• Title/Summary/Keyword: Surface classification

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PCA­based Waveform Classification of Rabbit Retinal Ganglion Cell Activity (주성분분석을 이용한 토끼 망막 신경절세포의 활동전위 파형 분류)

  • 진계환;조현숙;이태수;구용숙
    • Progress in Medical Physics
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    • v.14 no.4
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    • pp.211-217
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    • 2003
  • The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

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Development of Decision Tree Software and Protein Profiling using Surface Enhanced laser Desorption/lonization - Time of Flight - Mass Spectrometry (SELDI-TOF-MS) in Papillary Thyroid Cancer (의사결정트리 프로그램 개발 및 갑상선유두암에서 질량분석법을 이용한 단백질 패턴 분석)

  • Yoon, Joon-Kee;Lee, Jun;An, Young-Sil;Park, Bok-Nam;Yoon, Seok-Nam
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.4
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    • pp.299-308
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    • 2007
  • Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

A Program of Water Quality Management for Agricultural Reservoirs by Trophic State (농업용 저수지의 부영양화와 수질관리방안)

  • Lee, Kwang-Sik;Yoon, Kyung-Sup;Kim, Ho-Il;Kim, Hyung-Joong
    • Korean Journal of Environmental Agriculture
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    • v.22 no.2
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    • pp.166-171
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    • 2003
  • A total of 498 agricultural reservoirs ranging from $164{\times}10^3\;m^3$ to $253{\times}10^6\;m^3$ in storage volume were investigated from 1990 to 2001 with respect to Chl-${\alpha}$, COD concentration and pollutant loading of BOD, TN, and TP. The lakes and reservoirs could be classified to 4 types using the relationships between the ratio of storage volume per water surface area(ST/WS) and Chl-${\alpha}$ concentration. It is recommended that the improvement of polluted lakes should be performed in the order of integrated consolidation type ${\rightarrow}$ watershed consolidation type ${\rightarrow}$ in-lake consolidation type ${\rightarrow}$ Management type and reservoir should be constructed to be over $5{\sim}6\;m$ in depth(ST/WS ratio) for preventing the eutrophication of agricultural reservoirs. We propose that water quality criteria for agricultural water is changed from less than 8 mg/L to less than 6 mg/L for safety value, $6{\sim}10\;mg/L$ for concern value, and more than 10 mg/L for countermeasure value in COD concentration, respectively.

Suitability Classes for Italian Ryegrass (Lolium multiflorum Lam.) Using Soil and Climate Digital Database in Gangwon Province (강원도에서 토양과 기후 데이터베이스를 이용한 이탈리안 라이그라스의 재배 적지 구분)

  • Kim, Kyung-Dae;Sung, Kyung-Il;Jung, Yeong-Sang;Lee, Hyun-Il;Kim, Eun-Jeong;Nejad, Jalil Ghassemi;Jo, Mu-Hwan;Lim, Young-Chul
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.32 no.4
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    • pp.437-446
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    • 2012
  • As a part of establishing suitability classification for forage production, use of the national soil and climate database was attempted for Italian ryegrass (Lolium multiflorum Lam., IRG) in Gangwon Province. The soil data base were from Heugtoram of the National Academy of Agricultural Science, and the climate data base were from the National Center for Agro-Meteorology, respectively. Soil physical properties including soil texture, drainage, slope available depth and surface rock contents, and soil chemical properties including soil acidity and salinity, organic matter content were selected as soil factors. The crieria and weighting factors of these elements were scored. Climate factors including average daily minimum temperature, average temperature from March to May, the number of days of which average temperature was higher than $5^{\circ}C$ from September to December, the number of days of precipitation and its amount from October to May of the following year were selected, and criteria and weighting factors were scored. The electronic maps were developed with these scores using the national data base of soil and climate. Based on soil scores, the area of Goseong, Sogcho, Gangreung, and Samcheog in east coastal region with gentle slope were classified as the possible and/or the proper area for IRG cultivation in Gangwon Province. The lands with gentle or moderate slope of Cheolwon, Yanggu, Chuncheon, Hweongseong, Pyungchang and Jeongsun in west side slope of Taebaeg mountains were classified as the possible and/or proper area as well. Based on climate score, the east coastal area of Goseong, Sogcho, Yangyang, Gangreung and Samcheog could be classified as the possible or proper area. Most area located on west side of the Taebaeg mountains were classified as not suitable for IRG production. In scattered area in Chuncheon and Weonju, where the scores exceeded 60, the IRG cultivation should be carefully managed for good production. For better application of electronic maps.

Trend and Further Research of Rice Quality Evaluation (쌀의 품질평가 현황과 금후 연구방향)

  • Son, Jong-Rok;Kim, Jae-Hyun;Lee, Jung-Il;Youn, Young-Hwan;Kim, Jae-Kyu;Hwang, Hung-Goo;Moon, Hun-Pal
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.47
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    • pp.33-54
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    • 2002
  • Rice quality is much dependent on the pre-and post harvest management. There are many parameters which influence rice or cooked rice qualitys such as cultivars, climate, soil, harvest time, drying, milling, storage, safety, nutritive value, taste, marketing, eating, cooking conditions, and each nations' food culture. Thus, vice evaluation might not be carried out by only some parameters. Physicochemical evaluation of rice deals with amy-lose content, gelatinizing property, and its relation with taste. The amylose content of good vice in Korea is defined at 17 to 20%. Other parameters considered are as follows; ratio of protein body-1 per total protein amount in relation to taste, and oleic/linoleic acid ratio in relation to storage safety. The rice higher Mg/K ratio is considered as high quality. The optimum value is over 1.5 to 1.6. It was reported that the contents of oligosaccharide, glutamic acid or its derivatives and its proportionalities have high corelation with the taste of rice. Major aromatic compounds in rice have been known as hexanal, acetone, pentanal, butanal, octanal, and heptanal. Recently, it was found that muco-polysaccharides are solubilized during cooking. Cooked rice surface is coated by the muco-polysaccharide. The muco-polysaccharide aye contributing to the consistency and collecting free amino acids and vitamins. Thus, these parameters might be regarded as important items for quality and taste evaluation of rice. Ingredients of rice related with the taste are not confined to the total rice grain. In the internal kernel, starch is main component but nitrogen and mineral compounds are localized at the external kernel. The ingredients related with taste are contained in 91 to 86% part of the outside kernel. For safety that is considered an important evaluation item of rice quality, each residual tolerance limit for agricultural chemicals must be adopted in our country. During drying, rice quality can decline by the reasons of high drying temperature, overdrying, and rapid drying. These result in cracked grain or decolored kernel. Intrinsic enzymes react partially during the rice storage. Because of these enzymes, starch, lipid, or protein can be slowly degraded, resulting in the decline of appearance quality, occurrence of aging aroma, and increased hardness of cooked rice. Milling conditions concerned with quality are paddy quality, milling method, and milling machines. To produce high quality rice, head rice must contain over three fourths of the normal rice kernels, and broken, damaged, colored, and immature kernels must be eliminated. In addition to milling equipment, color sorter and length grader must be installed for the production of such rice. Head rice was examined using the 45 brand rices circulating in Korea, Japan, America, Australia, and China. It was found that the head rice rate of brand rice in our country was approximately 57.4% and 80-86% in foreign countries. In order to develop a rice quality evaluation system, evaluation of technics must be further developed : more detailed measure of qualities, search for taste-related components, creation and grade classification of quality evaluation factors at each management stage of treatment after harvest, evaluation of rice as food material as well as for rice cooking, and method development for simple evaluation and establishment of equation for palatability. On policy concerns, the following must be conducted : development of price discrimination in conformity to rice cultivar and grade under the basis of quality evaluation method, fixation of head rice branding, and introduction of low temperature circulation.

Aesthetic Landscape Assessment Based on Landscape Units in the Han River Riparian Area (경관단위 기반 수변환경의 심미적 평가 - 한강 수변을 대상으로 -)

  • Bae, Min-Ki;Park, Chang-Sug;Oh, Chung-Hyun
    • Journal of the Korean Institute of Landscape Architecture
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    • v.40 no.1
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    • pp.43-56
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    • 2012
  • The purpose of this study was to propose management strategies through aesthetic landscape assessments for landscape units in the Han River riparian(HRR) area. First, this research reclassified the HRR into "natural," "artificial," "agricultural," and mixed landscape types and selected 37 representative case areas(about $1km{\times}1km$). This study found 71 landscape units in consideration of topography and land surface classification. Landscape assessment consisted of landscape quality and landscape integration assessment. The criteria for assessing landscape quality were "naturalness," "interest," "uniqueness," and "landscape function." "Landscape quality" was ranked into five grades using a matrix. The landscape integration assessment consisted of an inner integration assessment in each landscape unit and outer integration assessment among landscape units. As a result of the field study, case sites were found to have 4,288 landscape units and an area of $42.8km^2$. The forest area was found to have the most space with $11,580,905m^2$(27.1%), while the wet lands had just $52,348m^2$(0.1%). In the landscape quality assessment, about 30.5% of the total area consisted of landscape units that scored highest in "naturalness". In the landscape integration assessment, about 39.3% of the total area consisted of landscape units which scored highest in "integration", denoting visual interrelation and harmony. The existence of disparities in landscape quality in accordance with the form of the landscaping was determined using a Oneway ANOVA, with "naturalistic" landscaping scoring the highest and "artificial" landscaping scoring lowest. This study may contribute to making the HRR area a more ecologically sound and visually attractive landscape space. It is recommended that the aesthetical and ecological value of the landscape unit should be assessed simultaneously in the future.

The Ecological Characteristics and Conservation Counterplan of Menyanthes trifoliata Habitat in Floating Mat in Korean East Coastal Lagoon, Sunyoodam (조름나물이 서식하는 동해안 석호 습지인 선유담의 생태적 특성 및 보전방안)

  • Kim, Heung-Tae;Lee, Gwang-Moon;Kim, Jae Geun
    • Journal of Wetlands Research
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    • v.15 no.1
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    • pp.25-34
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    • 2013
  • The purpose of this study is to investigate the properties of Menyanthes trifoliata habitat in coastal lagoons. To characterize plant composition in the habitats in the lagoon, the plot sampling method was applied. The depths of water and floating mat were measured. Surface water quality factors including pH, electrical conductivity (EC), dissolved oxygen (DO), and total dissolved solids (TDS) were measured in the sites. Phosphate, nitrate, ammonium, and major cations were measured in laboratory. The wetland has 78 taxa of wetland plants. The average coverage and density of M. trifoliata was 62.6% and $71.2/m^2$, respectively and Phragmites australis is important associate in Sunyoodam lagoon. The average depths of floating mats were 26.5cm in M. trifoliata and 68.9cm in the P. australis-M. trifoliata communities, and the water depth below the mat was 106.5cm and 17.7cm, respectively. The values of pH, DO, EC and TDS in the water were 5.06, 46.1%, 59.4 ${\mu}s/cm$, and 29.3 mg/L, respectively. The concentrations of phosphate, nitrate, and ammonium showed 47.2, 9321, and 15.9 ${\mu}g/L$, respectively. The concentrations of Ca, K, Na, and Mg had 11.1, 1.5, 15.1, and 11.3 mg/L, respectively. The habitats of M. trifoliata in the lagoon corresponds to a kind of lowland communities in Hewett's classification. To conserve the habitats of M. trifoliata in Sunyoodam lagoon, the supply of open water area, the construction of observation deck, and the block of inflow from the surrounding paddy fields are needed in the future.

Verification of Kompsat-5 Sigma Naught Equation (다목적실용위성 5호 후방산란계수 방정식 검증)

  • Yang, Dochul;Jeong, Horyung
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1457-1468
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    • 2018
  • The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.

A Study on the Application of Physical Soil Washing Technology at Lead-contaminated Shooting Range in a Closed Military Shooting Range Area (폐 공용화기사격장 내 납오염 사격장 군부지의 물리적 토양세척정화기술 적용성 연구)

  • Jung, Jaeyun;Jang, Yunyoung
    • Journal of Environmental Impact Assessment
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    • v.28 no.5
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    • pp.492-506
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    • 2019
  • Heavy metal contaminants in the shooting range are mostly present in a warhead circle or a metal fragment present as a particle, these fine metal particles are weathered for a long period of time is very likely that the surface is present as an oxide or carbon oxide. In particular, lead which is a representative contaminant in the shooting range soil, is present as more fine particles because it increases the softness and is stretched well. Therefore, by physical washing experiment, we conducted a degree analysis, concentration of heavy metals by cubic diameter, composition analysis of metallic substances, and assessment of applicability of gravity, magnetism and floating selection. The experimental results FESEM analysis and the measurement results lead to the micro-balance was confirmed thatthe weight goes outless than the soil ofthe same size in a thinly sliced and side-shaped structure according to the dull characteristics it was confirmed that the high specific gravity applicability. In addition, the remediation efficiency evaluation results using a hydrocyclone applied to this showed a cumulative remediation efficiency of 71%,twice 80%, 3 times 91%. On the other hand, magnetic sifting showed a low efficiency of 17%,floating selection -35mesh (0.5mm)target soil showed a relatively high efficiency to 39% -10mesh (2mm) efficiency was only 16%. The target treatment diameter of soil washing should be 2mm to 0.075mm, which is applied to the actual equipment by adding an additional input classification, which would require management as additional installation costs and processes are constructed. As a result, it is found that the soilremediation of shooting range can be separately according to the size of the warhead. The size is larger than the gravel diameter to most 5.56mm, so it is possible to select a specific gravity using a high gravity. However, the contaminants present in the metal fragments were found to be processed by separating using a hydrocyclone of the soil washing according to the weight is less than the soil of the same particle size in a thinly fragmented structure.

Performance of Investment Strategy using Investor-specific Transaction Information and Machine Learning (투자자별 거래정보와 머신러닝을 활용한 투자전략의 성과)

  • Kim, Kyung Mock;Kim, Sun Woong;Choi, Heung Sik
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.65-82
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    • 2021
  • Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.