• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.349-358
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• 2024

This study conducted a literature analysis to examine the overall trend of speech-language pathology in discourse research, focusing on studies on the topic of discourse from 2010 to 2023. Twenty-five papers were selected and analyzed in terms of research status, research subjects (age and subject type), and research methods (type and task). As a result, first, looking at the annual status of discourse research, it was confirmed that it is increasing starting from 2015 compared to 2010 to 2014. Second, the age of the research subjects and the types of experimental and control groups in the experimental study were examined. First, when analyzing the age of the subjects, research was actively conducted on school-age subjects (12 studies, 48.00%). When looking at the analysis of the types of experimental group subjects, the Normal group was the most (4 studies (19.04%)), and the control group subject type was also conducted with Normal as the control group (13 studies (61.90%)). It was the most. Third, in the analysis of research methods, it was found that the research type was very biased towards experimental studies, with 21 studies (84.00%). The type of research in terms of time was cross-sectional studies, which accounted for a high proportion of 21 studies (84.00%), and the research project used to evaluate discourse ability with a high proportion was discourse production, with a total of 12 studies (48.00%). This study comprehensively looked at discourse-related research related to language development and language disorders and sought to identify recent trends and the direction in which discourse-related research should move. The analysis of this study was limited to domestic papers. In follow-up research, we hope to understand the flow of research and discuss it, including overseas research related to discourse.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Journal of Physiology & Pathology in Korean Medicine
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• v.17 no.1
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• pp.1-24
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• 2003

This study was done to compile 104 experimental theses which are related to the antitumor and immuno-activating therapies between February 1990 through February 2002. Master's and doctoral theses were dassified by schools, degrees, materials, effects, experimental methods of antitumor and immunoactivity, and results. The following results were obtained from this study : 1. Classifying the theses by the school, 34.6% were presented by Daejeon University, 29.8% by Kyung-hee University and 11.5% by Won-kwang University. Of all theses, 51.0% were aimed for the doctoral degree and 43.3% were for the master's degree. All of three universities have their own cancer centers. 2. Classifying the theses by herb materials, complex prescription accounted for 60.3%, single herb accounted for 24.8% and herbal acupuncture accounted for 14.2%. Considering the key principles of the traditional medicine, complex prescription was much more thoroughly studied than single herb prescription. The results showed that the complex prescription had both antitumor activity and immuno-activating activity, which might reflects on multi-activation mechanisms by complex components. 3. Classifying the theses by the efficacy of herbs examined, in single herb, invigorating spleen and supplementing was 35.5%, expelling toxin and cooling was 29.0%, activating blood flow and removing blood stasis was 12.9%. In herbal acupuncture, invigorating spleen and supplementing was 52.9%, expelling toxin and cooling was 29.4%. In complex prescription, pathogen-free status was 41.9%, strengthening healthy qi to eliminate pathogen was 35.5%, strengthening healthy qi was 22.6%. It is presumed that the antitumor and immunoactivating therapy based on syndrome differentiation is the best way to develop oriental oncology. 4. Classifying the theses by antitumor experiments, cytotoxic effect was 48.1 %, survival time was 48.1 % and change of tumor size was 42.3%. Survival rate was not necessarily correlated with cytotoxicity. These data reflect the characteristic, wholistic nature of the oriental medicine which is based on BRM (biological response modifier). 5. Classifying the theses by immunoactivating experiments, hemolysin titer was 51.0%, hemagglutinin titer was 46.2% and NK cell's activity was 44.2%. In the future studies, an effort to elucidate specific molecular and cellular mechanisms of cytokine production in the body would be crucial. 6. Classifying the theses according to the data in terms of antitumor activity, 50% was evaluated good, 24.0% was excellent, and 15.5% have no effect. In an evaluation of immuno-activating activity, 35.9% was excellent and 18.0% showed a little effect. The index point, as described here, may helps to use experimental data for clinical trials. Changes in index points by varying dosage implicate the importance of oriental medical theory for prescription. 7. In 167 materials, IIP (immunoactivating index point, mean : 3.12±0.07) was significantly higher than AIP(antitumor index point, mean : 2.83±0.07). These data demonstrate that the effect of herb medicine on tumor activity depends more on immunoactivating activity than antitumor activity. This further implies that the development of herbal antitumor drugs must be preceded by the mechanistic understanding of immunoactivating effect. 8. After medline-searching tumor and herb-related articles from NCBI web site, we conclude that most of the studies are primarily focused on biomolecular mechanisms and/or pathways. Henceforth, we need to define the biomolecular mechanisms and/or pathways affected by herbs or complicated prescriptions. 9. Therefore, the most important point of oriental medical oncology is to conned between experimental results and clinical trials. For the public application of herbal therapy to cancer, it is critical to present the data to mass media. 10. To develop the relationship of experimental results and clinical trials, university's cancer clinic must have a long-range plan related to the university laboratories and, at the same time, a regular consortium for this relationship is imperative. 11. After all these efforts, a new type herbal medicine for cancer therapy which is to take care of the long-term administering and safety problem must be developed. Then, it would be expected that anti-tumor herbal acupuncture can improve clinical symptoms and quality of life (QOL) for cancer patients. 12. Finally, oriental medical cancer center must be constructed in NCC (National Cancer Center) or government agency for the development of oriental medical oncology which has international competitive power.

• Journal of the Korea Organic Resources Recycling Association
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• v.16 no.2
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• pp.74-80
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• 2008

Removal of nitrogen compound under nitrification related with denitrification by biofilm which developed on the porous media was investigated. With the investigation of $NH_4-N$ nitrification and autotrophic denitrification supplied with sulfur media as electron donor, conclusions were retrieved as follows. When $F/M_N$ ratio of $NH_4-N$ was increased from $0.0062-0.034gNH_4-N/g\;MLVSS{\cdot}day$ by the change of influent concentration and HRT the nitrification rate decreased as the increase of loading rate. Also under the same conditions of $F/M_N$ ratio, the alkalinity consumption rate of operation was higher at 8 hours of HRT than at 6 hours of HRT. Accordingly the influent loading rate variation by detention time with influent flow influenced more on the nitrification efficiency than the influent loading rate variation by the influent concentration did. Denitrification rate with various EBCT(Empty Bed Contact Time) showed average 25% at 8.4hrs of EBCT but sharply decreased average 5% at 4.6hrs of EBCT, so the operation would be more effective at above 8.4hrs of EBCT. Also denitrification rate was known to be adversely increased as $NO_3-N$ loading rate per unit volume of sulfur-media was decreased within the range of $0.5{\sim}2.0kgNO_3-N/m^3{\cdot}day$.

• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.147-165
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• 1992

This paper analyzes the macroeconomic effects of elections on the Korean economy and their future ramifications. It measures the shocks to the Korean economy caused by elections by taking the average of sample forecast errors from four major elections held in the 1980s. The seven variables' Bayesian Vector Autoregression Model which includes the Monetary Base, Industrial Production, Consumption, Consumer Price, Exports, and Investment is based on the quarterly time series data starting from 1970 and is updated every quarter before forecasts are made for the next quarter. Because of this updating of coefficients, which reflects in part the rapid structural changes of the Korean economy, this study can capture the shock effect of elections, which is not possible when using election dummies with a fixed coefficient model. In past elections, especially the elections held in the 1980s, $M_2$ did not show any particular movement, but the currency and base money increased during the quarter of the election was held and the increment was partly recalled in the next quarter. The liquidity of interest rates as measured by corporate bond yields fell during the quarter the election and then rose in the following quarter, which is somewhat contrary to the general concern that interest rates will increase during election periods. Manufacturing employment fell in the quarter of the election because workers turned into campaigners. This decline in employment combined with voting holiday produce a sizeable decline in industrial production during the quarter in which elections are held, but production catches up in the next quarter and sometimes more than offsets the disruption caused during the election quarter. The major shocks to price occur in the previous quarter, reflecting the expectational effect and the relaxation of government price control before the election when we simulate the impulse responses of the VAR model, imposing the same shocks that was measured in the past elections for each election to be held in 1992 and assuming that the elections in 1992 will affect the economy in the same manner as in the 1980s elections, 1992 is expected to see a sizeable increase in monetary base due to election and prices increase pressure will be amplified substantially. On the other hand, the consumption increase due to election is expected to be relatively small and the production will not decrease. Despite increased liquidity, a large portion of liquidity in circulation being used as election funds will distort the flow of funds and aggravate the fund shortage causing investments in plant and equipment and construction activities to stagnate. These effects will be greatly amplified if elections for the head of local government are going to be held this year. If mayoral and gubernatorial elections are held after National Assembly elections, their effect on prices and investment will be approximately double what they normally will have been have only congressional and presidential elections been held. Even when mayoral and gubernatorial elections are held at the same time as congressional elections, the elections of local government heads are shown to add substantial effects to the economy for the year. The above results are based on the assumption that this year's elections will shock the economy in the same manner as in past elections. However, elections in consecutive quarters do not give the economy a chance to pause and recuperate from past elections. This year's elections may have greater effects on prices and production than shown in the model's simulations because campaigners' return to industry may be delayed. Therefore, we may not see a rapid recall of money after elections. In view of the surge in the monetary base and price escalation in the periods before and after elections, economic management in 1992 should place its first priority on controlling the monetary aggregate, in particular, stabilizing the growth of the monetary base.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.86-90
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• 2012

Purpose: Quantification of myocardial blood flow (MBF) using dynamic PET imaging has the potential to assess coronary artery disease. Rb-82 plays a key role in the clinical assessment of myocardial perfusion using PET. However, MBF could be overestimated due to the underestimation of left ventricular input function in the beginning of the acquisition when the scanner has non-linearity between count rate and activity concentration due to the scanner dead-time. Therefore, in this study, we evaluated the count rate linearity as a function of the activity concentration in PET data acquired in list mode. Materials & methods: A cylindrical phantom (diameter, 12 cm length, 10.5 cm) filled with 296 MBq F-18 solution and 800 mL of water was used to estimate the linearity of the Biograph 40 True Point PET/CT scanner. PET data was acquired with 10 min per frame of 1 bed duration in list mode for different activity concentration levels in 7 half-lives. The images were reconstructed by OSEM and FBP algorithms. Prompt, net true and random counts of PET data according to the activity concentration were measured. Total and background counts were measured by drawing ROI on the phantom images and linearity was measured using background correction. Results: The prompt count rates in list mode were linearly increased proportionally to the activity concentration. At a low activity concentration (<30 kBq/mL), the prompt net true and random count rates were increased with the activity concentration. At a high activity concentration (>30 kBq/mL), the increasing rate of the prompt net true rates was slightly decreased while the increasing rate of random counts was increased. There was no difference in the image intensity linearity between OSEM and FBP algorithms. Conclusion: The Biograph 40 True Point PET/CT scanner showed good linearity of count rate even at a high activity concentration (~370 kBq/mL).The result indicates that the scanner is useful for the quantitative analysis of data in heart dynamic studies using Rb-82, N-13, O-15 and F-18.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10407-10412
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• 2015

Background: ${\beta}$-elemene, extracted from herb medicine Curcuma wenyujin has potent anti-tumor effects in various cancer cell lines. However, the activity of ${\beta}$-elemene against glioma cells remains unclear. In the present study, we assessed effects of ${\beta}$-elemene on human glioma cells and explored the underlying mechanism. Materials and Methods: Human glioma U87 cells were used. Cell proliferation was determined with MTT assay and colony formation assay to detect the effect of ${\beta}$-elemene at different doses and times. Fluorescence microscopy was used to observe cell apoptosis with Hoechst 33258 staining and change of glioma apoptosis and cell cycling were analyzed by flow cytometry. Real-time quantitative PCR and Western-blotting assay were performed to investigated the influence of ${\beta}$-elemene on expression levels of Fas/FasL, caspase-3, Bcl-2 and Bax. The experiment was divided into two groups: the blank control group and ${\beta}$-elemne treatment group. Results: With increase in the concentration of ${\beta}$-elemene, cytotoxic effects were enhanced in the glioma cell line and the concentration of inhibited cell viability ($IC_{50}$) was $48.5{\mu}g/mL$ for 24h. ${\beta}$-elemene could induce cell cycle arrest in the G0/G1 phase. With Hoechst 33258 staining, apoptotic nuclear morphological changes were observed. Activation of caspase-3,-8 and -9 was increased and the pro-apoptotic factors Fas/FasL and Bax were upregulated, while the anti-apoptotic Bcl-2 was downregulated after treatment with ${\beta}$-elemene at both mRNA and protein levels. Furthermore, proliferation and colony formation by U87 cells were inhibited by ${\beta}$-elemene in a time and does-dependent manner. Conclusions: Our results indicate that ${\beta}$-elemene inhibits growth and induces apoptosis of human glioma cells in vitro. The induction of apoptosis appears to be related with the upregulation of Fas/FasL and Bax, activation of caspase-3,-8 and -9 and downregulation of Bcl-2, which then trigger major apoptotic cascades.

• Clinical and Experimental Pediatrics
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• v.49 no.4
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• pp.417-423
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• 2006

Purpose : The objectives of this study were to assess ventricular function by tissue Doppler imaging in children who were receiving chemotherapy or who had received chemotherapy, and to apply repeated tissue Doppler imaging to make an early assessment in cardiac toxicity studies. Methods : This study was conducted on 23 oncology patients on-treatment or off-treatment from April 2005 to July 2005 at Dongsan Medical Center, Keimyung University. All patients(group 1) were divided into two groups, fractional shortening(FS) over 29 percent(group 2) and FS under 28 percent (group 3) in the first category. These same patients were also divided into the following groups : group treated with anthracyclin(group 4) and group treated without anthracyclin(group 5). Deceleration time(DT), isovolumic relaxation time(IVRT), FS, peak early diastolic(E), and peak late diastolic (A) velocity of transmitral flow were measured by M-mode and pulsed wave Doppler. Systolic(Sm), peak early diastolic(Em), and peak late diastolic(Am) velocity in apical 4-chamber and 2-chamber views were measured by tissue Doppler imaging. The author calculated a modified Tei index, E/A, E/Em ratio by using measured values. Results : Twenty three patients were enrolled : 12 boys and 11 girls. The average age of patients was 8 years and 4 months. Thirteen out of 23 patients were in the group treated with anthracyclin (group 4) and 6 had FS under 28 percent(group 3). E/Em ratio showed a significant difference between group 1 and control group($6.46{\pm}1.85$ vs $7.06{\pm}1.64$, P<0.05). Other parameters had no difference statistically. Conclusion : This study showed that the change of cardiac function developed earlier in diastolic function than in systolic function, as E/Em ratio reflecting the mean LV diastolic pressure showed a significant difference between the control group and chemotherapy groups. Echocardiography using tissue Doppler imaging is a non-invasive, comfortable and reliable method for post-chemotherapy follow up.