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Study of Effect on Performance of DE/BBO on Changing Parametric Values
Ekta,Mandeep Kaur 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.5
DE\BBO is the hybridization of Differential Evolution optimization and Biogeography Based Optimization. DE is considered to have good exploration ability and BBO is considered to have good exploitation ability, to achieve goodness of both techniques, these techniques have been combined. Hybridization of Differential evaluation and biogeography based optimization dominates the performance of biogeography based optimization. The influencing factors of performance of DE are scaling factor and cross-over rate which are used to track proper optimization. In this paper, it has been shown how DE/BBO outperforms BBO. The change in the performance of DE/BBO due to variation in some pre-considered variables has also been highlighted. It has been observed that DE/BBO performs best when scaling factor is 0.11 and cross over rate is 0.2.
Diversion of Constant Crossover Rate DE\BBO to Variable Crossover Rate DE\BBO\L
Ekta,Mandeep Kaur 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.1
DE\BBO is the combination of differential evolution and biogeography based optimization algorithm to get a better optimization algorithm in terms of convergence speed. In DE\BBO, constant crossover rate has been used which sometimes affect the performance of the hybrid algorithm leading to increase in convergence speed. To cope up with this problem, variable crossover rate has been introduced in the hybrid algorithm helping in removing the problem of constant crossover rate. Modified algorithm has been named as DE\BBO\L in which local search mutation and variable crossover rate are used. Testing of BBO, DE\BBO\rand\1 and DE\BBO\L has been performed on different test functions. The results reveal that DE\BBO\L with variable crossover rate is better than DE\BBO with constant crossover rate.
Ekta Chauhan 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.2
At present, greatest outdoor video-surveillance, optical remote sensing systems and driver-assistance have been designed to work under decent visibility weather conditions. Less visibility often happens weather of hazy or foggy conditions and can strongly influence accuracy or even general functionality of such vision systems. Fog reduces the visibility of a scene and thus the performance of numerous algorithms of computer vision which use feature knowledge. Fog formation is the function of the depth. Estimation of depth knowledge is under constraint problem if single image is presented. Hence, fog removal need assumptions or prior information. In this paper, present a novel algorithm for fog or haze removal purpose with combination of edge enhancement method, color enhancement method, adjustable empirical function and also Wiener filter for efficient outcomes.
Ekta Chauhan,Unmukh Datta 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.8
Electronic commerce, commonly known as eCommerce is trade in products using the internet. Security at the e-commerce becomes more and more important. Electronic transaction security is a challenging task because of the insecure communication channel. In this paper, we proposed a new algorithm to make an e commerce transaction more secure. In this work we are using AES to encrypt data and this data is embedded to image edges to perform Stenography in this paper target on compress the time of encryption and decryption adopting parallel processing on which AES will be applied freely. In the results show the comparison between our work and previous work and we found that parallel processing and multi threading on the AES algorithm our results are quite improved, our proposed algorithm is taking much less time in encrypt and embedding or decrypt and extraction.
Vascular dysfunction in patients with type 2 diabetes mellitus
Ekta Khandelwal,Mahaveer Jain,Sumeet Tripathi 대한임상신경생리학회 2023 Annals of Clinical Neurophysiology Vol.25 No.1
Background: Type 2 diabetic mellitus (T2DM) is an emerging global pandemic which is associated with lots of co-morbidities and reported vascular dysfunctions. T2DM associated vascular dysfunctions leads to vasculopathy in the form of altered peripheral vascular dynamics. Cold stress test (CST) is a reliable sympathetic reactivity test used for assessing vascular dysfunctions. In this study we are trying to quantify vascular dysfunctions in T2DM patients non invasively by various parameters of photoplethysmography (PPG) of cold stress test. Methods: Case control study had done in referral health center AIIMS, Raipur. Parameters are recorded by finger-PPG before, during and after CST (1 min) in 2 groups, control (n = 20 healthy volunteers) and case (n = 20 diagnosed T2DM patients). Results: Due to cold stress, PPG parameter peak amplitude was significantly decreased in both healthy and T2DM groups (p <0.001 and p <0.001, respectively). However, recovery trend of amplitude was significantly slow in T2DM compared to healthy subjects. Another PPG parameter peak to peak interval was significantly higher in healthy group compared to T2DM patients. Conclusions: This study showed that T2DM patients has significant deranged pulse volume parameters like amplitude and peak to peak interval can be used to objectively quantify the vasculopathy in T2DM patients by using sympathetic reactivity to cold stress.
BPAODV : Black Hole Prevention Using Trust Adhoc on Demand Distance Vector Routing Protocol
Ekta Gupta,Akhilesh Tiwari 보안공학연구지원센터 2014 International Journal of Future Generation Communi Vol.7 No.6
Now-a-days, wireless networks are playing vital role for facilitating communication between different entities for different purposes. In case of wireless networks, security aspect has now becomes a very major concern and most of the current researches are focusing in the same direction. This paper addresses the important problems relating to Black hole attack in adhoc network. During the research, a new and robust routing mechanism has been developed. Firstly, on the basis of Trust value and Credential value detection and prevention of Black hole attack has been performed. For assessing the performance of developed routing mechanism, experimentation has been done using NS2 simulator. Comparisons have been performed with AODV, Black hole AODV and results are as per the expectations.
Controlled $K$-frames in Hilbert C*-modules
Ekta Rajput,Nabin Kumar Sahu,Vishnu Narayan Mishra 강원경기수학회 2022 한국수학논문집 Vol.30 No.1
Controlled frames have been the subject of interest because of their ability to improve the numerical efficiency of iterative algorithms for inverting the frame operator. In this paper, we introduce the notion of controlled $K$-frame or controlled operator frame in Hilbert $C^{*}$-modules. We establish the equivalent condition for controlled $K$-frame. We investigate some operator theoretic characterizations of controlled $K$-frames and controlled Bessel sequences. Moreover, we establish the relationship between the $K$-frames and controlled $K$-frames. We also investigate the invariance of a controlled $K$-frame under a suitable map $T$. At the end, we prove a perturbation result for controlled $K$-frame.
Combination of Local, Global and k-mean using Wavelet Transform for Content Base Image Retrieval
Ekta Gupta,Rajendra Singh Kushwah 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.6
In today’s time, the requirement of content based image retrieval technique is more and more because of diverse areas such as Data Mining, Remote Sensing and Management of Earth Resources, , Crime Prevention, Weather forecasting, E-commerce, Medical Imaging. The proposed paper presents the content based image retrieval, using features like color and texture, called WBCHIR (Wavelet Based Color Histogram Image Retrieval).The shape and shade features are extracted in the course of wavelet transformation and color histogram and the arrangement of these features is vigorous to scaling and conversion of objects in an image. It is the first time to present segmentation and grid, feature extraction, K-means module and k-nearest neighbor clustering algorithms and bring in the neighborhood module to build the CBIR system. It is the hybrid method of global and local features with k-means clustering algorithm.