• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.1-10
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• 2000

Spatial analysis in GIS provides an important way that helps the end-users decision-making. For such a reason, query model for analysis should be able to support the users view conceptually in constructing query statements. The traditional approaches in design of query model used to extend the functionality of model that basically designed for manipulation of attribute-operations by appending operators for spatial operations to the query statements of model. However, by the reason of spatial operation's characteristics that are different from those of attribute operations In nature, the structures of query statements in previous approaches are unnatural, inconsistent, and therefore those query models in previous approaches are not able to support the users view in retrieving analysis. In this paper, we proposed the methodology for constructing of user query and internal processing this query based on object-oriented paradigm, in the view of spatial operations by using the basic concept that spatial query is a methodology for spatial analysis. In addition, we presented a strong possibility of designing spatial query model that might actively have interaction with its user by implementing CIW(Class-Information Window) query interface corresponded with the methodology proposed in this paper.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.337-341
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• 2021

In this paper, we describe the fabrication of a paper-based enzyme-linked immunosorbent assay (ELISA) to detect polygalacturonase (PG), which is used as a biomarker to determine whether a plant is infected with a disease. The proposed paper-based ELISA can analyze the concentration of PG in a short time using a small sample compared to the traditional ELISA, which is generally performed using a well plate. To increase the resolution of the sensor, we optimized the dilution ratio of the HRP-conjugated goat anti-rabbit IgG antibody and the dilution ratio of the anti-PG and HRP-conjugated goat anti-rabbit IgG antibodies. Furthermore, for quantitative analysis of PG concentration, Delta RGB analysis was conducted to detect color changes in the sensing window displayed by the PG samples at various concentrations. Based on the experiment, the fabricated paper-based ELISA could measure at least 0.25 ㎍ of PG and the measurement range was 0.25-2 ㎍. Therefore, the paper-based ELISA for detecting PG is expected to be able to determine the presence or absence of disease in crops at the infection stage in the future.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.6
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• pp.807-813
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• 1986

Measurements of interface states in a MOS capacitor by DLTS system using wideband monophase lock-in amplifier are discussed. A new signal analysis method that takes into account the bias pulse width and the gate off width is presented to remove the errors in the measured parameters of interface states resulting from the traditional method which neglects the effect of those widths. Theoretical calculations are made for the parameters related to the rate window, signal to noise ratio, and the energy resolution. On the grounds of this discussion, interface states of the MOS capacitor on p-type substrate of (110) orentation are measured with the optimal gate-off width with respect to the S/N ratio and the energy resolution. The results are interface state density of the order of 10**10 (cm-\ulcornereV**-1) to 10**11 (cm-\ulcornereV**-1) in the energy range of Ev+0.15(dV) to Ev+0.5(eV), and constant capture cross section of the order of 10**-16 (cm\ulcorner.

• Asia pacific journal of information systems
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• v.30 no.4
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• pp.719-740
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• 2020

The stock market changes continuously as new information emerges, affecting the judgments of investors. Online news articles are valued as a traditional window to inform investors about various information that affects the stock market. This paper proposed new ways to utilize online news articles with technical indicators. The suggested hybrid model consists of three models. First, a self-attention-based convolutional neural network (CNN) model, considered to be better in interpreting the semantics of long texts, uses news content as inputs. Second, a self-attention-based, bi-long short-term memory (bi-LSTM) neural network model for short texts utilizes news titles as inputs. Third, a bi-LSTM model, considered to be better in analyzing context information and time-series models, uses 19 technical indicators as inputs. We used news articles from the previous day and technical indicators from the past seven days to predict the share price of the next day. An experiment was performed with Korean stock market data and news articles from 33 top companies over three years. Through this experiment, our proposed model showed better performance than previous approaches, which have mainly focused on news titles. This paper demonstrated that news titles and content should be treated in different ways for superior stock price prediction.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• The Journal of Korean Academic Society of Nursing Education
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• v.7 no.1
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• pp.94-112
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• 2001

The main purpose of this study was to investigate the effectiveness of a standardized patients managed instruction program for a fundamentals of nursing. The standardized patients managed instruction was evaluated by using a quasi-experimental, nonequivalent control group posttest design with two separate classes of sophomore students attending fundamentals of nursing classes at one baccaleureate nursing school in Korea. Control group was taught by traditional lecture/model instruction and experimental group was taught by standardized patient managed instruction. Data were collected from December, 1999 to July, 2000 using checklist developed by researcher on following areas; clinical nursing performance, communication skills, and learning motivation. There were 36 students in the experimental group and 40 students in the control group. Data analysis was done using SPSS WINDOW. The results were summarized as follows ; 1. Clinical nursing performances were evaluated by change position, back care and hot bag apply. The total score was statistically significant higher in the experimental group than the control group(t=3.325, p=.000). Thus hypothesis 1 was supported. 2. Communication skill was evaluated by professional attitude and ability to explain to patients. There was a statistically significant difference between the experimental group and the control group (t=4.232, p=.000). Thus hypothesis 2 was supported. 3. Learning motivation was evaluated by self-reported questionnaires. There was statistically a significant difference between the experimental group and the control group(t=3.024, p=.004). Thus hypothesis 3 was supported. In conclusion, this study suggests that standardized patients managed instruction is an effective learning method to nursing students. By utilizing a standardized patient managed instruction, learning can proceed in a more relaxed environment and reduce the risks to patients because student inexperience are avoided. It is recommended to develop more standardized patients cases for wider areas of nursing educational and evaluate the program with more students using logitudinal method.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.35 no.5
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• pp.367-371
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• 2009

Purpose: The purpose of this study was to evaluate the feasibility of the outfracture osteotomy sinus graft technique with the evaluation of 5-year survival rate of the implants placed in the atrophic edentulous posterior maxillary area. Materials and methods: One hundred and thirteen cases of 96 patients who visited our center from Aug 2004 to July 2009 and were diagnosed as atrophic edentulous maxillary alveolar ridge, were selected and underwent augmentation sinus surgery with outfracture osteotomy technique. Feasibility of the outfracture osteotomy technique was investigated with clinical and radiographic evaluation to assess the survival rate of the total dental implants in augmentation sinus surgery of this new kind. Total fixture number available in follow-up period was 179, in which the lost 10 patients were excluded out of 96 patients. Results: Five-year cumulative survival rate was 97.2% with 5 failures of total 179 fixtures. The average follow-up period was 29 and a half months, with the minimum and maximum follow-up periods of 4 months 21 days and 59 months 14 days, respectively. Conclusion: Traditional infracture technique is a popular method for an augmentation sinus surgery. The authors modified this classical method by outfracturing and readapting the bony window after sinus graft, with excellent treatment results evidenced by high survival rate of 97.2% (174 out of 179 fixtures), which proves the feasibility of the newly-designed outfracture osteotomy sinus graft technique.

• Journal of the Korean Society of Costume
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• v.53 no.8
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• pp.121-135
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• 2003

The purpose of this study is to suggest a theoretical basis to name Sa(紗) and Ra(羅) remains properly by comparing and analyzing the name, usage, value, length and width of Sa(紗) and Ra(羅) recorded on documents made at the end period of Joseon. The features of Sa(紗) and Ra(羅) at the end of the Joseon Period are as follows. 1. The kinds of Sa(紗) are about 80, those of Ra(羅) are about 12, and those of Sa(紗) are significantly more than those of Ra(羅). In regard to the aspect of patterns, there were about 20 types of patterns in the case of Sa(紗), but no specific pattern for Ra(羅). 2. Some newly revealed patterns in the case of Sa (紗) are as follows. Baek -bok-mun(백복문) was a pattern full of ‘bats(박쥐[복])’, and Baek-jeop-mun(백접문) was a pattern full of ‘butterflies(나비[蝶])’ Jeop-mun(접문) was classified into ‘butterfly patterns(나비문[접문])’ and ‘traditional window flame patterns(창살문[접문])‘. 3. When considering the usages of Sa(紗) and Ra(羅), Sa(紗) was used for various detailed purposes according to their kinds and patterns, but Ra(羅) was mostly used for underwear. The most commonly used Sa(紗) was the Gab-sa type(甲紗類). On the contrary, the Go-sa type(庫紗類) was significantly less used than the Gab-sa type(甲紗類). However, it must have been of relatively high quality Sa(紗), shown by the fact that it was used for outer garments. In addition, the Gung-sa type(宮紗類) was the best quality Sa(紗), shown by the fact that it was used for court dress and official uniforms in the royal court. 4. Sa(紗) and Ra(羅) whose features have been examined we Gapsa(甲紗), Sun-in (純仁), Gosa(庫紗), Gwansa(官紗), Jusa(走紗), Eunjosa(은조사), Gwangsa(廣紗), Waesa(倭紗), Dorisa(도리사), Gong-yangsa(공양사), Rasa(羅紗), Danghangra(唐亢羅), Yanghangra(洋亢羅), Yunjura(윤주라), Eunra(銀羅), Jeohangra(저항라), Chura(秋羅). 5. Regarding the values of Sa(紗) and Ra(羅), they were high quality textures and its length and width of 1 Pil(疋), a roll of cloth, were not subdivided in detail such as in the case of plain weaved silks(平絹).

• Journal of the Korean Institute of Educational Facilities
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• v.24 no.6
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• pp.37-44
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• 2017

This study is about user satisfaction of the Junior College Library based on its characteristics of space composition. For this, we studied characteristics of space composition targeting the libraries in colleges in Seoul and Gyeonggi-do. First, in case of study of characteristics of space composition for books and library data, student satisfaction for traditional and normal library areas was high. It means that the service based on library areas should start from normal library areas as well as there is a change about space as the type of data in libraries change to electric data and multimedia. Second, If we look at the space for a reader and a user, satisfaction for a normal reading room was high. we can also see that satisfaction for a computer room and a multimedia reading room was not higher but still high. Also, the reason why satisfaction for a multimedia reading room that provides various activities was high was that the complex of a library space is needed to provide users with various activities. Third, in case of space for programme function and meeting, satisfaction for the room of video information and the group study room was high. we can see that user satisfaction for the space got high basically when a user is satisfied with the proper information technology based on interaction Fourth, as a result of variance analysis of 3 spaces of Junior College Library and the services, the size of the space of service does not influence user satisfaction directly. Even the space is small, if it decorates variously like with a lighting for a user, a window seat to meet the nature of users and has specific factors such as space reservation using internet, user satisfaction is high. If we summarise the result of this study, to make user satisfaction for speace in a Junior College Library higher, not just we need to try to make it extend as a educational, a cultural place but we also need to accept the student's requirement that the space also needs to be extend as a complex cultural space.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.354-361
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• 2011

Increasing interest and technological advances in smart home has led to active research on context-awareness service and prediction algorithms such as Bayesian Networks, Tree-Dimensional Structures and Genetic prediction algorithms. Context-awareness service presents that providing automatic customized service regarding individual user's pattern surely helps users improve the quality of life. However, it is difficult to implement context-awareness service because the problems are that handling coincidence with context information and exceptional cases have to consider. To overcome this problem, we proposes an Intelligent Sequential Matching Algorithm(ISMA), models context-awareness service using Timed Petri-net(TPN) which is petri-net to have time factor. The example scenario illustrates the effectiveness of the Timed Petri-net model and our proposed algorithm improves average 4~6% than traditional in the accuracy and reliability of prediction.