http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Dilip Kumar 한양대학교 경제연구소 2019 JOURNAL OF ECONOMIC RESEARCH Vol.24 No.1
The paper examines the evolution of volatility transmission from thecrude oil market to agricultural commodities during the period from1983 to 2015 based on the unbiased version of Rogers and Satchell(1991) volatility estimator, hereafter referred as the AddRS estimator. Our findings indicate that the dynamics of volatility transmission fromcrude oil to the given agricultural commodity is structurally unstableand exhibits structural breaks. We find that the structural breaks involatility series play a tiny role in explaining the structural breaks inthe measured volatility transmission from crude oil to the givenagricultural commodities. However, we find that the conditionalheteroskedasticity plays a significant role in explaining the structuralbreaks in measured volatility transmission from crude oil toagricultural commodity. The economic significance analysis indicatesthat the information from the crude oil market can be used to earnsubstantial economic gain in returns by investing in agriculturalcommodities.
Dilipkumar Munirathinam,Dhivya Mohanaj,Mohammed Beganam 대한치과보철학회 2012 The Journal of Advanced Prosthodontics Vol.4 No.3
PURPOSE. To evaluate the shear bond strength of resin luting agent to dentin surfaces cleansed with different agents like pumice, ultrasonic scaler with chlorhexidine gluconate, EDTA and the influence of these cleansing methods on wetting properties of the dentin by Axisymmetric drop Shape Analysis - Contact Diameter technique (ADSA-CD). MATERIALS AND METHODS. Forty coronal portions of human third molar were prepared until dentin was exposed. Specimens were divided into two groups: Group A and Group B. Provisional restorations made with autopolymerizing resin were luted to dentin surface with zinc oxide eugenol in Group A and with freegenol cement in Group B. All specimens were stored in distilled water at room temperature for 24 hrs and provisional cements were mechanically removed with explorer and rinsed with water and cleansed using various methods (Control-air-water spray, Pumice prophylaxis, Ultrasonic scaler with 0.2% Chlorhexidine gluconate, 17% EDTA). Contact angle measurements were performed to assess wettability of various cleansing agents using the ADSA-CD technique. Bond strength of a resin luting agent bonded to the cleansed surface was assessed using Instron testing machine and the mode of failure noted. SEM was done to assess the surface cleanliness. Data were statistically analyzed by one-way analysis of variance with Tukey HSD tests (alpha=.05). RESULTS. Specimens treated with EDTA showed the highest shear bond strength and the lowest contact angle for both groups. SEM showed that EDTA was the most effective solution to remove the smear layer. Also, mode of failure seen was predominantly cohesive for both EDTA and pumice prophylaxis. CONCLUSION. EDTA was the most effective dentin cleansing agent among the compared groups.
Masilamany Dilipkumar,Ali Ahadiyat,PeterMašán,Tse Seng Chuah 한국응용곤충학회 2015 Journal of Asia-Pacific Entomology Vol.18 No.2
There is a great deal of diversity among phoretic association particularly in mesostigmatic mites that exploited insect host to complete their dispersal strategy. Similarly, the red palm weevil, Rhynchophorus ferrugineus, also has been used as a carrier by the phoretic mites. In this study, we found Centrouropoda almerodai (Uropodidae), Macrocheles mammifer, Macrocheles cf. oigru (Macrochelidae), Uroobovella assamomarginata and Uroobovella javae (Dinychidae) as the phoreticmites associated with the Malaysian red palm weevils. Male weevils had significantly greater number of mites per host as compared to the female weevils. Present study revealed that the red palm weevils were infested with very large numbers of phoretic mites which occurmainly under the elytra. Our results combined with those in the literatures suggest the potential role of phoresy in the evolution of parasitism.
Influence of an upstream transonic axial compressor stage on the performance of inter-stage duct
Lakshya Kumar,Dilipkumar B. Alone,A. M. Pradeep 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.5
In this investigation, an inter-stage duct (ISD) design is carried out for three lengths based on the guidelines available in the open literature. The performance of the design is analyzed considering a stand-alone ISD with uniform inlet velocity and the flow coming from an upstream transonic compressor stage (TCS). The computational analysis is carried out for a 20° sector geometry. Three turbulence models, namely, SST, k-ε, and Reynolds stress, are compared for loss predictions. The flow behavior of the individual ducts is observed to be free from separation and is uniform at the exit. However, the duct performance is severely affected due to the presence of the upstream TCS. This investigation sheds light on the importance of considering upstream conditions for ISD design.
An Explainable Deep Learning Approach for Oral Cancer Detection
Babu P. Ashok,Rai Anjani Kumar,Ramesh Janjhyam Venkata Naga,Nithyasri A.,Sangeetha S.,Kshirsagar Pravin R.,Rajendran A.,Rajaram A.,Dilipkumar S. 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.3
With a high death rate, oral cancer is a major worldwide health problem, particularly in low- and middle-income nations. Timely detection and diagnosis are crucial for efective prevention and treatment. To address this challenge, there is a growing need for automated detection systems to aid healthcare professionals. Regular dental examinations play a vital role in early detection. Transfer learning, which leverages knowledge from related domains, can enhance performance in target categories. This study presents a unique approach to the early detection and diagnosis of oral cancer that makes use of the exceptional sensory capabilities of the mouth. Deep neural networks, particularly those based on automated systems, are employed to identify intricate patterns associated with the disease. By combining various transfer learning approaches and conducting comparative analyses, an optimal learning rate is achieved. The categorization analysis of the reference results is presented in detail. Our preliminary fndings demonstrate that deep learning efectively addresses this challenging problem, with the Inception-V3 algorithm exhibiting superior accuracy compared to other algorithms.