the time spent on processing each function in the protocol stack. Based on these analyses, we propose a Hybrid TOE architecture, in which functions imposing much loads on the host CPU are implemented using hardware and other functions are implemented using software.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.1-14
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• 2005

It is difficult to identify reusable and independent components in component-based development(CBD) process. Therefore existing methodologies have dealt the problem of component identification based on only developer's intuition and heuristics. As a result, it is difficult to identify the business components by common developers. Therefore, in this paper, we propose a new baseline and technique to identify the business components based on domain model such as use case diagrams, class diagrams, and sequence diagrams. proposed method identifies components through two phases; system component identification and business component identification. Especially, we consider structural characteristics as well as dependency characteristics according to methods call types and directions in identifying components. We also present a case study and comparative analysis and assessment to prove the practical use of our technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6860-6868
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• 2015

In this study, we consider a problem of forecasting daily city gas demand of Korea. Forecasting daily gas demand is a daily routine for gas provider, and gas demand needs to be forecasted accurately in order to guarantee secure gas supply. In this study, we analyze the time series of city gas demand in several ways. Data analysis shows that primary factors affecting the city gas demand include the demand of previous day, temperature, day of week, and so on. Incorporating these factors, we developed a multiple linear regression model. Also, we devised a sampling procedure that selectively collects the past data considering the characteristics of the city gas demand. Test results on real data exhibit that the MAPE (Mean Absolute Percentage Error) obtained by the proposed method is about 2.22%, which amounts to 7% of the relative improvement ratio when compared with the existing method in the literature.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4543-4549
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Burr distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.148-153
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• 2015

In our domestic software industries, it is focused on such a high quality development/ testing process, maturity measurement, and so on. But the real industrial fields are still working on a code-centric development. Most of the existing legacy systems did not keep the design and highly increased the code complexity with more patching of the original codes. To solve this problem, we adopt a code visualization technique which is important to reduce the code complexity among modules. To do this, we suggest a tool chaining method based on the existing open source software tools, which extends NIPA's Software Visualization techniques applied to procedural languages. In addition, it should be refactored to fix bad couplings of the quality measurement indicators within the code visualization. As a result, we can apply reverse engineering to the legacy code, that is, from programming via model to architecture, and then make high quality software with this approach.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.323-328
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• 2006

Proteins in a cell appear as spots in a two dimensional gel image which is used in protein analysis. The spots from the same protein are in near position when comparing two gel images. Finding out the different proteins between a normal tissue and a cancer one is important information in drug development. Automatic matching of gel images is difficult because they are made from biological experimental processes. This matching problem is known to be NP-hard. Neural networks are usually used to solve such NP-hard problems. Hopfield neural network is selected since it is appropriate to solve the gel matching. An energy function with location and distance parameters is defined. The two spots which make the energy function minimum are matching spots and they came from the same protein. The energy function is designed to reflect the topology of spots by examining not only the given spot but also neighborhood spots.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1127-1136
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• 2003

Estimation of software project cost, effort and duration in the early stage of software development cycle is a difficult and key problem in software engineering. Most of models estimate the development effort using the function point that is measured from the requirement specification. This paper presents optimal team size and duration prediction based on function point in order to provide information that can be used as a guide in selecting the most Practical and productive team size for a software development project. We introduce to productive metrics and cost for decision criteria of ideal team size and duration. The experimental is based on the analysis of 300 development and enhancement software project data. These data sets are divide in two subgroups. One is a development project; the other is a maintenance project. As a result of evaluation by productivity and cost measured criteria in two subgroups, we come to the conclusion that the most successful projects has small teams and minimum duration. Also, I proposed that predictive model for team sire and duration according to function point size based on experimental results. The presented models gives a criteria for necessary team site and duration according to the software size.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.62-68
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• 2018

This study was conducted to improve the shooting stability of self propelled artillery by improving the flick rammer system. The flick rammer system is designed to reduce crew fatigue and shorten the movement and loading time of the shell compared with the conventional manual loading system. Basically, in the flick rammer system of the shooting type, fall-back occurs intermittently, which causes problems in the rapid loading. To solve this problem, a detailed C.A.E. (Computer Aided Engineering) analysis of the internal structure of the existing rapid loading field was conducted. Through this, we sought a solution that can prevent fall-back by reducing the flying distance. We then optimized the loading station to reduce the flying distance and confirmed the possibility of suppressing the fall-back compared to the existing product through actual tests in the field.