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Classification of Fall in Sick Times of Liver Cirrhosis using Magnetic Resonance Image (자기공명영상을 이용한 간경변 단계별 분류에 관한 연구)

  • Park, Byung-Rae;Jeon, Gye-Rok
    • Journal of radiological science and technology
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    • v.26 no.1
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    • pp.71-82
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    • 2003
  • In this paper, I proposed a classifier of liver cirrhotic step using T1-weighted MRI(magnetic resonance imaging) and hierarchical neural network. The data sets for classification of each stage, which were normal, 1type, 2type and 3type, were obtained in Pusan National University Hospital from June 2001 to december 2001. And the number of data was 46. We extracted liver region and nodule region from T1-weighted MR liver image. Then objective interpretation classifier of liver cirrhotic steps in T1-weighted MR liver images. Liver cirrhosis classifier implemented using hierarchical neural network which gray-level analysis and texture feature descriptors to distinguish normal liver and 3 types of liver cirrhosis. Then proposed Neural network classifier teamed through error back-propagation algorithm. A classifying result shows that recognition rate of normal is 100%, 1type is 82.3%, 2type is 86.7%, 3type is 83.7%. The recognition ratio very high, when compared between the result of obtained quantified data to that of doctors decision data and neural network classifier value. If enough data is offered and other parameter is considered, this paper according to we expected that neural network as well as human experts and could be useful as clinical decision support tool for liver cirrhosis patients.

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A Study on DGPS Framework and Performance Evaluation for High-Accurate Localization based on GPS/AGPS (GPS/AGPS 기반의 고정밀 측위가 가능한 DGPS 프레임워크 및 성능평가에 관한 연구)

  • Seo, Ho-Seok;Jung, Se-Hoon;Oh, Min-Joo;Park, Dong-Gook;Sim, Chun-Bo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.9 no.8
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    • pp.927-938
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    • 2014
  • A number of crime and disease relief situation show a clear increasing trend in domestic and overseas country. In particular, we desperately need a fast location information sharing with high accuracy for dealing with this situation efficiently. In this paper, we propose a DGPS framework and performance evaluation based on Web service enable increase location accuracy using low-cost GPS or AGPS. The framework consists of mobile station to realize the final service by receiving the correction values that are created in the base station closest to the current position from DGPS server, base station system to transmit the correct values to DPGS server by installing at base point and DGPS framework working at DGPS server. Our framework is fundamentally designed to respond based on XML to service request. In addition, for performance evaluation, we make use of 3 sites of Level 2 city base-station among the base stations being operated in Suncheon-si. Through performance evaluation, we show that our framework outperforms about 10%~15% in terms of error improvement rate, compared with the existing schemes. And we have the advantage that various services can be expanded owing to receiving the correction values through mobile device such as, smart phone, smart pad, net-book by using XML based Web services.

Comparison of Performance of Measuring Method of VIS/NIR Spectroscopic Spectrum to Predict Soluble Solids Content of 'Shingo' Pear (VIS/NIR 스펙트럼 측정모드에 따른 신고 배의 당도 예측성능 비교)

  • Suh, Sang-Ryong;Lee, Kyeong-Hwan;Yu, Seung-Hwa;Yoo, Soo-Nam;Choi, Yeong-Soo
    • Journal of Biosystems Engineering
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    • v.36 no.2
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    • pp.130-139
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    • 2011
  • Three modes of VIS/NIR spectroscopic measurement (interactance and two modes of transmission) were compared for their ability to estimate soluble solids content (SSC) of 'Shingo' pear non-destructively. The two transmission modes are named as full- and semi-transmission, where full-transmission stands for passing of light through abdomen of pear and semi-transmission is for transit of light mainly through flesh of pear. For comparison of the modes, prediction models developed from the collected spectroscopic data by the three modes were developed and tested for comparison of their performance. Partial least square regression (PSLR) was used to develop the models and various pre-processing methods were applied to develop models of high accuracy. The experiment was repeated three times with pears produced in different regions. The experiments resulted that selection of pre-processing is very important to attain accurate models, and multiplicative scatter correction (MSC) was selected as a pre-processor of high accuracy for the three modes of spectroscopic measurement in every experiment. Except for MSC, different group of pre-processing methods were selected for the three modes of measurement in every experiment without any tendency to the tested modes of measurement and pears of different produced region. Root-mean-square error of prediction (RMSEP) of prediction models of the three modes of measurement using prepreocessor of MSC were compared for their ability to estimate SSC. The models resulted in ranges of $0.37{\sim}0.57^{\circ}Brix$, $0.65{\sim}0.72^{\circ}Brix$, $0.39{\sim}0.51^{\circ}Brix$ for interactance, full- and semi-transmission, respectively. As shown, modes of semi-transmission and interactance resulted about the same level of prediction accuracy and were noted as modes of high performance to predict SSC.

Target Identification for Metabolic Engineering: Incorporation of Metabolome and Transcriptome Strategies to Better Understand Metabolic Fluxes

  • Lindley, Nic
    • Proceedings of the Korean Society for Applied Microbiology Conference
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    • 2004.06a
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    • pp.60-61
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    • 2004
  • Metabolic engineering is now a well established discipline, used extensively to determine and execute rational strategies of strain development to improve the performance of micro-organisms employed in industrial fermentations. The basic principle of this approach is that performance of the microbial catalyst should be adequately characterised metabolically so as to clearlyidentify the metabolic network constraints, thereby identifying the most probable targets for genetic engineering and the extent to which improvements can be realistically achieved. In order to harness correctly this potential, it is clear that the physiological analysis of each strain studied needs to be undertaken under conditions as close as possible to the physico-chemical environment in which the strain evolves within the full-scale process. Furthermore, this analysis needs to be undertaken throughoutthe entire fermentation so as to take into account the changing environment in an essentially dynamic situation in which metabolic stress is accentuated by the microbial activity itself, leading to increasingly important stress response at a metabolic level. All too often these industrial fermentation constraints are overlooked, leading to identification of targets whose validity within the industrial context is at best limited. Thus the conceptual error is linked to experimental design rather than inadequate methodology. New tools are becoming available which open up new possibilities in metabolic engineering and the characterisation of complex metabolic networks. Traditionally metabolic analysis was targeted towards pre-identified genes and their corresponding enzymatic activities within pre-selected metabolic pathways. Those pathways not included at the onset were intrinsically removed from the network giving a fundamentally localised vision of pathway functionality. New tools from genome research extend this reductive approach so as to include the global characteristics of a given biological model which can now be seen as an integrated functional unit rather than a specific sub-group of biochemical reactions, thereby facilitating the resolution of complexnetworks whose exact composition cannot be estimated at the onset. This global overview of whole cell physiology enables new targets to be identified which would classically not have been suspected previously. Of course, as with all powerful analytical tools, post-genomic technology must be used carefully so as to avoid expensive errors. This is not always the case and the data obtained need to be examined carefully to avoid embarking on the study of artefacts due to poor understanding of cell biology. These basic developments and the underlying concepts will be illustrated with examples from the author's laboratory concerning the industrial production of commodity chemicals using a number of industrially important bacteria. The different levels of possibleinvestigation and the extent to which the data can be extrapolated will be highlighted together with the extent to which realistic yield targets can be attained. Genetic engineering strategies and the performance of the resulting strains will be examined within the context of the prevailing experimental conditions encountered in the industrial fermentor. Examples used will include the production of amino acids, vitamins and polysaccharides. In each case metabolic constraints can be identified and the extent to which performance can be enhanced predicted

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A Sensitivity Analysis of Design Parameters of an Underground Radioactive Waste Repository Using a Backpropagation Neural Network (Backpropagation 인공신경망을 이용한 지하 방사성폐기물 처분장 설계 인자의 민감도 분석)

  • Kwon, S.;Cho, W.J.
    • Tunnel and Underground Space
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    • v.19 no.3
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    • pp.203-212
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    • 2009
  • The prediction of near field behavior around an underground high-level radioactive waste repository is important for the repository design as well as the safety assessment. In this study, a sensitivity analysis for seven parameters consisted of design parameters and material properties was carried out using a three-dimensional finite difference code. From the sensitivity analysis, it was found that the effects of borehole spacing, tunnel spacing, cooling time and rock thermal conductivity were more significant than the other parameters. For getting a statistical distribution of buffer and rock temperatures around the repository, an artificial neural network, backpropagation, was applied. The reliability of the trained neural network was tested with the cases with randomly chosen input parameters. When the parameter variation is within ${\pm}10%$, the prediction from the network was found to be reliable with about a 1% error. It was possible to calculate the temperature distribution for many cases quickly with the trained neural network. The buffer and rock temperatures showed a normal distribution with means of $98^{\circ}C$ and $83.9^{\circ}C$ standard deviations of $3.82^{\circ}C$ and $3.67^{\circ}C$, respectively. Using the neural network, it was also possible to estimate the required change in design parameters for reducing the buffer and rock temperatures for $1^{\circ}C$.

Change detection algorithm based on amplitude statistical distribution for high resolution SAR image (통계분포에 기반한 고해상도 SAR 영상의 변화탐지 알고리즘 구현 및 적용)

  • Lee, Kiwoong;Kang, Seoli;Kim, Ahleum;Song, Kyungmin;Lee, Wookyung
    • Korean Journal of Remote Sensing
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    • v.31 no.3
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    • pp.227-244
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    • 2015
  • Synthetic Aperture Radar is able to provide images of wide coverage in day, night, and all-weather conditions. Recently, as the SAR image resolution improves up to the sub-meter level, their applications are rapidly expanding accordingly. Especially there is a growing interest in the use of geographic information of high resolution SAR images and the change detection will be one of the most important technique for their applications. In this paper, an automatic threshold tracking and change detection algorithm is proposed applicable to high-resolution SAR images. To detect changes within SAR image, a reference image is generated using log-ratio operator and its amplitude distribution is estimated through K-S test. Assuming SAR image has a non-gaussian amplitude distribution, a generalized thresholding technique is applied using Kittler and Illingworth minimum-error estimation. Also, MoLC parametric estimation method is adopted to improve the algorithm performance on rough ground target. The implemented algorithm is tested and verified on the simulated SAR raw data. Then, it is applied to the spaceborne high-resolution SAR images taken by Cosmo-Skymed and KOMPSAT-5 and the performances are analyzed and compared.

Prediction of the content of white clover and perennial ryegrass in fresh or dry mixtures made up from pure botanical samples, by near infrared spectroscopy

  • Blanco, Jose A.;Alomar, Daniel J.;Fuchslocher, Rita I.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1266-1266
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    • 2001
  • Pasture composition, an important attribute determining sward condition and value, is normally assessed by hand separation, drying and measuring weight contribution of each species in the mixture. This is a tedious, time and labour consuming procedure. NIRS has demonstrated the potential for predicting botanical composition of swards, but most of the work has been carried out on dry samples. The aim of this work was to evaluate the feasibility of developing NIR models for predicting the white clover and ryegrass content in fresh or dry mixtures artificially prepared from pure samples of both species. Mixtures from pure stands of white clover(Trifolium repens) and perennial ryegrass (Lolium perenne) were prepared with different proportions (0 to 100%) of each species (fresh weight). A total of 55 samples were made (11 mixtures,5 cuts). Spectra (400 to 2500 nm) were taken from fresh chopped (rectangular cuvettes, transport sample module) samples, in a NIR Systems 6500 scanning monochromator controlled by the software NIRS 3 (Infrasoft International), which was also utilized for calibration development. Different math treatments (derivative order, subtraction gap and smooth segment) and a scatter correction treatment of the spectra (SNV and Detrend) were tested. Equations were developed by modified partial least squares. Prediction accuracy evaluated by cross-validation, showed that percentage of clover or ryegrass, as contribution in dry weight, can be successfully percentage of clover or ryegrass, as contribution in dry weight, can be successfully predicted either on fresh or dried samples, with equations developed by different math treatments. Best equations for fresh samples were developed including a first, second, or third derivative, whereas for dry samples best equations included a second or third derivative. Standard errors of ross validation were about 6% for fresh and 3.6% for dry samples, Coefficient of determination of cross validation (1-VR) were over 0.95 times the value of SECV for fresh samples and over 8 times the value of SECV for dry samples. Scatter correction (SNV and Detrend) in general improved prediction accuracy. It is concluded more precise on dried and ground samples, it can be used with an acceptable error level and less time and labour, on fresh samples.

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A Study on the Construction of Database, Online Management System, and Analysis Instrument for Biological Diversity Data (생물다양성 자료의 데이터베이스화와 온라인 관리시스템 및 분석도구 구축에 관한 연구)

  • Bec Kee-Yul;Jung Jong-Chul;Park Seon-Joo;Lee Jong-Wook
    • Journal of Environmental Science International
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    • v.14 no.12
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    • pp.1119-1127
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    • 2005
  • The management of data on biological diversity is presently complex and confusing. This study was initiated to construct a database so that such data could be stored in a data management, and analysis instrument to correct the problems inherent in the current incoherent storage methods. MySQL was used in DBMS(DataBase Management System), and the program was basically produced using Java technology Also, the program was developed so people could adapt to the requirements that are changing every minute. We hope this was accomplished by modifying easily and quickly the advanced programming technology and patterns. To this end, an effective and flexible database schema was devised to store and analyze diversity databases. Even users with no knowledge of databases should be able to access this management instrument and easily manage the database through the World Wide Web. On a basis of databases stored in this manner, it could become routinely used for various databases using this analysis instrument supplied on the World Wide Web. Supplying the derived results by using a simple table and making results visible using simple charts, researchers could easily adapt these methods to various data analyses. As the diversity data was stored in a database, not in a general file, this study makes the precise, error-free and high -quality storage in a consistent manner. The methods proposed here should also minimize the errors that might appear in each data search, data movement, or data conversion by supplying management instrumentation on the Web. Also, this study was to deduce the various results to the level we required and execute the comparative analysis without the lengthy time necessary to supply the analytical instrument with similar results as provided by various other methods of analysis. The results of this research may be summerized as follows: 1)This study suggests methods of storage by giving consistency to diversity data. 2)This study prepared a suggested foundation for comparative analysis of various data. 3)It may suggest further research, which could lead to more and better standardization of diversity data and to better methods for predicting changes in species diversity.

Design and Manufacture of Improved Obstacle-Overcoming type Indoor Moving and Lifting Electric Wheelchair (향상된 장애물 극복형 실내 이·승강 전동휠체어의 설계 및 제작)

  • Kim, Young-Pil;Ham, Hun-Ju;Hong, Sung-Hee;Ko, Seok-Cheol
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.11
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    • pp.851-860
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    • 2020
  • With an increase in the aging population and a rising social interest in health and welfare, studies to improve healthcare in the elderly are being actively conducted. This study attempted to improve the current design and manufacture of elevating electric wheelchairs to enhance user safety and convenience. Seat design based on the user's body shape, convenience while boarding or alighting, caster turning radius and, safety and stability features that prevent shaking when the user gets up or sits down were improved. A driving experiment was conducted to evaluate the operation of the indoor electric wheelchair designed and manufactured with these additional functionalities. During the test, the performance parameters evaluated were continuous driving time, turning radius, maximum lifting and lowering load, maximum lifting height, noise level, minimum distance sensing by the driving auxiliary sensor, ability to interact with server and app programs, and the duty cycle maximum error rate. The test confirmed that this improved electric wheelchair successfully met target parameters. In a future study, we will evaluate this improved electric wheelchair from a user's perspective for its usability parameters, such as satisfaction, convenience and stability.

Use of Nitrogen Dioxide as Exposure Marker of Passive Smiking for Non-smoking Service-workers at Restaurants (음식점 비흡연 종업원의 간접흡연 노출량 지표로써 이산화질소 이용)

  • Won-Ho Yang;Young-Lim Kho;In-Kyu(Paul) Han;Chong-Min Lee;Moon-Shik Zong;Moon-Ho Chung
    • Journal of environmental and Sanitary engineering
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    • v.15 no.3
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    • pp.1-7
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    • 2000
  • There is increasing evidence suggestion that passive smoking increases the risk of lung cancer and other disease, though the potential health effects of exposure to environmental tobacco smoke (ETS) is a controversial subject. Since smoking in restaurant is prevalent in Korea, the concern on passive smoking exposure of non-smoking service-workers has been requested. ETS exposure of non-smoking service-workers at restaurant was assessed because they hare spent their times in restaurant indoors. The purpose of this study was feasibility of nitrogen dioxide($NO_2$) as exposure marker of ETS. The results of the study were as follows; 1. Average $NO_2$ concentrations in indoor and outdoor t restaurants were 57.1ppb(${\pm}12.4$) and 54.29ppb(${\pm}9.54$), respectively. Comparing office-workers, service-workers at restaurants were exposured highly. 2. The personal $NO_2$ measurement as exposure marker of ETS could cause the exposure error because $NO_2$ can be generated by combustion appliances in indoor. 3. Service-workers spent their most time(86.6%) in indoor. Mean time spent at restaurant indoors and at home was 9.4 hours and 10.9 hours, respectively. 4. Personal $NO_2$ levels correlated with indoor $NO_2$ concentrations of restaurant (r=0.70) and of their home (r=0.52) rather than of outdoor $NO_2$ concentration of restaurant (r=0.35). The cause of personal $NO_2$ exposure of non-smoking service-workers were considered as smoking of guests and combustion appliance indoors. 5. personal $NO_2$ exposures were estimated using Monte-Carlo simulation and time-weighted model. Estimated personal $NO_2$ level was 47.25ppb(${\pm}8.3$).

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