• Journal of Life Science
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• v.25 no.11
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• pp.1214-1222
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• 2015

The purpose of this study was to determine the effect of Pueraria lobate-root based combination supplementation containing Rehmannia glutinosa and exercise on histone modification in ovariectomized rat hindlimb skeletal muscle. Sixty rats were fed with high fat diet and randomly assigned into the following groups for 8 weeks: 1)HSV; High fat+Sedentary+Vehicle, 2)HSP; High fat+Sedentary+PR, 3)HSH; High fat+Sedentary+Estradiol, 4)HEV; High fat+Ex+Vehicle, 5)HEP; High fat+Ex+PR, 6)HEH; High fat+Ex+Estradiol. Exercise consisted of low intensity treadmill exercise(1-4th wk:15 m/min for 30 min, 5-8th wk: 18 m/min for 40 min, 5 times/week). The result of this study showed that exercise and Pueraria and Rehmannia glutinosa intake suppressed weight gain. Furthermore, exercise and Pueraria and Rehmannia glutinosa intake increased muscle mass. This study observed H3K9 acetylation and demethylation in plantaris muscle in exercised group, but no difference in soleus muscle. To test whether the decrease in HDAC4, HDAC5 and G9a mRNA levels after exercise and Pueraria/Rehmannia glutinosa intake, HDAC4, HDAC5 and G9a mRNA levels were determined by real-time PCR. Only exercise induced HDAC5 and G9a mRNA reduction in plantaris muscle, but not in soleus muscle. In conclusion, these data demonstrates that exercise and Pueraria/Rehmannia glutinosa intake effect on body compositions. These changes are regulated by epigenetic modifications, such as histone acetylation and methylation. Future studies should focus on gene-specific epigenetics and other epigenetic mechanism for Pueraria/Rehmannia glutinosa intake.

• Women's Health Nursing
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• v.6 no.2
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• pp.234-257
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• 2000

At present in the medical care, the study and effort for producing health service to consider efficiency, effectiveness, and quality are urgently called for because of the difficulty in the keen competition according to the inter- nationalization and opening, the operation in the medical institution service testing system, the change in the medical policy of KDRGs, and the lack of the health care cost increasing rate. As an alternative, the case management for the new management system is introduced in the U.S., and the Critical Pathway that is the method designing the contents of activity and its result has been developed and applied in order to anticipate and manage the patient-outcome for the realization of the cost-effective case-management. Thus, this study intended to analyze the effectiveness to obtain by developing the Critical Pathway presented as the method to improve the quality-betterment and cost effectiveness through the continuous and consistent patient management for the hysterectomy patient and applying it to the real practice. As a study method, this author formed a conceptual framework through considering five Critical Pathway used in the current U.S. and three Critical Pathway presented in the literature to develop the Critical Pathway for the hysterectomy patient, and made out the preliminary Critical Pathway through reviewing the old chart. This author made the verified the validity of the expert group about the developed Critical Pathway, and to confirm the possibility of practice application, completed and settled the final Critical Pathway after using the Critical Pathway to the hysterectomy patient from March 1st to 15th, 1997. Finally, to analyze the application-effect of the developed Critical Pathway, this author offered health care service applying the Critical Pathway to the hysterectomy patient from April 15th to August 31th, 1997. The guide for the Critical Pathway was carried out in advance by outpatient setting nurse for outpatient setting visit before the operation, and after hospitalization the primary nurse monitored the execution degree on the every duty. After discharge this author surveyed the complication through phone visiting, and one month after discharge surveyed the patient's reaction about the offered service when outpatient setting visit and analyzed the result. The source for health care cost was obtained by the statistics about the hospital charge which was offered by the General Business Department. The results were as follows. 1. It was decided that the vertical line of the Critical Pathway was made up of eight items such as monitoring/assessment, treatment, line/drains, activity, medication, lab test, diet, patient teaching, and the horizontal line of the Critical Pathway was made up of from hospitalization to discharge. 2. After the analysis of service contents through reviewing the old chart, it was decided that the horizontal line of the preliminary Critical Pathway was made up of from hopitalization to fourth postoperative day, and the vertical line of it was divided into eight items which were the contents to occur with the time frame of the horizontal line. 3. After the verifying the validity of the expert group about the preliminary Critical Pathway, the horizontal line was amended from hopitalization to third postoperative day, and taking their consensus, some contents of the horizontal line was amended and deleted. 4. From March 1st to 15th, 1997, to confirm the clinical suitability, this author offered eight hysterectomy patients the medical service through the Critical Pathway. The result was that three of them could be discharged at the expected discharge day, and the others later than that day. Supplementing the preliminary Critical Pathway through analyzing the cause of that delay- case, this author developed the final Critical Pathway. 5. There were no significant differences between the experimental and the control group in the incidence of complication(P > 0.05). 6. The 92.4% of experimental group was satisfied with the Critical Pathway service. 7. The length of hospital stay of the experimental group offered with the Critical Pathway service was 4.6 days and there was a significant difference that it was 1.3 days shorter than that of the control group(t=-29.514, P=0.000). 8. There wsa a significant difference that the mean medical charge per one patient of the experimental group offered the Critical Pathway service was cheaper \124,150 than that of the control group(t=-9.826, P=0.000). 9. The result that the author assumed and analyzed hospital income with the rate of turning bed was assumed that the increase of hospital income was \63,245,072 for that study, and the income increase was expected with \68,704,864 for a year. The result that this author applied the Critical Pathway to the hysterectomy patient have no differences in the incidence of complication, high satisfaction with that service, and the length of hospital stay decreased in the experimental group, and the mean hospital charge per one patient decreased, but hospital income increased. Suggestions for further study and nursing practice are as follows. 1. The study to apply the Critical Pathway for a year, verify the validity, and measure the effect repeatedly is needed. 2. To apply and manage the Critical Pathway effectively, the study to computerize it is needed. 3. The study to develop hospital-based Critical Pathway about other diseases or procedure, and measure the effect is needed.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.145-157
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• 2004

The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.117-137
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• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.441-450
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• 2014

The stock market is constantly changing and sometimes the stock prices unaccountably plummet or surge. So, the stock market is recognized as a complex system and the change on the stock prices is unpredictable. Recently, many researchers try to understand the stock market as the network among individual stocks and to find a clue about the change of the stock prices from big data being created in real time from Internet. We focus on the correlation between the stock prices and the human interactions in Internet especially in the stock message boards. To uncover this correlation, we collected and investigated the articles concerning with 57 target companies, members of KOSPI200. From the analysis result, we found that there is no significant correlation between the stock prices and the article volume, but the strength of correlation between the article volume and the stock prices is relevant to the stock return. We propose a new method for recommending stock portfolio base on the result of our analysis. According to the simulated investment test using the article data from the stock message boards in 'Daum' portal site, the returns of our portfolio is about 1.55% per month, which is about 0.72% and 1.21% higher than that of the Markowitz's efficient portfolio and that of the KOSPI average respectively. Also, the case using the data from 'Naver' portal site, the stock returns of our proposed portfolio is about 0.90%, which is 0.35%, 0.40%, and 0.58% higher than those of our previous portfolio, Markowitz's efficient portfolio, and KOSPI average respectively. This study presents that collective human behavior on Internet stock message board can be much helpful to understand the stock market and the correlation between the stock price and the collective human behavior can be used to invest in stocks.

• Journal of Soil and Groundwater Environment
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• v.7 no.4
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• pp.77-86
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• 2002

Surfactant enhanced in-situ soil flushing was performed to remediate the soil and groundwater at an oil contaminated site, where had been used as a military vehicle repair area for 40 years. A section from the contaminated site (4.5 m $\times$ 4.5 m $\times$ 6.0 m) was selected for the research, which was composed of heterogeneous sandy and silt-sandy soils with average $K_d$ of 2.0$\times$$10^{-4}$cm/sec. Two percent of sorbitan monooleate (POE 20) and 0.07% of iso-prophyl alcohol were mixed for the surfactant solution and 3 pore volumes of surfactant solution were injected to remove oil from the contaminated section. Four injection wells and two extraction wells were built in the section to flush surfactant solution. Water samples taken from extraction wells and the storage tank were analyzed on a gas-chromatography (GC) for TPH concentration in the effluent with different time. Five pore volumes of solution were extracted while TPH concentration in soil and groundwater at the section were below the Waste Water Discharge Limit (WWDL). The effluent TPH concentration from wells with only water flushing was below 10 ppm. However, the effluent concentration using surfactant solution flushing increased to 1751 ppm, which was more than 170 times compared with the concentration with only water flushing. Total 18.5 kg of oil (TPH) was removed from the soil and groundwater at the section. The concentration of heavy metals in the effluent solution also increased with the increase of TPH concentration, suggesting that the surfactant enhanced in-situ flushing be available to remove not only oil but heavy metals from contaminated sites. The removal efficiency of surfactant enhanced in-situ flushing was investigated at the real contaminated site in Korea. Results suggest that in-situ soil flushing could be a successful process to remediate contaminated sites distributed in Korea.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.347-357
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• 2003

This paper describes on the suppression of sea clutter on marine radar display using a cell-averaging CFAR(constant false alarm rate) technique, and on the analysis of radar echo signal data in relation to the estimation of ARPA functions and the detection of the shadow effect in clutter returns. The echo signal was measured using a X -band radar, that is located on the Pukyong National University, with a horizontal beamwidth of $$3.9^{\circ}$$, a vertical beamwidth of $20^{\circ}$, pulsewidth of $0.8 {\mu}s$ and a transmitted peak power of 4 ㎾ The suppression performance of sea clutter was investigated for the probability of false alarm between $l0-^0.25;and; 10^-1.0$. Also the performance of cell averaging CFAR was compared with that of ideal fixed threshold. The motion vectors and trajectory of ships was extracted and the shadow effect in clutter returns was analyzed. The results obtained are summarized as follows；1. The ARPA plotting results and motion vectors for acquired targets extracted by analyzing the echo signal data were displayed on the PC based radar system and the continuous trajectory of ships was tracked in real time. 2. To suppress the sea clutter under noisy environment, a cell averaging CFAR processor having total CFAR window of 47 samples(20+20 reference cells, 3+3 guard cells and the cell under test) was designed. On a particular data set acquired at Suyong Man, Busan, Korea, when the probability of false alarm applied to the designed cell averaging CFAR processor was 10$^{-0}$.75/ the suppression performance of radar clutter was significantly improved. The results obtained suggest that the designed cell averaging CFAR processor was very effective in uniform clutter environments. 3. It is concluded that the cell averaging CF AR may be able to give a considerable improvement in suppression performance of uniform sea clutter compared to the ideal fixed threshold. 4. The effective height of target, that was estimated by analyzing the shadow effect in clutter returns for a number of range bins behind the target as seen from the radar antenna, was approximately 1.2 m and the information for this height can be used to extract the shape parameter of tracked target..

• Journal of Genetic Medicine
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• v.8 no.1
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• pp.1-16
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• 2011

Owing to the risk of fetal loss associated with prenatal diagnostic procedures (amniocentesis, chorionic villus sampling), noninvasive prenatal diagnosis (NIPD) is ultimate goal of prenatal diagnosis. The discovery of circulating cell-free fetal DNA (cffDNA) in maternal plasma in 1997 has opened up new probabilities for NIPD by Dr. Lo et al. The last decade has seen great development in NIPD. Fetal sex and fetal RhD status determination by cffDNA analysis is already in clinical use in certain countries. For routine use, this test is limited by the amount of cell-free maternal DNA in blood sample, the lack of universal fetal markers, and appropriate reference materials. To improve the accuracy of detection of fetal specific sequences in maternal plasma, internal positive controls to confirm to presence of fetal DNA should be analyzed. We have developed strategies for noninvasive determination of fetal gender, and fetal RhD genotyping using cffDNA in maternal plasma, using real-time quantitative polymerase chain reaction (RT-PCR) including RASSF1A epigenetic fetal DNA marker (gender-independent) as internal positive controls, which is to be first successful study of this kind in Korea. In our study, accurate detection of fetal gender through gestational age, and fetal RhD genotyping in RhD-negative pregnant women was achieved. In this assay, we show that the assay is sensitive, easy, fast, and reliable. These developments improve the reliability of the applications of circulating fetal DNA when used in clinical practice to manage sex-linked disorders (e.g., hemophilia, Duchenne muscular dystrophy), congenital adrenal hyperplasia (CAH), RhD incompatibility, and the other noninvasive pregnant diagnostic tests on the coming soon. The study was the first successful case in Korea using cffDNA in maternal plasma, which has created a new avenue for clinical applications of NIPD.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.