• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.839-850
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• 2021

Risk-adjusted return is believed to be one of the optimal parameters to determine an optimum portfolio. A risk-adjusted return is a calculation of the profit or potential profit from an investment that takes into account the degree of risk that must be accepted to achieve it. This paper presents a new procedure in portfolio selection and utilizes these results to optimize the risk level of risk-adjusted Islamic stock portfolios. It deals with the weekly close price of active issuers listed on Jakarta Islamic Index Indonesia for a certain time interval. Overall, this paper highlights portfolio selection, which includes determining the number of stocks, grouping the issuers via technical analysis, and selecting the best risk-adjusted return of portfolios. The nominated portfolio is modeled using Quadratic Programming (QP). The result of this study shows that the portfolio built using the lowest Value at Risk (VaR) outperforms the market proxy on a risk-adjusted basis of M-squared and was chosen as the best portfolio that can be optimized using QP with a minimum risk of 2.86%. The portfolio with the lowest beta, on the other hand, will produce a minimum risk that is nearly 60% lower than the optimal risk-adjusted return portfolio. The results of QP are well verified by a heuristic optimizer of fmincon.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.54-54
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• 2015

Crops lack genetic resistance to most necrotrophic soil-borne pathogens and parasitic nematodes that are ubiquitous in agroecosystems worldwide. To overcome this disadvantage, plants recruit and nurture specific group of antagonistic microorganisms from the soil microbiome to defend their roots against pathogens and other pests. The best example of this microbe-based defense of roots is observed in disease-suppressive soils in which the suppressiveness is induced by continuously growing crops that are susceptible to a pathogen. Suppressive soils occur globally yet the microbial basis of most is still poorly described. Fusarium wilt, caused by Fusarium oxysporum f. sp. fragariae is a major disease of strawberry and is naturally suppressed in Korean fields that have undergone continuous strawberry monoculture. Here we show that members of the genus Streptomyces are the specific bacterial components of the microbiome responsible for the suppressiveness that controls Fusarium wilt of strawberry. Furthermore, genome sequencing revealed that Streptomyces griseus, which produces a novel thiopetide antibiotic, is the principal species involved in the suppressiveness. Finally, chemical-genetic studies demonstrated that S. griseus antagonizes F. oxysporum by interfering with fungal cell wall synthesis. An attack by F. oxysporum initiates a defensive "cry for help" by strawberry root and the mustering of microbial defenses led by Streptomyces. These results provide a model for future studies to elucidate the basis of microbially-based defense systems and soil suppressiveness from the field to the molecular level.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.247-263
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• 2016

The purpose of the study is to derive success factors of B2C reverse auction business model, a business model contributes to the recent innovative practices in e-commerce and service sector. Electronic reverse auction has been traditionally used to ensure the procurement convenience and purchasing efficiency in B2B or B2G settings, however, e-RA is now expanding its basis toward B2C commerce industry along the huge success of an online e-RA travel service provider Priceline.com. Recently, B2C e-RA business model is getting the spotlight in the Korean venture industry with a variety of startups in diverse areas. However, e-RA does not work perfect in all kinds of trade settings. Therefore, we conducted a multiple case study to find out the success factors of B2C business model as follows : First, large supplier basis is an important factor that constructs a quasi-perfect competition environment. Second, the high online and mobile accessibility or e-readiness of Korean consumers was also a critical aspect of the success of e-RA. Lastly, e-RA performs best when the supplier switching cost is low and the trading occurs infrequently.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.463-474
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• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.39-49
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• 2013

This paper presents a method of improving the performance of a day-ahead 24-h load curve and peak load forecasting. The next-day load curve is forecasted using radial basis function (RBF) neural network models built using the best design parameters. To improve the forecasting accuracy, the load curve forecasted using the RBF network models is corrected by the weighted sum of both the error of the current prediction and the change in the errors between the current and the previous prediction. The optimal weights (called "gains" in the error correction) are identified by differential evolution. The peak load forecasted by the RBF network models is also corrected by combining the load curve outputs of the RBF models by linear addition with 24 coefficients. The optimal coefficients for reducing both the forecasting mean absolute percent error (MAPE) and the sum of errors are also identified using differential evolution. The proposed models are trained and tested using four years of hourly load data obtained from the Korea Power Exchange. Simulation results reveal satisfactory forecasts: 1.230% MAPE for daily peak load and 1.128% MAPE for daily load curve.

• Archives of design research
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• no.18
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• pp.37-48
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• 1996

For succesful political advertisements the role of mutual communications between advertisers and their targets (i.e. voters) should be magnified, which must be based on the understanding of voter's life-style including the trends of daily life, their philosophy and attitude toward the contemporary matters. During the campaign period for the last parliamentry election the most important issue was nothing but who could be the best representer of their region without any political considerations compared to previous election and the decision made by voters has been evaluated as one of most brilliant ones so far. One thing to note from the last election is that many new faces have been high lighted and that could not have been possible if they could not differentiate their campaign from one of unchanged senior politicians by calling more attentions of voters to them by scrutinizing competitors' election pledges. The differentiation strategy in election campaigns is basically detecting small signs of changes in voters life\ulcornerstyle, bringing them into relief and provoking voters attentions to the election and advertiser. In this sense niche marketing strategy is the differentiating strategy itself and it can be a useful guide in political advertisement for the triumph of advertiser in elections as well as for heathy and fresh political environments on the basis increased attentions of voters. In this paper, aiming at further development of the niche marketing in political advertisements we propose questions whether the niche marketing in the last parliamentary election was introduced on the basis of concept of differentation by analysing last election's strategies targeted at voters specific dispositions.

• Journal of computational fluids engineering
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• v.9 no.4
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• pp.55-63
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• 2004

The three-dimensional Stokes flow within a staggered screw channel is obtained by using a finite volume method. The geometry is intended to mimic the single screw extruder having staggered arrangement of flights. The flow solution is then subjected to the analysis of the stirring performance. In the analysis of the stirring performance, the stretching-mapping method developed by the author is employed for calculating the materials' stretching exponents, which are to be used in quantification of the mixing effect. The numerical results Indicate that the staggered geometry gives indeed far much better stirring-performance than the standard (nonstaggered) flight geometry. It was also shown that care must be given to the selection of the basis planes for evaluating the local stretching rate, and it turns out that the best method (H-method) has its basis plane just on the half way between the past and future evolution of fluid particles subjected to the defromation. In evaluating the stretching exponent, the expansion ratio must be considered which is one of the characteristic differences of the actual three-dimensional flows from the two-dimensionmal counterparts. The larger axial pressure-difference causes in general the smaller stirring performance while the flow rate is increased. The smaller channel length also increases the stirring performance.

• Journal of Integrative Natural Science
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• v.3 no.4
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• pp.231-236
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• 2010

Partial charge is an important and fundamental concept which can explain many aspects of chemistry. Since a molecule can be regarded as neclei surrounded by electron cloud, there is no way to define a partial charge accurately. Nevertheless, there have been many attempts to define these seemingly impossible parameters, since they would facilitate the understanding of molecular properties such as molecular dipole moment, solvation, hydrogen bonding, molecular spectroscopy, chemical reaction, etc. Common methods are based on the charge equalization, orbital occupancy, charge density, and electric multipole moments, and electrostatic potential fitting. Methods based on the charge equalization using electronegativity are very fast, and therefore they have been used to study many compounds. Methods to subdivide orbital occupancy using basis set conversion, relies on the notion that molecular orbitals are composed of atomic orbitals. The main idea is to reduce overlap integral between two nuclei using converted orthogonal basis sets. Using some quantum mechanical observables like electrostatic potential or charge multipole moments. Using potential grids obtained from wavefunction, partial charges can be fitted. these charges are most useful to describe intermolecular electrostatic interactions. Methods to using dipole moment and its derivatives, seems to be sensitive the level of theory, Dividing electron density using density gradient being the most rigorous theoretically among various schemes, bears best potential to describe the charge the most adequately in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.912-915
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• 2002

This paper presents off-line handwritten numeral recognition method by using Eigen-Vectors. In this method, numeral features are extracted statistically by using Eigen-Vectors through KL transform and input numeral is recognized in the feature space by the nearest-neighbor classifier. In our feature extraction method, basis vectors which express best the property of each numeral type within the extensive database of sample numeral images are calculated, and the numeral features are obtained by using this basis vectors. Through the experiments with the unconstrained handwritten numeral database of Concordia University, we have achieved a recognition rate of 96.2%.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2107-2115
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• 2018

Over recent years, high-concentration of particulate matters (e.g., a.k.a. fine dust) in South Korea has increasingly evoked considerable concerns about public health. It is intractable to track and report $PM_{10}$ measurements to the public on a real-time basis. Even worse, such records merely amount to averaged particulate concentration at particular regions. Under this circumstance, people are prone to being at risk at rapidly dispersing air pollution. To address this challenge, we attempt to build a predictive model via deep learning to the concentration of particulates ($PM_{10}$). The proposed method learns a binary decision rule on the basis of video sequences to predict whether the level of particulates ($PM_{10}$) in real time is harmful (>$80{\mu}g/m^3$) or not. To our best knowledge, no vision-based $PM_{10}$ measurement method has been proposed in atmosphere research. In experimental studies, the proposed model is found to outperform other existing algorithms in virtue of convolutional deep learning networks. In this regard, we suppose this vision based-predictive model has lucrative potentials to handle with upcoming challenges related to particulate measurement.