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- 저자 : Harish Garg (검색결과 3 건)
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Harish Garg,Nikunj Aggarwal,Alka Tripathi 원광대학교 기초자연과학연구소 2017 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.13 No.6
The theme of this work is to investigate a new generalized parametric directed divergence measure for intuitionistic fuzzy sets. For it, the entire paper is divided into two folds. Firstly, a new measure has been presented by incorporating the idea of convex linear combinations of the degree of their membership functions. Some desirable properties of the proposed measure have been also investigated. Secondly, divergence measure based method for solving the decision making problem has been presented. A ranking of the different attributes is based on the proposed generalized divergence measure and the sensitivity analysis on the ranking of the system has been done based on the decision-making parameters. An illustrative examples have been studied to show that the proposed function is more reasonable in the decision-making process than other existing functions.
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An Aggressive Large Epithelioid Hemangioendothelioma of the Anterior Mediastinum in a Young Woman
Roman Dutta,Harish Pal,Garima Garg,Sambit Mohanty 대한흉부외과학회 2018 Journal of Chest Surgery (J Chest Surg) Vol.51 No.6
Hemangioendothelioma is a rare vascular tumor with involvement of the liver, brain, long bones, and lung. Among the 6 histological subtypes, epithelioid hemangioendothelioma (EHE) is the most aggressive. Its occurrence in the mediastinum is quite rare, and very few cases have been documented. The reported cases in the literature have described difficulties in the preoperative diagnosis due to the unusual histological appearance of the tumor. Immunohistochemistry remains the mainstay for a definitive diagnosis. Due to its low incidence, there is no standard treatment for mediastinal EHE, but curative resection is the preferred treatment option where possible, with chemotherapy used as an adjuvant treatment or in cases of widespread inoperable disease. The present case study describes an aggressive EHE occurring in an 18-year-old woman in the anterior mediastinum.
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Nonstationary-Epileptic-Spike Detection Algorithm in EEG Signal using SNEO
Amit Kumar Kohli,Harish Kumar Garg 대한의용생체공학회 2013 Biomedical Engineering Letters (BMEL) Vol.3 No.2
Purpose This correspondence presents the evaluation of nonstationary epileptic spike (ES) detection algorithm in the electroencephalogram (EEG) signal using the smoothed nonlinear energy operator (SNEO) based on the different time-domain window functions. However, the incorporation of adaptive threshold determination procedure enhances the performance of proposed ES detector. Methods The detection procedure exploits the fact that the presence of instantaneous ES corresponds to the high instantaneous energy content at the high frequencies. In addition to the stochastic amplitude, sign and the location of appearance of triangular spikes in the synthetic EEG signal,its base-width is also considered to be variable for the nonstationary analysis. The five pairs of EEG signals,obtained from electrodes placed on the left and right frontal cortex of male adult WAG/Rij rats, are used for the testing of proposed adaptive scheme in the real-time environment,which is a genetic animal model of human epilepsy. Results The simulation results are presented to demonstrate that the choice of window function plays a significant role in the efficient detection of ESs. The computational complexity is found to be in trade-off relationship with the detection accuracy of algorithm. Conclusions It may be inferred that the real-time EEG signals (rat data) can be processed and analyzed using the proposed adaptive scheme for the ES detection, which supersedes the conventional techniques.
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