• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.27-47
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• 1992

Engineers have developed new instruments that aid in diagnosis and therapy Ultrasonic imaging has provided a nondamaging method of imaging internal organs. A complex transducer emits ultrasonic waves at many angles and reconstructs a map of internal anatomy and also velocities of blood in vessels. Fast computed tomography permits reconstruction of the 3-dimensional anatomy and perfusion of the heart at 20-Hz rates. Positron emission tomography uses certain isotopes that produce positrons that react with electrons to simultaneously emit two gamma rays in opposite directions. It locates the region of origin by using a ring of discrete scintillation detectors, each in electronic coincidence with an opposing detector. In magnetic resonance imaging, the patient is placed in a very strong magnetic field. The precessing of the hydrogen atoms is perturbed by an interrogating field to yield two-dimensional images of soft tissue having exceptional clarity. As an alternative to radiology image processing, film archiving, and retrieval, picture archiving and communication systems (PACS) are being implemented. Images from computed radiography, magnetic resonance imaging (MRI), nuclear medicine, and ultrasound are digitized, transmitted, and stored in computers for retrieval at distributed work stations. In electrical impedance tomography, electrodes are placed around the thorax. 50-kHz current is injected between two electrodes and voltages are measured on all other electrodes. A computer processes the data to yield an image of the resistivity of a 2-dimensional slice of the thorax. During fetal monitoring, a corkscrew electrode is screwed into the fetal scalp to measure the fetal electrocardiogram. Correlations with uterine contractions yield information on the status of the fetus during delivery To measure cardiac output by thermodilution, cold saline is injected into the right atrium. A thermistor in the right pulmonary artery yields temperature measurements, from which we can calculate cardiac output. In impedance cardiography, we measure the changes in electrical impedance as the heart ejects blood into the arteries. Motion artifacts are large, so signal averaging is useful during monitoring. An intraarterial blood gas monitoring system permits monitoring in real time. Light is sent down optical fibers inserted into the radial artery, where it is absorbed by dyes, which reemit the light at a different wavelength. The emitted light travels up optical fibers where an external instrument determines O2, CO2, and pH. Therapeutic devices include the electrosurgical unit. A high-frequency electric arc is drawn between the knife and the tissue. The arc cuts and the heat coagulates, thus preventing blood loss. Hyperthermia has demonstrated antitumor effects in patients in whom all conventional modes of therapy have failed. Methods of raising tumor temperature include focused ultrasound, radio-frequency power through needles, or microwaves. When the heart stops pumping, we use the defibrillator to restore normal pumping. A brief, high-current pulse through the heart synchronizes all cardiac fibers to restore normal rhythm. When the cardiac rhythm is too slow, we implant the cardiac pacemaker. An electrode within the heart stimulates the cardiac muscle to contract at the normal rate. When the cardiac valves are narrowed or leak, we implant an artificial valve. Silicone rubber and Teflon are used for biocompatibility. Artificial hearts powered by pneumatic hoses have been implanted in humans. However, the quality of life gradually degrades, and death ensues. When kidney stones develop, lithotripsy is used. A spark creates a pressure wave, which is focused on the stone and fragments it. The pieces pass out normally. When kidneys fail, the blood is cleansed during hemodialysis. Urea passes through a porous membrane to a dialysate bath to lower its concentration in the blood. The blind are able to read by scanning the Optacon with their fingertips. A camera scans letters and converts them to an array of vibrating pins. The deaf are able to hear using a cochlear implant. A microphone detects sound and divides it into frequency bands. 22 electrodes within the cochlea stimulate the acoustic the acoustic nerve to provide sound patterns. For those who have lost muscle function in the limbs, researchers are implanting electrodes to stimulate the muscle. Sensors in the legs and arms feed back signals to a computer that coordinates the stimulators to provide limb motion. For those with high spinal cord injury, a puff and sip switch can control a computer and permit the disabled person operate the computer and communicate with the outside world.

• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1479-1488
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• 2018

On September 3rd 2017, strong artificial seismic signals from North Korea were detected in KMA (Korea Meteorological Administration) seismic network. The location of the epicenter was estimated to be Punggye-ri nuclear test site and it was the most powerful to date. The event was not studied well due to accessibility and geodetic measurements. Therefore, we used remote sensing data to analyze surface changes around Mt. Mantap area. First of all, we tried to detect surface deformation using InSAR method with Advanced Land Observation Satellite-2 (ALOS-2). Even though ALOS-2 data used L-band long wavelength, it was not working well for this particular case because of decorrelation on interferogram. The main reason would be large deformation near the Mt. Mantap area. To overcome this limitation of decorrelation, we applied offset tracking method to measure deformation. However, this method is affected by window kernel size. So we applied various window sizes from 32 to 224 in 16 steps. We could retrieve 2D surface deformation of about 3 m in maximum in the west side of Mt. Mantap. Second, we used Pleiadas-A/B high resolution satellite optical images which were acquired before and after the 6th nuclear test. We detected widespread surface damage around the top of Mt. Mantap such as landslide and suspected collapse area. This phenomenon may be caused by a very strong underground nuclear explosion test. High-resolution satellite images could be used to analyze non-accessible area.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.363-375
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• 2024

Waterbody change detection using satellite images has recently been carried out in various regions in South Korea, utilizing multiple types of sensors. This study utilizes optical satellite images from Landsat and Sentinel-2 based on Google Earth Engine (GEE) to analyze long-term surface water area changes in four monitored small and medium-sized water supply dams and agricultural reservoirs in South Korea. The analysis covers 19 years for the water supply dams and 27 years for the agricultural reservoirs. By employing image analysis methods such as normalized difference water index, Canny Edge Detection, and Otsu'sthresholding for waterbody detection, the study reliably extracted water surface areas, allowing for clear annual changes in waterbodies to be observed. When comparing the time series data of surface water areas derived from satellite images to actual measured water levels, a high correlation coefficient above 0.8 was found for the water supply dams. However, the agricultural reservoirs showed a lower correlation, between 0.5 and 0.7, attributed to the characteristics of agricultural reservoir management and the inadequacy of comparative data rather than the satellite image analysis itself. The analysis also revealed several inconsistencies in the results for smaller reservoirs, indicating the need for further studies on these reservoirs. The changes in surface water area, calculated using GEE, provide valuable spatial information on waterbody changes across the entire watershed, which cannot be identified solely by measuring water levels. This highlights the usefulness of efficiently processing extensive long-term satellite imagery data. Based on these findings, it is expected that future research could apply this method to a larger number of dam reservoirs with varying sizes,shapes, and monitoring statuses, potentially yielding additional insights into different reservoir groups.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Journal of the Korean earth science society
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• v.31 no.6
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• pp.600-607
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• 2010

In 2008, multiple episodes of large-scale transport of natural airborne particles and anthropogenically affected particles from different sources in the East Asian continent were identified in the National Oceanic and Atmospheric Administration (NOAA) satellite RGB-composite images and the mass concentrations of ground level particulate matters. To analyze the aerosol size distribution during the large-scale transport of atmospheric aerosols, both aerosol optical depth (AOD; proportional to the aerosol total loading in the vertical column) and fine aerosol weighting (FW; fractional contribution of fine aerosol to the total AOD) of Moderate resolution Imaging Spectroradiometer (MODIS) aerosol products were used over the East Asian region. The six episodes of massive natural airborne particles were observed at Cheongwon, originating from sandstorms in northern China, Mongolia and the loess plateau of China. The $PM_{10}$ and $PM_{2.5}$ stood at 70% and 16% of the total mass concentration of TSP, respectively. However, the mass concentration of $PM_{2.5}$ among TSP increased as high as 23% in the episode in which they were flowing in by way f the industrial area in east China. In the other five episodes of anthropogenically affected particles that flowed into the Korean Peninsula from east China, the mass concentrations of $PM_{10}$ and $PM_{2.5}$ among TSP reached 82% and 65%, respectively. The average AOD for the large-scale transport of anthropogenically affected particle episodes in the East Asian region was measured at $0.42{\pm}0.17$ compared with AOD ($0.36{\pm}0.13$) for the natural airborne particle episodes. Particularly, the regions covering east China, the Yellow Sea, the Korean Peninsula, and the east Korean sea were characterized by high levels of AOD. The average FW values observed during the event of anthropogenically affected aerosols ($0.63{\pm}0.16$) were moderately higher than those of natural airborne particles ($0.52{\pm}0.13$). This observation suggests that anthropogenically affected particles contribute greatly to the atmospheric aerosols in East Asia.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.3
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• pp.226-233
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• 2007

Purpose: Dual reporter gene imaging has several advantages for more sophisticated molecular imaging studies such as gene therapy monitoring. Herein, we have constructed hepatoma cell line expressing dual reporter genes of sodium iodide symporter (NIS) and enhanced green fluorescence protein (EGFP), and the functionalities of the genes were evaluated in vivo by nuclear and optical imaging. Materials and Methods: A pRetro-PN vector was constructed after separating NIS gene from pcDNA-NIS. RSV-EGFP-WPRE fragment separated from pLNRGW was cloned into pRetro-PN vector. The final vector expressing dual reporter genes was named pRetro-PNRGW. A human hepatoma (HepG2) cells were transfected by the retrovirus containing NIS and EGFP gene (HepG2-NE). Expression of NIS gene was confirmed by RT-PCR, radioiodine uptake and efflux studies. Expression of EGFP was confirmed by RT-PCR and fluorescence microscope. The HepG2 and HepG2-NE cells were implanted in shoulder and hindlimb of nude mice, then fluorescence image, gamma camera image and I-124 microPET image were undertaken. Results: The HepG2-NE cell was successfully constructed. RT-PCR showed NIS and EGFP mRNA expression. About 50% of cells showed fluorescence. The iodine uptake of NIS-expressed cells was about 9 times higher than control. In efflux study, $T_{1/2}$ of HepG2-NE cells was 9 min. HepG2-NE xenograft showed high signal-to-background fluorescent spots and higher iodine-uptake compared to those of HepG2 xenograft. Conclusion: A hepatoma cell line expressing NIS and EGFP dual reporter genes was successfully constructed and could be used as a potential either by therapeutic gene or imaging reporter gene.

• Korean Journal of Optics and Photonics
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• v.28 no.5
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• pp.203-212
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• 2017

A scientific model refers to a conceptual system that can describe, explain, and predict a particular physical phenomenon. The co-construction of the scientific model is attracting attention as a new teaching and learning strategy in the field of science education and various studies. The evaluation and modification of models compared with the predicted models of data from the real world is the core of modeling strategy. However, there were only a limited data provided by the teacher in many studies of modeling comparing the students' predictions of their own models. Most of the students were not given the opportunity to evaluate the suitability of the model with the data in the real world. The purpose of this study was to develop a scientific model co-construction program that can evaluate the model by directly comparing the predicted models with the observed data from the real world. Through a collaborative discussion between teachers and researchers for 6 months, a 5-session scientific model co-construction program on the subject 'image formation by convex lenses' for second grade middle school students was developed. Eighty (80) students in 3 classes and a science teacher with 20 years of service from general public co-educational middle school in Gyeonggi-do participated in this 2-week program. After the class, students were asked about the helpfulness and difficulty of the class, and whether they would like to recommend this class to a friend. After the class, 95.8% of the students constructed the scientific model more than the model using the construction rule. Students had difficulties to identify principles or understand their friends, but the result showed that they could understand through model evaluation experiment. 92.5% of the students said that they would be more than willing to recommend this program to their friends. It is expected that the developed program will be applied to the school and contribute to the improvement of students' modeling ability and co-construction ability.

• Journal of Korean Ophthalmic Optics Society
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• v.16 no.4
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• pp.357-362
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• 2011

Purpose: The narrow-band pass color-filters with a 500 nm central wavelength and 12 nm FWHM using $Ti_3O_5/SiO_2$ mutilayer were fabricated, and their characteristics and structures were studied. Methods: the optical constants, n and k, of the $Ti_3O_5$ and $SiO_2$ thin films were obtained from the transmittances of their thin film. The narrow-band pass color-filters were designed with these optical constants and the AR coating of the filter was also designed. $Ti_3O_5/SiO_2$ multilayer filters were made by electron beam evaporation apparatus and the transmittaces of the filters were measured by spectrophotometer. the number of layers and the thicknesses of filters were calculated from the cross section of filters by SEM image and the composition of filters was analysed by XPS analysis. Results: The optimization of AR coating for the narrow-band pass color-filter was [air$|SiO_2(90)|Ti_3O_5(36)|SiO_2(5)|Ti_3O_5(73)|SiO_2(30)|Ti_3O_5(15)|$ glass], and the optimization of filter layer for the color filter was [air$|SiO_2(192)|Ti_3O_5(64)|SiO_2(102)|Ti_3O_5(66)|SiO_2(112)|Ti_3O_5(74)|SiO_2(120)|Ti_3O_5(68)|SiO_2(123)|Ti_3O_5(80)|SiO_2(109)|Ti_3O_5(70)|SiO_2(105)|Ti_3O_5(62)|SiO_2(99)|Ti_3O_5(63)|SiO_2(98)|Ti_3O_5(51)|SiO_2(60)|Ti_3O_5(42)|SiO_2(113)|Ti_3O_5(88)|SiO_2(116)|Ti_3O_5(68)|SiO_2(89)|Ti_3O_5(49)|SiO_2(77)|Ti_3O_5(48)|SiO_2(84)|Ti_3O_5(51)|SiO_2(85)|Ti_3O_5(48)|SiO_2(59)|Ti_3O_5(34)|SiO_2(71)|Ti_3O_5(44)|SiO_2(65)|Ti_3O_5(45)|SiO_2(81)|Ti_3O_5(52)|SiO_2(88)|$ glass]. It was known that the color-filters fabricated by the simulation data were composed of 41 layers by SEM image and the top layer of filters was $SiO_2$ layer and the filters were composed of $SiO_2$/$Ti_3O_5$ multilayer by XPS analysis. It was also known that the mixed thin film of TiO2 and $Ti_3O_5$ was made during the deposition of the $Ti_3O_5$ material. Conclusions: The narrow-band pass color-filters with a 500 nm central wavelength and 12 nm FWHM using $Ti_3O_5/SiO_2$ mutilayer of 41 layer were fabricated, and it was known that the mixed form of TiO2 and $Ti_3O_5$ thin film was made during the deposition of the $Ti_3O_5$ material.