• BMB Reports
• /
• v.30 no.6
• /
• pp.390-396
• /
• 1997

A sandwich-type enzyme-linked immunosorbent assay (ELISA) for the quantification of human apolipoprotein A-I (apoA-I) was developed using monoclonal antibodies. For this assay, we used three monoclonal antibodies to trap and detect apo A-I. HDAI16 and HDA15 monoclonal antibodies were used for trapping apoA-I and HDAI8 monoclonal antibody was for detecting apoA-I. These three monoclonal antibodies were produced by immunizing mice with high density lipoprotein (HDL) isolated from human plasma. By immunoblot analysis, these three monoclonal antibodies were specific to apoA-I and showed no cross-reactivities with other plasma proteins. The results of competition assays for epitope cross-reactivity test also verified that these monoclonal antibodies identified separate and distinct epitopes on HDL and apoA-I. Affinity constants of monoclonal antibodies were measured by ELISA. Their association constants ranged from $10^7$ to $10^8$ $M^{-1}$. For this assay, pure apoA-I was isolated by affinity chromatography using monoclonal antibodies. In this sandwich assay, the amount of HRP-labeled HDAI8 bound to apoA-I trapped by HDAI16 and HDAI5 was proportional to apoA-I concentration in the range of 0 to 500ng/ml. ApoA-I concentration in plasma was calculated from the linear regression equation of standard curve. The precision and reliability of the assays are reflected in the low intra-and interassay coefficients of variation that averaged 3.25% and 4.30%, respectively. This assay is sensitive, simple, reproducible, convenient in incubation interval, and does not use radioisotope: thus it can be widely applied in clinical laboratories.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.65-82
• /
• 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.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.30 no.4
• /
• pp.460-470
• /
• 1985

Experiments were carried out to evaluate the standard gravity in determining potential kernel size and to determine the effective sampling way by analyzing intra - and inter - plant variations for some source and sink characters using eleven semi-dwarf indica and three japonica cultivars including four semi-dwarf indica nearisogenic lines. Also, additional experiments were conducted to understand yearly variation and variety x year interaction effects for ten characters related to source and sink and to characterize the varietal difference of pre- and post-heading self-competition employing three parental varieties and their F$\sub$5/ progenies in 1982 and 1983. It is desirable to determine the potential kernel size by average kernel wight of rice grains showing above 1.15 specific gravity. There was significant difference in leaf area per tiller, spikelets and sink capacity per panicle among vigorous, intermediate and inferior tillers classified by differentiated order and vigorousness. Although it was difficult to find out any significant difference in grain-fill ratio, ratio of perfectly ripened grain, potential kernel size and sink/source ratio between vigorous and intermediate tillers, there was big difference between them and inferior one. The coefficients of variation within each tiller-group for some characters related to source and sink were larger with the order of vigorous tillers < intermediate one '||'&'||'lt; inferior one, and the average heritability of all characters, evaluated by the ratio of varietal variance (equation omitted) to total variance (equation omitted), were higher with the order of inferior tillers '||'&'||'lt; intemediate one '||'&'||'lt; superior one. Therefore, it is desirable to sample the vigorous tillers to represent the varietal difference of these traits. '82-'83 year variations of three parental cultivars were significant for all traits except for leaf area/tiller, panicles/hill, leaf area index and rough rice yield. The characters showing highly significant variance of variety x year interaction were growth duration from transplanting to heading, leaf area/tiller, sink/source ratio, sink capacity/panicle and grain yield. Generalized yearly response of three parental varieties (Suweon 264, Raegyeong, IR1317-70-l) and their F$\sub$5/ progenies on the 1st and 2nd principal components extracted from ten source and sink characters generally exhibited reduction in both source and sink. However, there were diverse variety x year interactions such as progenies showing similar reaction with their parents and intermediate or recombinational yearly response with little or considerable yearly movement on the four-dimensional planes of the two upper principal components between 1982 and 1983. Sink characters revealing highly significant border effect were grain-fill ratio, spikelets and sink capacity per panicle. Among them the latter two especially showed significant variety x border effect interaction. Self-competition characterized by relative weakness of inside plant's sink characters compared to the border one was more severe during the reproductive stage before heading than maturing stage. Though the larger sink capacity per panicle generally disclosed the severer self-competition, some lines (like Suweon 264) revealed severe self-competition with small sink capacity while a few others showed tender self-competition in spite of big sink capacity per panicle.

• Korean Journal of Weed Science
• /
• v.2 no.2
• /
• pp.75-113
• /
• 1982

Studies were carried out 1) to define the shape and size of sampling quadrat and its number of observations for weed experiments, 2) to characterize the growth and community of major summer weeds under upland condition and 3) to investigate the factors influencing competition between weeds and soybeans under weed-free and weedy conditions in early and late season cultures. No significant difference was noted among different shapes of quadrat (regular, rectangular, band, and circular) in the sampling efficiency of weeds. The results also suggested that the minimum size of quadrat was 0.25$m^2$ and the minimum number of replication was 2 times per plot. The major dominant weeds were about 10 species in the experimental field and the total number of weeds was in the range of 70 - 1,600 plants per $m^2$. Among the weeds Digitaria sanguinalis and Portulaca oleracea were the most dominant species. Growth amount and reproduction capability were also measured by weed species. Five different weed communities were identified in the field. The degree of dispersion by weed species and association among weeds were investigated. Intra-(within soybeans) and inter-specific (between soybeans and weeds) competition were studied in early and late season cultures of soybeans. The average yield of soybeans per plant was significantly decreased in both season cultures due to intra-specific competition as the planting density of soybeans increased, On the other hand, the average yield of soybeans per l0a was proportionally increased to the increase of planting density and the rate of its increase was more significant under weedy than weed-free condition. Most of the agronomic characteristics of soybeans were affected by weeds and its degree was greater in sparse planting than in dense planting and in early season than in late-season culture. Digitaria sanguinalis was the most competitive to soybeans in early season and both of Digitaria sanguinalis and Portulaca oleracea affected primarily the growth of soybeans in late season with about the same competitiveness. The occurrence of weeds was significantly decreased in early season and slightly decreased in late-season by dense planting of soybeans. The total growth amount of weeds was also considerably decreased by increase of soybean planting density both in early- and late-season cultures. The occurrence of Digitaria sanguinalis which was the most dominant in both seasons, and its growth amount was significantly decreased as the planting density of soybean was increased. On the other hand, the occurrence of Portulaca oleracea which was only dominant in late-season culture did not show significant response to the planting density of soybeans.