Time filter

Source Type

Mumbai, India

Datta Meghe College of Engineering is a private engineering college located in Airoli, Navi Mumbai, Maharashtra, India. The college is affiliated to the University of Mumbai and approved by the Directorate of Technical Education , Maharashtra State and All India Council of Technical Education , New Delhi. It is the best college in Navi Mumbai as per the survey conducted by Indian Council of Technical Education in 2007. Wikipedia.

Chore H.S.,Datta Meghe College of Engineering | Ingle R.K.,Visvesvaraya National Institute of Technology | Sawant V.A.,Indian Institute of Technology Roorkee
Structural Engineering and Mechanics | Year: 2014

The study deals with physical modeling of space frame- pile foundation and soil system using finite element models. The superstructure frame is analyzed using complete three -dimensional finite element method where the component of the frame such as slab, beam and columns are descretized using 20 node isoparametric continuum elements. Initially, the frame is analyzed assuming the fixed column bases. Later the pile foundation is worked out separately wherein the simplified models of finite elements such as beam and plate element are used for pile and pile cap, respectively. The non-linear behaviour of soil mass is incorporated by idealizing the soil as non-linear springs using p-y curve along the lines similar to that by Georgiadis et al. (1992). For analysis of pile foundation, the non-linearity of soil via p-y curve approach is incorporated using the incremental approach. The interaction analysis is conducted for the parametric study. The non-linearity of soil is further incorporated using iterative approach, i.e., secant modulus approach, in the interaction analysis. The effect the various parameters of the pile foundation such as spacing in a group and configuration of the pile group is evaluated on the response of superstructure owing to non-linearity of the soil. The response included the displacement at the top of the frame and bending moment in columns. The non-linearity of soil increases the top displacement in the range of 7.8 %- 16.7%. However, its effect is found very marginal on the absolute maximum moment in columns. The hogging moment decreases by 0.005% while sagging moment increases by 0.02%. Copyright © 2014 Techno-Press, Ltd.

Sawarkar S.,Datta Meghe College of Engineering
ICWET 2010 - International Conference and Workshop on Emerging Trends in Technology 2010, Conference Proceedings | Year: 2010

The proposed method detects the exact location of masses and circumscribed masses in mammograms based on RBFNN (Redial Basis Function Neural Network) with accuracy of 62% and 50% respectively for mammograms containing masses. The recognition rate for the normal one reaches 94.89% in MIAS (Mammography Image Analysis Society) database. Also the results are independent of preprocessing. This procedure is implemented by performing sub-image windowing analysis. The evaluation of the proposed mass and circumscribed mass detection was carried out in the MIAS database, giving reliable detection. Copyright 2010 ACM.

Nirmal A.J.,Datta Meghe College of Engineering | Gaikwad V.B.,University of Mumbai
International Conference and Workshop on Emerging Trends in Technology 2011, ICWET 2011 - Conference Proceedings | Year: 2011

Content Based Image Retrieval System retrieves images using color, texture and shape properties of the image. Different methods which are implemented in this paper are Discrete wavelet transform (DWT), Gabor wavelet transform (GWT), Color histogram (CH), color autocorrelogram (CA). Integration of color and texture features is done using different methods and their comparison is done using precision and recall as performance measures.. DWT (D) method is implemented using the combination of statistical mean and standard deviation features and perceptual feature directionality. The best results are obtained with GWT (A) + CH method as compared to all other ten methods as phase information from the Gabor transformed coefficients is taken into consideration. Copyright © 2011 ACM.

Londhe S.,Vishwakarma Institute of Information Technology | Charhate S.,Datta Meghe College of Engineering
Hydrological Sciences Journal | Year: 2010

Accurate forecasting of streamflow is essential for the efficient operation of water resources systems. The streamflow process is complex and highly nonlinear. Therefore, researchers try to devise alterative techniques to forecast streamflow with relative ease and reasonable accuracy, although traditional deterministic and conceptual models are available. The present work uses three data-driven techniques, namely artificial neural networks (ANN), genetic programming (GP) and model trees (MT) to forecast river flow one day in advance at two stations in the Narmada catchment of India, and the results are compared. All the models performed reasonably well as far as accuracy of prediction is concerned. It was found that the ANN and MT techniques performed almost equally well, but GP performed better than both these techniques, although only marginally in terms of prediction accuracy in normal and extreme events. © 2010 IAHS Press.

Ashraf K.N.,Ramrao Adik Institute of Technology | Amarsinh V.,Ramrao Adik Institute of Technology | Satish D.,Datta Meghe College of Engineering
Proceedings of the 2013 3rd IEEE International Advance Computing Conference, IACC 2013 | Year: 2013

Mobile devices often change their location which triggers the handover from one access router to another. Mobility management provides a way to retain the ongoing session of the mobile node. It is crucial to provide efficient handoff mechanism support for mobile devices. Mobile IPv6 (MIPv6) and its extensions have been proposed for this purpose. Fast Mobile IPv6 (FMIPv6) and Hierarchical Mobile IPv6 (HMIPv6) have been developed as host-based mobility management protocols whereas Proxy Mobile IPv6 (PMIPv6) and Fast Proxy Mobile IPv6 (FPMIPv6) have been proposed as network-based mobility management protocols. In this paper, survey and detailed signaling of each protocol is presented followed by analysis of these protocols based on handover latency and signaling cost. Finally numerical results are presented and commented. © 2013 IEEE.

Discover hidden collaborations