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EXPLICIT FORMULAS FOR KOROBOV POLYNOMIALS
DMITRY V. KRUCHININ 장전수학회 2017 Proceedings of the Jangjeon mathematical society Vol.20 No.1
In this paper we find some explicit and recurrence formulas for the Korobov polynomials and numbers. Also, author gives another explicit formulas for the degenerate Bernoulli polynomials and numbers. New recursion formulas and identities for these polynomials are also obtained.
A note on Carlitz's type q-Changhee numbers and polynomials
Dmitry V. Dolgy,장관우,권혁인,김태균 장전수학회 2017 Advanced Studies in Contemporary Mathematics Vol.27 No.4
In this paper, we consider the Carlitz's type q-analogue of Changhee numbers and polynomials and we give some explicit formulae for these numbers and polynomials.
EXPLICIT EXPRESSIONS FOR CATALAN-DAEHEE NUMBERS
Dmitry V. Dolgy,장관우,김대산,김태균 장전수학회 2017 Proceedings of the Jangjeon mathematical society Vol.20 No.1
In this paper, we give some new and interesting identities and properties for the Catalan-Daehee numbers arising from p-adic invariant inte- grals on Zp.
SUMS OF FINITE PRODUCTS OF ORDERED BELL FUNCTIONS
DMITRY V. DOLGY,김대산,김태균,장관우,Toufik Mansour 장전수학회 2018 Advanced Studies in Contemporary Mathematics Vol.28 No.3
We study three different types of sums of finite products of ordered Bell functions. We derive Fourier series expansion for them and express each of them in terms of Bernoulli functions.
Dmitry Aleksandrovich Zinovkin,Sergey Leonidovich Achinovich,Mikhail Grigoryevich Zubritskiy,Jacqueline Linda Whatmore,Md Zahidul Islam Pranjol 대한병리학회 2019 Journal of Pathology and Translational Medicine Vol.53 No.5
Background: In this study, we investigate the expression of markers of angiogenesis and microvessel density (MVD) in cases of microcystic, elongated and fragmented (MELF) pattern, with its prognostic role in the survival of endometrioid endometrial adenocarcinomas (EA) patients. Methods: In this study, 100 cases of EA, 49 cases with MELF pattern and 51 without, were immunohistochemically stained for galectin-1, vascular endothelial growth factor (VEGF), and MVD. Morphometry and statistical (univariate and multivariate) analyses were performed to assess overall survival (OS) and disease-free survival. Results: The expression of VEGF (p < .001) and galectin-1 (p < .001), as well as MVD area (p < .001) and number of vessels/mm2 (p < .050), were significantly higher in the +MELF pattern group compared to the –MELF group. A low negative correlation between MELF-pattern and the number of days of survival (p < .001, r = –0.47) was also found. A low positive correlation of MELF-pattern with galectin-1 expression (p < .001, r = 0.39), area of vessels/mm2 (p < .001, r = 0.36), outcome of EA (p < .001, r = 0.42) and VEGF expression (p < .001, r = 0.39) suggests potential pathological relevance of these factors in the prognosis of EA. A univariate survival analysis indicated a role for all parameters of survival. Multivariate Cox proportional hazard regression analysis revealed that only area of vessels/mm2 (hazard ratio [HR], 1.018; 95% confidence interval [CI], 1.002 to 1.033), galectin-1 (HR, 1.049; 95% CI, 1.025 to 1.074) and VEGF (HR, 1.049; 95% CI, 1.022 to 1.077) play key roles in OS. Conclusions: This study reports an increase in MVD, VEGF and galectin-1 expression in EA with MELF pattern and suggests that MELF pattern, along with the angiogenic profile, may be a prognostic factor in EA.
Deep learning in nickel-based superalloys solvus temperature simulation
Dmitry A., Tarasov,Andrey G., Tyagunov,Oleg B., Milder Techno-Press 2022 Advances in aircraft and spacecraft science Vol.9 No.5
Modeling the properties of complex alloys such as nickel superalloys is an extremely challenging scientific and engineering task. The model should take into account a large number of uncorrelated factors, for many of which information may be missing or vague. The individual contribution of one or another chemical element out of a dozen possible ligants cannot be determined by traditional methods. Moreover, there are no general analytical models describing the influence of elements on the characteristics of alloys. Artificial neural networks are one of the few statistical modeling tools that can account for many implicit correlations and establish correspondences that cannot be identified by other more familiar mathematical methods. However, such networks require careful tuning to achieve high performance, which is time-consuming. Data preprocessing can make model training much easier and faster. This article focuses on combining physics-based deep network configuration and input data engineering to simulate the solvus temperature of nickel superalloys. The used deep artificial neural network shows good simulation results. Thus, this method of numerical simulation can be easily applied to such problems.
Deep learning in nickel-based superalloys solvus temperature simulation
Dmitry A., Tarasov,Andrey G., Tyagunov,Oleg B., Milder Techno-Press 2022 Advances in aircraft and spacecraft science Vol.9 No.5
Modeling the properties of complex alloys such as nickel superalloys is an extremely challenging scientific and engineering task. The model should take into account a large number of uncorrelated factors, for many of which information may be missing or vague. The individual contribution of one or another chemical element out of a dozen possible ligants cannot be determined by traditional methods. Moreover, there are no general analytical models describing the influence of elements on the characteristics of alloys. Artificial neural networks are one of the few statistical modeling tools that can account for many implicit correlations and establish correspondences that cannot be identified by other more familiar mathematical methods. However, such networks require careful tuning to achieve high performance, which is time-consuming. Data preprocessing can make model training much easier and faster. This article focuses on combining physics-based deep network configuration and input data engineering to simulate the solvus temperature of nickel superalloys. The used deep artificial neural network shows good simulation results. Thus, this method of numerical simulation can be easily applied to such problems.
독점 및 복점시장 판매자의 부정적 정보 공개에 관한 실험 연구
( Dmitry A. Shapiro ),이재선 ( Jaesun Lee ) 한국경제학회 2022 The Korean Economic Review Vol.38 No.1
본 연구는 독점 및 복점시장에서 판매자가 상품에 대한 품질정보를 독점하여 구매자가 알 수 없는 상황에서의 정보공개에 대한 결정을 경제학실험으로 살펴보았다. 본 실험에서 판매자는 상품 정보에 대한 정직한 혹은 부정직한 cheap-talk 메세지를 소비자에게 보냄으로써 품질에 대한 정보공개 여부를 결정한다. 실험 결과, 낮은 품질의 상품 판매자가 품질정보에 대한 기만 없이 정직하게 정보를 공개하는 경향이 존재하며, 판매자가 낮은 품질정보를 기만 없이 제공할 때, 이는 복점시장에서 상품차별화로 귀결되어 소비자가 높은 비율로 상품을 구매하는 결과로 이어졌다. 한편, 이러한 낮은 품질 정보의 제공이 판매자 이익에 부정적인 영향을 주는지는 분명하지 않았다: 대체로 부정적인 영향은 통계적으로 유의미하지 않았고, 어떤 시장조건들 하에서는 오히려 긍정적인 영향을 보였다. 낮은 품질정보의 공개는 상품 구매율을 향상시킴으로써 독점시장에서 긍정적인 후생 효 과를 가져온 반면, 복점시장 하에서는 비효율적인 낮은 품질 상품의 구매율을 높임으로써 전체 후생에 미약하거나 부정적인 영향을 보였다. We provide an experimental analysis of the setting where a seller, either a monopolist or a duopolist, sells a product with quality that is unobservable to buyers. The seller can send either an honest or dishonest cheap-talk message to buyers about the product quality. We show that low-quality sellers have a positive propensity to communicate their low-quality to buyers. Communicating low-quality results in buyers’ higher-propensity to purchase the product and introduces product differentiation in a duopoly. We do not find strong evidence that communicating low-quality information negatively affects sellers’ profit: the effect is often insignificant, and in some treatments it becomes significantly positive. Finally, revealing negative information has a strong positive welfare effect in a monopoly, where it raises the likelihood of product purchase; but a weak or negative effect in a duopoly, where it boosts the likelihood of purchasing a socially inefficient low-quality product.