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M. Preethi,C. Velayutham,S. Arumugaperumal International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.3
Hyperspectral imaging technology is one of the most efficient and fast-growing technologies in recent years. Hyperspectral image (HSI) comprises contiguous spectral bands for every pixel that is used to detect the object with significant accuracy and details. HSI contains high dimensionality of spectral information which is not easy to classify every pixel. To confront the problem, we propose a novel RGB channel Assimilation for classification methods. The color features are extracted by using chromaticity computation. Additionally, this work discusses the classification of hyperspectral image based on Domain Transform Interpolated Convolution Filter (DTICF) and 3D-CNN with Bi-directional-Long Short Term Memory (Bi-LSTM). There are three steps for the proposed techniques: First, HSI data is converted to RGB images with spatial features. Before using the DTICF, the RGB images of HSI and patch of the input image from raw HSI are integrated. Afterward, the pair features of spectral and spatial are excerpted using DTICF from integrated HSI. Those obtained spatial and spectral features are finally given into the designed 3D-CNN with Bi-LSTM framework. In the second step, the excerpted color features are classified by 2D-CNN. The probabilistic classification map of 3D-CNN-Bi-LSTM, and 2D-CNN are fused. In the last step, additionally, Markov Random Field (MRF) is utilized for improving the fused probabilistic classification map efficiently. Based on the experimental results, two different hyperspectral images prove that novel RGB channel assimilation of DTICF-3D-CNN-Bi-LSTM approach is more important and provides good classification results compared to other classification approaches.
An Intelligent Approach in Monitoring and Controlling of Bunker Coal Level in Thermal Power Plant
M.Surekha,R.Preethi,S.Kalpanadevi,N. Suthanthira Vanitha 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.4
Currently coal fired power plant requires bunker or stock piles in order to place the coal for storage purpose and to use it effectively when demand arises. Real time sensors are used to sense level of the coal and to pass data to computational systems for processing hence further actions such as refilling and distributing of coal can be automated. Further the control action in level sensing can be enhanced by using fuzzy logic controller which is an intelligent system. Thus the proposed system of coal unit provides the optimum control with increased efficiency. The simulation results are achieved by using LabVIEW.
Gastric Adenocarcinoma with Prostatic Metastasis
Roshni, S.,Anoop, T.M.,Preethi, T.R.,Shubanshu, G.,Lijeesh, A.L. The Korean Gastric Cancer Association 2014 Journal of gastric cancer Vol.14 No.2
Metastasis of gastric adenocarcinoma to the prostate gland is extremely rare. Herein, we report a case of gastric adenocarcinoma in a 56-year-old man with prostatic metastasis diagnosed through the analysis of biopsy specimens from representative lesions in the stomach and prostate gland. Immunohistochemistry of the prostatic tissue showed positive staining for cytokeratin 7 and negative staining for prostate-specific antigen (PSA), whereas the serum PSA level was normal, confirming the diagnosis of prostatic metastasis from carcinoma of the stomach.
K. Jeyasubramanian,G.S. Hikku,A.V.M. Preethi,V.S. Benitha,N. Selvakumar 한국공업화학회 2016 Journal of Industrial and Engineering Chemistry Vol.37 No.-
Superhydrophobicity on the cotton fabric was accomplished by coating a mixture of polyvinyl chloride,copper stearate and Fe2O3/Cr2O3 nanoparticles. Firm attachment of copper stearate and the nanoparticles on the surface of cotton was achieved by employing polyvinyl chloride solution as the binder. The non-wettable nature of the surface modified cotton fabrics were evaluated through WCAmeasurement, which exhibited superhydrophobic nature for nano Fe2O3 (147.58) and Cr2O3 (151.18)impregnated cotton. Moreover, the surface roughness contributing towards the enhancement of WCA oncotton was indirectly evaluated by coating a thin film over a glass surface utilizing the same additiveswas reported through AFM.