• Title/Summary/Keyword: generalized free products

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Deep Learning-based Product Recommendation Model for Influencer Marketing (인플루언서를 위한 딥러닝 기반의 제품 추천모델 개발)

  • Song, Hee Seok;Kim, Jae Kyung
    • Journal of Information Technology Applications and Management
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    • v.29 no.3
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    • pp.43-55
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    • 2022
  • In this study, with the goal of developing a deep learning-based product recommendation model for effective matching of influencers and products, a deep learning model with a collaborative filtering model combined with generalized matrix decomposition(GMF), a collaborative filtering model based on multi-layer perceptron (MLP), and neural collaborative filtering and generalized matrix Factorization (NeuMF), a hybrid model combining GMP and MLP was developed and tested. In particular, we utilize one-class problem free boosting (OCF-B) method to solve the one-class problem that occurs when training is performed only on positive cases using implicit feedback in the deep learning-based collaborative filtering recommendation model. In relation to model selection based on overall experimental results, the MLP model showed highest performance with weighted average precision, weighted average recall, and f1 score were 0.85 in the model (n=3,000, term=15). This study is meaningful in practice as it attempted to commercialize a deep learning-based recommendation system where influencer's promotion data is being accumulated, pactical personalized recommendation service is not yet commercially applied yet.

Demographic and lifestyle factors and selenium levels in men and women in the U.S.

  • Park, Kyong;Rimm, Eric;Siscovick, David;Spiegelman, Donna;Morris, J. Steven;Mozaffarian, Dariush
    • Nutrition Research and Practice
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    • v.5 no.4
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    • pp.357-364
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    • 2011
  • Selenium is an antioxidant trace element linked to cardiovascular disease and cancer. Although diet is a major source, relatively little else is known about independent determinants of selenium levels in free-living humans. In this study, we aimed to investigate the independent demographic. lifestyle, and dietary determinants of selenium levels in 1,997 men and 1,905 women in two large prospective U.S. cohorts. Toenail selenium levels were quantified using neutron activation analysis. Diet, geographic residence, demographic, and environmental factors were assessed by validated self-administered questionnaires. Multivariate generalized linear models were conducted to assess the independent relations of these factors with toenail selenium levels, correcting for measurement error in the diet. In multi variable-adjusted analyses, independent predictors of higher selenium were male gender (6.3% higher levels); living in West and Northern-Midwest U.S. regions (8.9% and 7.4% higher than Southern-Midwest regions, respectively); consumption of beef and bread products (between 0.7 - 2.5% higher per daily serving); and selenium supplement use (6.9% higher than non-users); whereas cigarette smoking (5-10% lower than never smokers), older age (0.6% lower per 5 years), and consumption of eggs, white rice, dairy products, coffee, and alcohol (between 0.1 to 2.0% lower per daily serving) were associated with lower selenium. Multiple dietary and non-dietary factors independently predicted selenium levels, suggesting that both consumption and non-dietary processes (e.g.. related to oxidant status) may affect levels. Significant geographic variation in selenium levels exists in the US.

Mechanical and Rheological Properties of Rice Plant (수도(水稻)의 역학적(力學的) 및 리올러지 특성(特性)에 관(關)한 연구(硏究))

  • Huh, Yun Kun;Cha, Gyun Do
    • Korean Journal of Agricultural Science
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    • v.14 no.1
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    • pp.98-133
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    • 1987
  • The mechanical and rheological properties of agricultural materials are important for engineering design and analysis of their mechanical harvesting, handling, transporting and processing systems. Agricultural materials, which composed of structural members and fluids do not react in a purely elastic manner, and their response when subjected to stress and strain is a combination of elastic and viscous behavior so called viscoelastic behavior. Many researchers have conducted studies on the mechanical and rheological properties of the various agricultural products, but a few researcher has studied those properties of rice plant, and also those data are available only for foreign varieties of rice plant. This study are conducted to experimentally determine the mechanical and the rheological properties such as axial compressive strength, tensile strength, bending and shear strength, stress relaxation and creep behavior of rice stems, and grain detachment strength. The rheological models for the rice stem were developed from the test data. The shearing characteristics were examined at some different levels of portion, cross-sectional area, moisture content of rice stem and shearing angle. The results obtained from this study were summarized as follows 1. The mechanical properties of the stems of the J aponica types were greater than those of the Indica ${\times}$ Japonica hybrid in compression, tension, bendingand shearing. 2. The mean value of the compressive force was 80.5 N in the Japonica types and 55.5 N in the Indica ${\times}$ Japonica hybrid which was about 70 percent to that of the Japonica types, and then the value increased progressively at the lower portion of the stems generally. 3. The average tensile force was about 226.6 N in the Japonica types and 123.6 N in the Indica ${\times}$ Japonica hybrid which was about 55 percent to that of the Japonica types. 4. The bending moment was $0.19N{\cdot}m$ in the Japonica types and $0.13N{\cdot}m$ in the Indica ${\times}$ Japonica hybrid which was 68 percent to that of the Japonica types and the bending strength was 7.7 MPa in the Japonica types and 6.5 MPa in the Indica ${\times}$ Japonica hybrid respectively. 5. The shearing force was 141.1 N in Jinju, the Japonica type and 101.4 N in Taebaeg, the Indica ${\times}$ Japonica hybrid which was 72 percent to that of Jinju, and the shearing strength of Taebaeg was 63 percent to that of Jinju. 6. The shearing force and the shearing energy along the stem portion in Jinju increased progressively together at the lower portions, meanwhile in Taebaeg the shearing force showed the maximum value at the intermediate portion and the shearing energy was the greatest at the portion of 21 cm from the ground level, and also the shearing strength and the shearing energy per unit cross-sectional area of the stem were the greater values at the intermediate portion than at any other portions. 7. The shearing force and the shearing energy increased with increase of the cross-sectional area of the rice stem and with decrease of the shearing angie from $90^{\circ}$ to $50^{\circ}$. 8. The shearing forces showed the minimum values of 110 N at Jinju and of 60 N at Taebaeg, the shearing energy at the moisture content decreased about 15 percent point from initial moisture content showed value of 50 mJ in Jinju and of 30 mJ in Taebaeg, respectively. 9. The stress relaxation behavior could be described by the generalized Maxwell model and also the compression creep behavior by Burger's model, respectively in the rice stem. 10. With increase of loading rate, the stress relaxation intensity increased, meanwhile the relaxation time and residual stress decreased. 11. In the compression creep test, the logarithmic creep occured at the stress less than 2.0 MPa and the steady-state creep at the stress larger than 2.0 MPa. 12. The stress level had not a significant effect on the relaxation time, while the relaxation intensity and residual stress increased with increase of the stress level. 13. In the compression creep test of the rice stem, the instantaneous elastic modulus of Burger's model showed the range of 60 to 80 MPa and the viscosities of the free dashpot were very large numerical value which was well explained that the rice stem was viscoelastic material. 14. The tensile detachment forces were about 1.7 to 2.3 N in the Japonica types while about 1.0 to 1.3 N in Indica ${\times}$ Japonica hybrid corresponding to 58 percent of Japonica types, and the bending detachment forces were about 0.6 to 1.1 N corresponding to 30 to 50 percent of the tensile detachment forces, and the bending detachment of the Indica ${\times}$ Japonica hybrid was 0.1 to 0.3 N which was 7 to 21 percent of Japonica types. 15. The detachment force of the lower portion was little bigger than that of the upper portion in a penicle and was not significantly affected by the harvesting period from September 28 to October 20. 16. The tensile and bending detachment forces decreased with decrease of the moisture content from 23 to 13 percent (w.b.) by the natural drying, and the decreasing rate of detachment forces along the moisture content was the greater in the bending detachment force than the tensile detachment force.

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A Study on Developing a VKOSPI Forecasting Model via GARCH Class Models for Intelligent Volatility Trading Systems (지능형 변동성트레이딩시스템개발을 위한 GARCH 모형을 통한 VKOSPI 예측모형 개발에 관한 연구)

  • Kim, Sun-Woong
    • Journal of Intelligence and Information Systems
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    • v.16 no.2
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    • pp.19-32
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    • 2010
  • Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.