• The Journal of Korean Academy of Prosthodontics
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• v.57 no.2
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• pp.102-109
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• 2019

Purpose: The purpose of this study was to evaluate the accuracy of three types of intraoral scanners and the accuracy of the single abutment and bridge abutment model. Materials and methods: In this study, a single abutment, and a bridge abutment with missing first molar was fabricated and set as the reference model. The reference model was scanned with an industrial three-dimensional scanner and set as reference scan data. The reference model was scanned five times using the three intraoral scanners (CS3600, CS3500, and EZIS PO). This was set as the evaluation scan data. In the three-dimensional analysis (Geomagic control X), the divided abutment region was selected and analyzed to verify the scan accuracy of the abutment. Statistical analysis was performed using SPSS software (${\alpha}=.05$). The accuracy of intraoral scanners was compared using the Kruskal-Wallis test and post-test was performed using the Pairwise test. The accuracy difference between the single abutment model and the bridge abutment model was analyzed by the Mann-Whitney U test. Results: The accuracy according to the intraoral scanner was significantly different (P < .05). The trueness of the single abutment model and the bridge abutment model showed a statistically significant difference and showed better trueness in the single abutment (P < .05). There was no significant difference in the precision (P = .616). Conclusion: As a result of comparing the accuracy of single and bridge abutments, the error of abutment scan increased with increasing scan area, and the accuracy of bridge abutment model was clinically acceptable in three types of intraoral scanners.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.366-375
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• 2019

This experiment aims to determine the proper irrigation scheduling based on a whole-substrate capacitance using a newly developed device (SCMD) by comparing with the integrated solar radiation automated irrigation system (ISR) and sap flow sensor automated irrigation system (SF) for the cultivation of tomato (Solanum lycopersicum L. 'Hoyong' 'Super Doterang') during spring to winter season. For the SCMD system, irrigation was conducted every 10 minutes after the first irrigation was started until the first run-off was occurred, of which the substrate capacitance was considered to be 100%. When the capacitance threshold (CT) was reached to the target point, irrigation was re-conducted. After that, when the target drain volume (TDV) was occurred, the irrigation stopped. The irrigation volume per event for the SCMD was set to 50, 75, or 100 mL at CT 0.9 and TDV 100 mL during the spring to summer cultivation, and the CT was set to 0.65, 0.75, 0.80, or 0.90 in the winter cultivation. When the irrigation volume per event was set to 50, 75, or 100 mL, the irrigation frequency in a day was 39, 29, and 19, respectively, and the drain rate was 3.04, 9.25, and 20.18%, respectively. When the CT was set to 0.65, 0.75, or 0.90 in winter, the irrigation frequency was about 6, 7, 15 times, respectively and the drain rate was 9.9, 10.8, 35.3% respectively. The signal of stem sap flow at the beginning of irrigation starting time did not correspond to that of solar irradiance when the irrigation volume per event was set to 50 or 75 mL, compared to that of 100 mL. In winter cultivation, the stem sap flow rate and substrate volumetric water content at the CT 0.65 treatment were very low, while they were very high at CT 0.90 was high. All the integrated data suggest that the proper range of irrigation volume per event is from 75 to 100 mL under at CT 0.9 and TDV 100 mL during the spring to summer cultivation, and the proper CT seems to be higher than 0.75 and lower than 0.90 under at 75 mL of the irrigation volume per event and TDV 70 mL during the winter cultivation. It is going to be necessary to investigate the relationship between capacitance value and substrate volumetric water content by determining the correction coefficient.

• Korean Journal of Applied Biomechanics
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• v.30 no.1
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• pp.103-109
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• 2020

Objective: The purpose of this study is to compare the muscle activity by electrode location in the biceps brachii during the arm curl isometric exercise and to provide the basic data needed to develop the proper electrode location of the biceps brachii based on the study results comparing the muscle activity by the angle of the elbow joint. Method: 17 adult males (Age: 21.50±4.63 yrs, height: 175.29±5.97 cm, weight: 63.79±15.31 kg, upper-arm length: 30.10±1.22 cm) participated in the study. In the arm curls isometric exercise, the experiment was divided into 1st and 2nd steps to compare muscle activity according to electrode location in the biceps brachii and muscle activity according to elbow angle change. In the first experiment, the surface electrode was attached at one-third point on the line from medial acromion to cubital fossa, according to the measurement method indicated by SENIAM. The elbow angle was set to 90°. In the second experiment, according to the proposed method of this study, the electrodes were separated at one finger's width in the left and right direction at one-third point on the line from medial acromion to cubital fossa, attached at the long head and short head. From the long head electrode, in about a width of two fingers in proximal direction, a total of three electrodes were attached at the myotendinal junction of the long head. The elbow angles were set as 70°, 90°, and 110°, and the isometric exercise (100% MVC) for 5 seconds was maintained with keeping the forearm and the rope to be 90° for the first and second experiments. Results: During the arm curl isometric exercise, there was no significant difference in SH and SENIAM proposition location proposed by this researcher. LH was shown to be lower than the muscle activity of the location proposed by SENIAM and there were significant (p<.01) differences. MJ appeared lower than the muscle activity of the location proposed by SENIAM and there were significant (p<.001) differences. The muscle activity by the elbow joint angle of SH in the biceps brachii was shown in large order of 70°<90°<110°, but there was no significant difference. The muscle activity by the elbow joint angle of LH was shown in large order of 90°<70°<110°, but there was no significant difference. The muscle activity by the elbow joint angle of MJ was shown in large order of 110°<90°<70°, but there was no significant difference. Conclusion: During the arm curl isometric exercise of the biceps brachii, it is judged appropriate to attach surface electrodes to the location proposed by SENIAM.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.3
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• pp.185-197
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• 2001

Recently, the design method by VHDL coding and synthesis has been used widely. As the integration ratio increases, the amount design by VHDL at a time also increases so many coding errors occur in a design. Thus, lots of time and effort is dissipated to detect those coding errors. This paper proposed a method to verify the coding errors in VHDL behavioral-level designs. As the methodology, we chose the method to detect the coding error by applying the generated set of verifying patterns and comparing the responses from the error-free case(gold unit) and the real design. Thus, we proposed an algorithm to generate the verifying pattern set for the coding errors. Verifying pattern generation is peformed for each code and the coding errors are classified as two kind: condition errors and assignment errors. To generate the patterns, VHDL design is first converted into the corresponding CDFG(Control & Data Flow Graph) and the necessary information is extracted by searching the paths in CDFG. Path searching method consists of forward searching and backward searching from the site where it is assumed that coding error occurred. The proposed algorithm was implemented with C-language. We have applied the proposed algorithm to several example VHDL behavioral-level designs. From the results, all the patterns for all the considered coding errors in each design could be generated and all the coding errors were detectable. For the time to generate the verifying patterns, all the considered designed took less than 1 ［sec］ of CPU time in Pentium-II 400MHz environments. Consequently, the verification method proposed in this paper is expected to reduce the time and effort to verify the VHDL behavioral-level designs very much.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2059-2065
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• 2013

This goal of this research was to evaluate the cost-effectiveness of the National Cancer Screening Program (NCSP) for breast cancer in the Republic of Korea from a government expenditure perspective. In 2002-2003 (baseline), a total of 8,724,860 women aged 40 years or over were invited to attend breast cancer screening by the NCSP. Those who attended were identified using the NCSP database, and women were divided into two groups, women who attended screening at baseline (screened group) and those who did not (non-screened group). Breast cancer diagnosis in both groups at baseline, and during 5-year follow-up was identified using the Korean Central Cancer Registry. The effectiveness of the NCSP for breast cancer was estimated by comparing 5-year survival and life years saved (LYS) between the screened and the unscreened groups, measured using mortality data from the Korean National Health Insurance Corporation and the National Health Statistical Office. Direct screening costs, indirect screening costs, and productivity costs were considered in different combinations in the model. When all three of these costs were considered together, the incremental cost to save one life year of a breast cancer patient was 42,305,000 Korean Won (KW) (1 USD=1,088 KW) for the screened group compared to the non-screened group. In sensitivity analyses, reducing the false-positive rate of the screening program by half was the most cost-effective (incremental cost-effectiveness ratio, ICER=30,110,852 KW/LYS) strategy. When the upper age limit for screening was set at 70 years, it became more cost-effective (ICER=39,641,823 KW/LYS) than when no upper age limit was set. The NCSP for breast cancer in Korea seems to be accepted as cost-effective as ICER estimates were around the Gross Domestic Product. However, cost-effectiveness could be further improved by increasing the sensitivity of breast cancer screening and by setting appropriate age limits.

• The Journal of Engineering Geology
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• v.16 no.4 s.50
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• pp.337-349
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• 2006

Seven hundred and fifty one fractures of the rhyolitic tuffaceous rock masses were mapped using 6 scanlines placed on rock slope exposures that were within 8.02 km of Busan-Ulsan highway. These data were analyzed to find the number of fracture sets that exist in the rock slopes and the probability distributions of orientation, spacing, trace length and fracture size in 3-D for each of the fracture sets. All the fracture set orientation distributions exhibit high variability. The Fisher distributions were found to be unsuitable to represent the statistical distribution of orientation for most of the fracture sets. The probability distributions, gamma, exponential and lognormal were found to be highly suitable to represent the distribution of spacing and semi-trace length of fracture sets. In obtain-ing these distributions, corrections were applied for sampling biases associated with spacing and trace length. The generated fracture system in 3-D was used to make predictions of fracture traces for each fracture set on 2-D win-dows. Developed stochastic 3-D fracture network for the rock mass was validated by comparing statistical proper-ties of the observed fracture traces on scanlines with the predicted fracture traces on the scanlines. This exercise fumed out to be successful.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.3
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• pp.8-14
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• 2012

Improving the speed of image processing is in great demand according to spread of high quality visual media or massive image applications such as 3D TV or movies, AR(Augmented reality). SIMD computer attached to a host computer can accelerate various image processing and massive data operations. MAMS is a multi-access memory system which is, along with multiple processing elements(PEs), adequate for establishing a high performance pipelined SIMD machine. MAMS supports simultaneous access to pq data elements within a horizontal, a vertical, or a block subarray with a constant interval in an arbitrary position in an $M{\times}N$ array of data elements, where the number of memory modules(MMs), m, is a prime number greater than pq. MAMS-PP4 is the first realization of the MAMS architecture, which consists of four PEs in a single chip and five MMs. This paper presents implementation of image processing algorithms and performance analysis for MAMS-PP16 which consists of 16 PEs with 17 MMs in an extension or the prior work, MAMS-PP4. The newly designed MAMS-PP16 has a 64 bit instruction format and application specific instruction set. The author develops a simulator of the MAMS-PP16 system, which implemented algorithms can be executed on. Performance analysis has done with this simulator executing implemented algorithms of processing images. The result of performance analysis verifies consistent response of MAMS-PP16 through the pyramid operation in image processing algorithms comparing with a Pentium-based serial processor. Executing the pyramid operation in MAMS-PP16 results in consistent response of processing time while randomly response time in a serial processor.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1131-1131
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• 2001

To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.4
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• pp.398-422
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• 2017

Objectives: The major aim of this study is to construct the database of retrospective exposure assessment for crystalline silica through reviews of literatures in South Korea. Methods: Airborne concentrations of crystalline silica were collected using an academic information search engine, Research Information Service System(RISS), operated by the Korea Education & Research Information Service(KERIS). The key words used for the literature search were 'silica', 'crystalline silica', 'cristobalite', 'quartz' and 'tridymite'. A total number of 18 published documents with the information of crystalline silica level in air or bulk samples were selected and used to estimate retrospective exposures to crystalline silica. Weighted arithmetic mean(WAM) calculated across studies was summarized by industry type. Industries were classified according to Korea Standard Industrial Classification(KSIC) using information provided in the literature. Results: A total of 2,131 individual air sampling data measured from 1987 to 2012 were compiled. Compiled individual measurement data consisted of 827 respirable crystalline silica (RCS), 31 total crystalline silica(TCS), 24 crystalline silica(CS), 778 respirable dust(RD) and 471 total dust(TD). Most of RCS measurements(68.9%) were collected from 'cast of metals(KSIC 243)'. Comparing industry types, 'mining coal and lignite(KISC 051)' showed the highest WAM concentration of RCS, $0.14mg/m^3$, followed by $0.11mg/m^3$ of 'manufacture of other non-metallic mineral products(KSIC 239)', $0.108mg/m^3$ of 'manufacture of ceramic ware(KSIC 232)', $0.098mg/m^3$ of 'heavy construction(KSIC 412)' and $0.062mg/m^3$ of 'cast of metals(KSIC 243)'. In terms of crystalline silica contents in airborne dust, 'manufacture of other non-metallic mineral products(KSIC 239)' showed the highest value of 7.3%(wt/wt), followed by 6.8% of 'manufacture of ceramic ware(KSIC 232)', 5.8% of 'mining of iron ores(KSIC 061)', 4.9% of 'cast of metals(KSIC 243)' and 4.5% of 'heavy construction(KSIC 412)'. WAM concentrations of RCS had no consistent trends over time from 1994 ($0.26mg/m^3$) to 2012 ($0.12mg/m^3$). Conclusion: The data set related RCS exposure level by industries can be used to determine not only the possibility of retrospective exposure to RCS, but also to evaluate the level of quantitative retrospective exposure to RCS.