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Reversible data hiding, in which the stego-media can be reversed to the original cover media exactly, has attracted increasing interests from the data hiding community. Recently, reversible data hiding (RDH) in encrypted images has gained attention form researchers, since it losslessly recovers original image from stego image after extraction of embedded(More)
The Purpose of current study is that Osteoporosis is a systemic disorder characterized by low bone mass leading to fractures reported commonly in females after menopause. The investigations for osteoporosis most commonly used DEXA are very costly and not easily available. Few studies have proposed the use of orthopantomogram as a diagnostic marker for(More)
Pangong is a brackish water lake having environmental conditions that are hostile to supporting life. This is the first report unveiling the microbial diversity of sediment from Pangong Lake, Ladakh, India, using a high-throughput metagenomic approach. Metagenomic data analysis revealed a community structure of microbes in which functional genetic diversity(More)
INTRODUCTION Tooth morphometry is resistant to postmortem destruction and can be used as an adjunct in skeletal sex and age determination. Therefore, an attempt was made to compare mandibular canine index (MCI) and Pont's index for their level of accuracy in gender determination for a Puducherry population. AIMS AND OBJECTIVES To evaluate crown size and(More)
We report the soil microbial diversity and functional aspects related to degradation of recalcitrant compounds, determined using a metagenomic approach, in a landfill lysimeter prepared with soil from Ghazipur landfill site, New Delhi, India. Metagenomic analysis revealed the presence and functional diversity of complex microbial communities responsible for(More)
In this paper, comparison of classic adaptive-filtering algorithms, such as LMS and RLS of Volterra filter, consist of adapting the coefficients of linear filters in real time. These algorithms have applications in a number of situations where the signals measured in the environment can be well modeled as Gaussian noises applied to linear systems, and their(More)
However, there exist some flaws in classical K-means clustering algorithm. First, the algorithm is sensitive in selecting initial centroids and can be easily trapped at a local minimum with regards to the measurement (the sum of squared errors). Secondly, the KM problem in terms of finding a global minimal sum of the squared errors is NP-hard even when the(More)
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