• The Journal of Bigdata
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• v.5 no.1
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• pp.29-39
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• 2020

Purpose The atmosphere of respect for individual tastes that have spread throughout society has changed the consumption trend. As a result, the travel industry is also seeing customized travel as a new trend that reflects consumers' personal tastes. In particular, there is a growing interest in 'film-induced tourism', one of the areas of travel industry. We hope to satisfy the individual's motivation for traveling while watching movies with customized travel proposals, which we expect to be a catalyst for the continued development of the 'film-induced tourism industry'. Design/methodology/approach In this study, we implemented a methodology through 'OCR' of extracting and suggesting film location information that viewers want to visit. First, we extract a scene from a movie selected by a user by using 'OpenCV', a real-time image processing library. In addition, we detected the location of characters in the scene image by using 'EAST model', a deep learning-based text area detection model. The detected images are preprocessed by using 'OpenCV built-in function' to increase recognition accuracy. Finally, after converting characters in images into recognizable text using 'Tesseract', an optical character recognition engine, the 'Google Map API' returns actual location information. Significance This research is significant in that it provides personalized tourism content using fourth industrial technology, in addition to existing film tourism. This could be used in the development of film-induced tourism packages with travel agencies in the future. It also implies the possibility of being used for inflow from abroad as well as to abroad.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.79-86
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• 2005

In this paper, we propose a new LINF(Linear Independent Non-negative Factorization) algorithm for real-time face recognition systea This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction Part we applied subtraction image, the detection of eye and mouth region , and normalization method, and then in the face recognition Part we used LINF in extracted face candidate region images. The existing recognition system using only PCA(Principal Component Analysis) showed low recognition rates, and it was hard in the recognition system using only LDA(Linear Discriminants Analysis) to apply LDA directly when the training set is small. To overcome these shortcomings, we reduced dimension as the matrix that had non-negative value to be different from former eigenfaces and then applied LDA to the matrix in the proposed system We have experimented using self-organized DAIJFace database and ORL database offered by AT(')T laboratory in Cambridge, U.K. to evaluate the performance of the proposed system. The experimental results showed that the proposed method outperformed PCA, LDA, ICA(Independent Component Analysis) and PLMA(PCA-based LDA mixture algorithm) method within the framework of recognition accuracy.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.2
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• pp.94-99
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• 2010

This paper presents a charge pump architecture for correcting the current mismatch due to the PVT variation. In general, the current mismatch of the charge pump should be minimized to improve the phase noise and spur performance of the PLL. In order to correct the current mismatch of the charge pump, the current difference is detected by the replica charge pump and fed back into the main charge pump. This scheme is very simple and guarantees the high accuracy compared with the prior works. Also, it shows a good dynamic performance because the mismatch is corrected continuously. It is implemented in 0.13um CMOS process and the die area is $100{\mu}m\;{\times}\;160{\mu}m$. The voltage swing is from 0.2V to 1V at supply voltage of 1.2V. The charging and discharging currents are $100{\mu}A$, respectively and the current mismatch due to the PVT variation is less than 1%.

• Journal of agricultural medicine and community health
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• v.36 no.4
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• pp.218-226
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• 2011

Objectives: Paraquat (PQ) is a widely used ionic pesticide that is fatal when ingested accidentally or for suicidal purposes. It is thought that chronic exposure of PQ is related with the development of Parkinson's disease, but epidemiological studies have not yet confirmed that theory. This study attempted to estimate the possibility of environmental PQ exposure through soil and water. Materials and Methods: We analyzed the amount of decomposed PQ solution in wet soil after exposure to ultraviolet light. An artificial rainfall condition was simulated over soil sprayed with PQ to measure the amount of eluted PQ. In addition, PQ was diluted in water from three differently rated rivers and the changes in PQ concentration were measured after ultraviolet exposure over one month. High performance liquid chromatography/ultra violet detection was used to analyze the concentrations of PQ. Results: In the method we used, the recovery rate of PQ showed a precision rate less than 5%, an accuracy greater than 88%, and the calibration equation was y=5538.8x-440.01($R^2$=0.9985). There were no significant differences in the concentrations of PQ obtained from the three specimens over a 1-week period. From the PQ-sprayed soil, the artificial rainfall conditions showed no PQ elution over a 1-month period, and there was no significant differences in PQ concentrations according to ultraviolet exposure among the three samples. Conclusions: PQ remains well adsorbed naturally in soil. However, it may still exist in an integrated state for a long time in the hydrosphere, so the possibility of PQ exposure through drinking water cannot be disqualified.

• Korean Journal of Optics and Photonics
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• v.4 no.1
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• pp.15-21
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• 1993

This paper describes the design and development of a KrF excimer laser stepper and discusses the detailed system parameters and characterization data obtained from the performance test. We have developed a deep UV step-and-repeat system, operating at 248 nm, by retrofitting a commercial modules such as KrF excimer laser, precision wafer stage and fused silica illumination and 5X projection optics of numerical aperture 0.42. What we have developed, to the basic structure, are wafer alignment optics, reticle alignment system, autofocusing/leveling mechanisms and environment chamber. Finally, all these subsystem were integrated under the control of microprocessor-based controllers and computer. The wafer alignment system comprises the OFF-AXIS and the TTL alignment. The OFF-AXIS alignment system was realized with two kinds of optics. One is the magnification system with the image processing technique and the other is He-Ne laser diffraction type system using the alignment grating on the wafer. 'The TTL alignment system employs a dual beam inteferometric method, which takes advantages of higher diffraction efficiency compared with other TTL type alignment systems. As the results, alignment accuracy for OFF-AXIS and TTL alignment system were obtained within 0.1 $\mu\textrm{m}$/ 3 $\sigma$ for the various substrate on the wafers. The wafer focusing and leveling system is modified version of the conventional systems using position sensitive detectors (PSD). This type of detection method showed focusing and leveling accuracies of about $\pm$ 0.1 $\mu\textrm{m}$ and $\pm$ 0.5 arcsec, respectively. From the CD measurement, we obtained 0.4 $\mu\textrm{m}$ resolution features over the full field with routine use, and 0.3 $\mu\textrm{m}$ resolution was attainable under more strict conditions.

• YAKHAK HOEJI
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• v.51 no.2
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• pp.96-102
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• 2007

Measurement of globotriaosylceramide (Gb3, ceramide trihexoside) in urine has clinical importance for monitoring after enzyme replacement therapy in Fabry disease patients. The disease is an X-linked lipid storage disorder that results from a deficiency of the enzyme ${\alpha}$-galactosidase A (${\alpha}$-Gal A). The lack of ${\alpha}$-Gal A causes an intracellular accumulation of glycosphingolipids, mainly Gb3. A simple, rapid, and highly sensitive analytical method for Gb3 in urine was developed without labor-extensive pre-treatment by electrospray ionization MS/MS (ESI-MS/MS). Only simple 5-fold dilution of urine is necessary for the extraction and isolation of Gb3 in urine. Gb3 in diluted urine was dissolved in dioxane containing C17:0 Gb3 as an internal standard. After centrifugation it was directly injected and analyzed through guard column by in combination with multiple reaction monitoring mode of ESI-MS/MS. Eight isoforms of Gb3 were completely resolved from urine matrix. C24:0 Gb3 occupied 50% of total Gb3 as a major component in urine. Linear relationship for Gb3 isoforms was found in the range of 0.005${\sim}$5.0 ${\mu}$g/ml. The limit of detection (S/N=5) was 0.005 ${\mu}$g/ml and limit of quantification was 0.05 ${\mu}$g/ml for C24:0 Gb3 with acceptable precision and accuracy. Correlation coefficient of calibration curves for 8 Gb3 isoforms ranged from 0.9598 to 0.9975. This method could be useful for rapid and sensitive 1st line Fabry disease screening, monitoring and/or diagnostic tool for Fabry disease.

• Journal of Life Science
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• v.21 no.1
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• pp.9-14
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• 2011

Perceived exertion involves detection and interpretation of sensations arising from the body during physical exercise. Physiological variables such as heart rate and oxygen consumption positively correlate with ratings of perceived exertion (RPE). It is unknown whether the accuracy of predicting exercise intensity from RPE differs between men and women. Therefore, it was examined whether men or women could predict relative exercise intensity, determined by oxygen consumption, more accurately from RPE. Ten male and ten female young adult subjects aged 25.1${\pm}$3.52 yr volunteered to participate. RPE were determined by the Borg 15-category scale, and a standard Bruce treadmill protocol was used to perform graded exercise testing. There was no significant difference in slope means between males and females (p=0.501). No significant difference was observed when plotting rates of perceived exertion (RPE) vs. percentage of $VO_2$ max. The relative maximal oxygen consumptions ($VO_{2max,\;}_{rel}$) were 52.36${\pm}$7.35 ml/kg/min for males and 41.44${\pm}$6.71 ml/kg/min for females, respectively and there was a significantly high difference between the two groups in the relative $VO_{2max}$, as well as figures of 4.05${\pm}$0.36 l/min for males and 2.53${\pm}$0.39 l/min for females in the absolute $VO_{2max}$ in this study. There were no significant differences in slope, y-intercept, and standard error of estimate (SEE) between males and females. No significant difference with RPE according to exercise intensity was found between males and females. However, RPE was a useful predictor of exercise intensity in independent genders.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.11
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• pp.1604-1609
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• 2016

An HPLC analysis method was developed for standard determination of marmesin as a functional health material in Broussonetia kazinoki extract. HPLC was performed on a $C_{18}$ Kromasil column ($4.6{\times}250mm$, $5{\mu}m$) with a gradient elution of 0.1% (v/v) trifluoroacetic acid and acetonitrile at a flow rate of 1.0 mL/min at $30^{\circ}C$. The analyte was detected at 330 nm. The HPLC method was validated in accordance with International Conference on Harmonization guidelines for analytical procedures with respect to specificity, precision, accuracy, and linearity. The limit of detection and quantitation were 6.2 and $18.6{\mu}g/mL$, respectively. Calibration curves showed good linearity ($r^2$>0.9999), and the precision of analysis was satisfactory (less than 0.3%). Recoveries of quantified compound ranged from 100.35 to 101.18%. This result indicates that the established HPLC method is very useful for the determination of marker compounds in B. kazinoki extracts.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.847-857
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• 2018

As the number of malicious code increases steeply, cyber attack victims targeting corporations, public institutions, financial institutions, hospitals are also increasing. Accordingly, academia and security industry are conducting various researches on malicious code detection. In recent years, there have been a lot of researches using machine learning techniques including deep learning. In the case of research using Convolutional Neural Network, ResNet, etc. for classification of malicious code, it can be confirmed that the performance improvement is higher than the existing classification method. However, one of the characteristics of the target attack is that it is custom malicious code that makes it operate only for a specific company, so it is not a form spreading widely to a large number of users. Since there are not many malicious codes of this kind, it is difficult to apply the previously studied machine learning or deep learning techniques. In this paper, we propose a method to classify malicious codes when the amount of samples is insufficient such as targeting type malicious code. As a result of the study, we confirmed that the accuracy of 97% can be achieved even with a small amount of data by applying the Memory Augmented Neural Networks model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.609-616
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• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.