Browsing by Author "Goyal, R."
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Item Brain Tumor Segmentation Using Deep Neural Networks: A Comparative Study(Springer Science and Business Media Deutschland GmbH, 2023) Gautam, P.; Goyal, R.; Upadhyay, U.; Naik, D.The research presents brain tumor segmentation from medical images like MRI scans using various deep neural networks. Tumors can arise anywhere in the brain and can be of different contrast, form, and magnitude. The proposed networks are designed for glioblastoma (high-grade and low-grade) tumors in MRI scans. The study explores various architectures designed for medical data image segmentation. The two-path CNN architecture implemented in the study exploits local and more global contextual features. The two-path CNN architecture was extended using three cascading architectures (Input, Local, and MF). Also, the researchers used the popular semantic segmentation architecture models, U-net, specially designed for medical image segmentation. Finally, the study compared the Cascaded and the U-net performance based on F1 score and Dice loss. It was concluded that the U-net architecture performed better than Cascading architecture and delivered a more precise boundary for the target tumor in an MRI scan. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Numerical simulation of progressive fracture propagation in petroleum reservoir rock strata using finite element modeling(2014) Goyal, R.; Singh, K.; Reddyy, D.V.Reservoir perforation allows for interfacing of the pay-zone and the production casing in the petroleum wellbore. Perforations are key interface for fluid movement in completion and they are extremely important for effective design and itis to beensured that well has appropriate number and size of perforation. For directing formation petroleu mfluid from subsurface zone, cased well must be perforated. Perforationis created by implementing controlled detonation of steel casing, cement casing and surrounding rock using specially design edand manufactured shaped charges. Perforating shockwaves and high impact pressureshattertherockto breakdown and propagate crack through it. Numerical model of acuboidal rock sample is createdto decide the preferred fracture plane. Under balance forces have also been taken in account to calculate Von-misesstress. Simulations are performed in order tostudy the behavior of compound stress during chargede to nation of rock and casing fracture. Crack propagation in different directions and principal planes has been found out. Usingthese results, location ofchargesoncasingcanbe defined to propagate fracture indesired locations. This report presents numerical analysis of fracture propagation during charged detonation using finite element methods (FEM).. 2014 CAFET-INNOVA TECHNICAL SOCIETY.Item Numerical simulation of progressive fracture propagation in petroleum reservoir rock strata using finite element modeling(CAFET INNOVA Technical Society cafetinnova@gmail.com 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2014) Goyal, R.; Singh, K.; Reddyy, D.V.Reservoir perforation allows for interfacing of the pay-zone and the production casing in the petroleum wellbore. Perforations are key interface for fluid movement in completion and they are extremely important for effective design and itis to beensured that well has appropriate number and size of perforation. For directing formation petroleu mfluid from subsurface zone, cased well must be perforated. Perforationis created by implementing controlled detonation of steel casing, cement casing and surrounding rock using specially design edand manufactured shaped charges. Perforating shockwaves and high impact pressureshattertherockto breakdown and propagate crack through it. Numerical model of acuboidal rock sample is createdto decide the preferred fracture plane. Under balance forces have also been taken in account to calculate Von-misesstress. Simulations are performed in order tostudy the behavior of compound stress during chargede to nation of rock and casing fracture. Crack propagation in different directions and principal planes has been found out. Usingthese results, location ofchargesoncasingcanbe defined to propagate fracture indesired locations. This report presents numerical analysis of fracture propagation during charged detonation using finite element methods (FEM).. © 2014 CAFET-INNOVA TECHNICAL SOCIETY.Item Preface(Springer Science and Business Media Deutschland GmbH, 2025) Kashyap, A.; Li, R.Y.M.; Goyal, R.; Deepak, M.D.; Mahesh, G.[No abstract available]Item Preface(Springer Science and Business Media Deutschland GmbH, 2025) Kashyap, A.; Li, R.Y.M.; Goyal, R.; Deepak, M.D.; Mahesh, G.[No abstract available]Item Preface(Springer Science and Business Media Deutschland GmbH, 2025) Kashyap, A.; Goyal, R.; Li, R.Y.M.; Mahesh, G.; Deepak, M.D.[No abstract available]Item Quarter circular breakwater: Prediction of transmission using multiple regression and artificial neural network(2014) Goyal, R.; Singh, K.; Hegde, A.V.The physical model study of coastal structures is a nonlinear process influenced by innumerable parameters. As a result of a lack of definite systems, intricacies, and high costs involved in the physical models, we need a simple mathematical tool to predict wave transmission through quarter circular breakwater (QBW). QBW is a state-of-theart breakwater essentially based on the exploitation of the concepts of semicircular breakwater. This paper discusses the use of soft computing tools such as MATLAB based multiple regression (MR) and artificial neural network (ANN) to predict the wave transmission coefficient of QBW. To assess the accuracy of the proposed model and its ability to forecast, correlation coefficient and mean squared error are availed. On comparing the results obtained from MR and ANN, it is concluded that ANN gives more accurate results and can be used as a powerful tool for the modeling of hydrodynamic breakwater transmission through QBW. It serves as a viable alternative to the conventional physical model to simulate the hydrodynamic transmission performance of QBW.Item Quarter circular breakwater: Prediction of transmission using multiple regression and artificial neural network(Marine Technology Society Inc. mtsdir@erols.com, 2014) Goyal, R.; Singh, K.; Hegde, A.V.The physical model study of coastal structures is a nonlinear process influenced by innumerable parameters. As a result of a lack of definite systems, intricacies, and high costs involved in the physical models, we need a simple mathematical tool to predict wave transmission through quarter circular breakwater (QBW). QBW is a state-of-theart breakwater essentially based on the exploitation of the concepts of semicircular breakwater. This paper discusses the use of soft computing tools such as MATLAB based multiple regression (MR) and artificial neural network (ANN) to predict the wave transmission coefficient of QBW. To assess the accuracy of the proposed model and its ability to forecast, correlation coefficient and mean squared error are availed. On comparing the results obtained from MR and ANN, it is concluded that ANN gives more accurate results and can be used as a powerful tool for the modeling of hydrodynamic breakwater transmission through QBW. It serves as a viable alternative to the conventional physical model to simulate the hydrodynamic transmission performance of QBW.