Walchand Institute of Technology
Walchand Institute of Technology
Deshmukh B.,Walchand Institute of Technology |
Pardeshi S.,College of Engineering, Pune
Smart Innovation, Systems and Technologies | Year: 2017
Miniaturization has inherited the necessity of micro-mechanism. Micro-motion devices are expected to deliver high positioning accuracy and potentially have wide applications in the industry such as development of Micro factories. A flexure based joint-less pantograph is designed as a mechanical amplifier to achieve a geometric amplification of input displacement for a linear positioning system. This arrangement is useful for achieving motion amplification for a precision actuator Piezo actuator. Design and manufacturing of such system is a challenging task and the important aspect of DFMA is considered. Guidelines are suggested for researchers who intend to develop similar setups. Macro scale Wire Electric Discharge Machine (WEDM) is used for manufacturing micro-mechanism. Concept ‘Do not fight with gravity’ is implemented in setup development. All constraints applied in simulation, are applied on the mechanism to replicate directional motion in the setup developed. The performance of mechanism was observed under a vision based system. Setup developed has been successfully used for the performance evaluation of compliant pantograph. © Springer Nature Singapore Pte Ltd. 2017.
Indi T.S.,Walchand Institute of Technology
2013 IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology, ICE-CCN 2013 | Year: 2013
Traditionally biometric features like fingerprint and iris pattern are used for unique identification of a person. Recent evolution in biometric is use of ear for identification. A system is presented here for person identification using ear features and or thumbprint. In our system, minutiae points extracted from scanned thumb print of a person and digitally captured ear image is processed to extract ear features (Helix rim, Lobule, Triangularfossa, Concha and Tragus). These extracted features are stored into database for matching process. The minutiae points are used to uniquely identify a person and in matching process projection lines used to quantify ear features. Matching process gives matched profile as a result of system in graphical format as well as textual format with tolerance limit of ± 15%. The matching algorithm will be using this text data to find target person profile. © 2013 IEEE.
Abel M.S.,Gulbarga University |
Tawade J.V.,Walchand Institute of Technology |
Shinde J.N.,Swamy Vivekananda Institute of Technology andra Pradesh
Advances in Mathematical Physics | Year: 2012
An analysis is performed to investigate the effect of MHD and thermal radiation on the two-dimensional steady flow of an incompressible, upper-convected Maxwells (UCM) fluid in presence of external magnetic field. The governing system of partial differential equations are transformed into a system of coupled nonlinear ordinary differential equations and is solved numerically by efficient shooting technique. Velocity and temperature fields have been computed and shown graphically for various values of physical parameters. For a Maxwell fluid, a thinning of the boundary layer and a drop in wall skin friction coefficient is predicted to occur for the higher elastic number which agrees with the results of Hayat et al. 2007 and Sadeghy et al. 2006. The objective of the present work is to investigate the effect of elastic parameter β, magnetic parameter Mn, Eckert number Ec, Radiation parameter N, and Prandtl number Pr on flow and heat transfer charecteristics. © 2012 M. Subhas Abel et al.
Kashid S.S.,Walchand Institute of Technology |
Maity R.,Indian Institute of Technology Kharagpur
Journal of Hydrology | Year: 2012
Prediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different 'homogeneous monsoon regions'. © 2012 Elsevier B.V.
Maity R.,Indian Institute of Technology Kharagpur |
Kashid S.S.,Walchand Institute of Technology
Water Resources Research | Year: 2011
Basin-scale streamflow is influenced by numerous local and global climate inputs. In this paper, genetic programming (GP) is combined with "importance analysis" to identify the important global climate inputs and local meteorological variables needed for prediction of weekly streamflow at the basin scale. The analysis is carried out for the Mahanadi River in India using global climate inputs, namely, the El Nio-Southern Oscillation (ENSO) index and equatorial Indian Ocean Oscillation (EQUINOO) index; local meteorological inputs, including outgoing longwave radiation (OLR), total precipitable water (TPW), temperature anomaly (TA), and pressure anomaly (PA); and streamflow information from previous time steps. The rainfall information over the basin is intentionally not utilized so that the procedure may be applicable to basins with little or no rain gauge information and to achieve a longer prediction lead time. The Birnbaum importance measure is used to assess the importance of each input. Results of this study show that the relative importance of individual input variables is influenced by time lags. It is observed that among various local meteorological inputs, OLR and PA are more important than TA and TPW. Among large-scale circulation indices, ENSO index is important for previous 5th to 7th week, whereas EQUINOO index is important for previous 3rd to 6th week. On the basis of their importance measures, 15 indices were selected from the initial group of 30 indices. The GP-derived streamflow forecasting models could predict weekly streamflow with good accuracy (correlation coefficient r = 0.821) for such a complex system.
Dol S.M.,Walchand Institute of Technology
Proceedings - IEEE 7th International Conference on Technology for Education, T4E 2015 | Year: 2015
Fe.g. is an animated flowchart with example which can be used for algorithm based subjects. In Fe.g., first the working of algorithm is demonstrated with the help of animated flowchart and then the step by step working of algorithm with the help of example. So this activity is considered for the subject System Programming of Third Year Computer Science and engineering. One group pre-test pots-test model is considered to test the effectiveness of this activity. The results are also explained in this paper. © 2015 IEEE.
Aher S.B.,Walchand Institute of Technology |
Lobo L.M.R.J.,Walchand Institute of Technology
Knowledge-Based Systems | Year: 2013
Data mining is the process which is used to analyze the large database to find the useful pattern. Data mining can be used to learn about student's behavior from data collected using the course management system such as Moodle (Modular Object-Oriented Developmental Learning Environment). Here in this paper we show how data mining techniques such as clustering and association rule algorithm is useful in Course Recommendation System which recommends the course to the student based on choice of other students for particular set of courses collected from Moodle. As a result of Course Recommendation System, we can recommend to new student who has recently enrolled for some course e.g. Operating System, the new course to be opted e.g. Distributed System. Our approach uses combination of clustering technique - Simple K-means and association rule algorithm - Apriori and finds the result. These results were compared with the results of open source data mining tool-Weka. The result obtained using combined approach matches with real world interdependencies among the courses. Other combinations of clustering and association rule algorithms are also discussed here to select the best combination. This Course Recommendation System could help in building intelligent recommender system. This approach of recommending courses to new students can be immensely be useful in "MOOC (Massively Open Online Courses)". © 2013 Elsevier B.V. All rights reserved.
Thalange A.,Walchand Institute of Technology |
Dixit S.K.,Walchand Institute of Technology
Procedia Computer Science | Year: 2016
Bridging communication gap between the deaf and dumb people with the common man is a big challenge. A sign language recognition system could provide an opportunity for the deaf and dumb to communicate with non-signing people without the need for an interpreter. Research in the area of Sign language recognition has become very significant due to various challenges faced while capturing of the sign. Not a single efficient methodology or algorithm is developed which overcomes all the difficulties and recognizes all the signs with cent percent accuracy. This paper proposes two new feature extraction techniques of Combined Orientation Histogram and Statistical (COHST) Features and Wavelet Features for recognition of static signs of numbers 0 to 9, of American Sign Language (ASL). The system performance is measured by extracting four different features of Orientation Histogram, Statistical Measures, COHST Features and Wavelet Features for training and recognition of ASL numbers individually using neural network. It is observed that COHST method forms a strong feature than the individual Orientation Histogram and Statistical Features giving higher average recognition rate. Of all the System designed for static ASL numbers recognition, Wavelet features based system gives the best performance with maximum average recognition rate of 98.17%. © 2016 The Authors. Published by Elsevier B.V.
Palle A.,Walchand Institute of Technology |
Kulkarni R.B.,Walchand Institute of Technology
ACM International Conference Proceeding Series | Year: 2016
Presently retrieving and managing the distributed large images has turned into an important research Topic. Content based image retrieval is the process to retrieve relevant image from database using visual parameters. In this work, we are using CBIR approach to the medical image management application. The purpose of this research work is to find similar mri brain images using content based image retrieval on hadoop platform. Application of this work is to predict normal and abnormal mri brain image using decision making algorithm. Tree based classification algorithm can be used for decision making. © 2016 ACM.
Awatade M.H.,Walchand Institute of Technology
AIP Conference Proceedings | Year: 2011
A model of how speech amplitude spectra are affected by additive noise is studied. Acoustic features are extracted based on the noise robust parts of speech spectra without losing discriminative information. An existing two non-linear processing methods, harmonic demodulation and spectral peak-to-valley ratio locking, are designed to minimize mismatch between clean and noisy speech features. Previously studied methods, including peak isolation , do not require noise estimation and are effective in dealing with both stationary and non-stationary noise. © 2011 American Institute of Physics.