Literacy Level of Muslim Girls in Uttar Pradesh
This paper main aims to find out the literacy level of Muslim girls in Uttar Pradesh and it also aims to compare the literacy level of Muslim girls in Uttar Pradesh between two census i.e. 2001 and 2011. The study is based on the secondary sources of data which has been collected from the census of India 2001 and 2011. In this paper, Researcher’s focused on the status of Muslim girls’ literacy rate in Uttar Pradesh. It is found that more than half i.e., 53.95 per cent of the total population of the Muslims in India is illiterate with 17.48 per cent literate people just for the name sake only. If we talk about Uttar Pradesh then we found that 50.59 per cent Muslim girls are literate in 2011 (as per census 2011) in which 47.04 literate in rural areas and 56.44 literate in urban areas. This show better result from the census report 2001 in which 31.58 Muslim girls were literate in rural areas and 47.31 Muslim girls were literate in urban areas. The results have revealed that the literacy level of Muslim girls in Uttar Pradesh is not satisfactory and needs special attention.
Published by: Pooja Singh, Dr. Meena Bhandari
Author: Pooja Singh
Paper ID: V3I3-1502
Paper Status: published
Published: June 7, 2017
An Object Tracking Mechanism in Wireless Sensor Networks
The continuously widening variety of Wireless Sensor Networks (WSNs) applications requires node this is certainly precise which needs efficient and error free localization practices. Localization methods created in past times are totally centered on really good computation this is certainly numerical of network variables such as for example transmission range, propagation form, transmitted or received power, delivering or arrival time, connection information etc. These variables are susceptible towards ecological presence and circumstance of hurdles in environment. As wireless sensor companies tend to be ubiquitous in general, localization is a factor this is certainly essential be fixed. Localization of a node that is unknown be identified through a collection of research nodes. In this work, we provide a novel hybrid localization strategy, which determines the location this is certainly exact of an unknown node through the mixture of both range free and range based practices.
Published by: Pinki Rathee, Sanjeev Indora
Author: Pinki Rathee
Paper ID: V3I3-1465
Paper Status: published
Published: June 7, 2017
Voice Based Email for Blind People
Abstract - The advancement in computer based accessible systems has opened up many avenues for the visually impaired across a wide majority of the globe. Audio feedback based virtual environment like, the screen readers have helped blind people to access internet applications immensely. However, a large section of visually impaired people in different countries in particular, the Indian sub-continent could not benefit much from such systems. This was primarily due to the difference in the technology required for Indian languages compared to those corresponding to other popular languages of the world. In this paper, we describe the voicemail system architecture that can be used by a blind person to access e-mails easily and efficiently. The contribution made by this research has enabled the blind people to send and receive voice based e-mail messages in their native language with the help of a mobile device. Our proposed system GUI has been evaluated against the GUI of a traditional mail server. We found that our proposed architecture performs much better than that of the existing GUIS. In this project we use voice to text and text to voice technique access for blind people.
Published by: K. Jayachandran, P. Anbumani
Author: K. Jayachandran
Paper ID: V3I3-1462
Paper Status: published
Published: June 6, 2017
Classification and Retrieval of Texture Images Using Gabor Filtering and Statistical Features
Content Based Image Retrieval (CBIR) is a developing trend in Digital Image processing. CBIR is used to search and retrieve the query image from wide range of database. Many features and algorithms can be used for efficient image retrieval. The features of CBIR as colors, shapes, textures etc. can be derived from image itself. This project represents the retrieval of images based on the texture images. The focus of project is on the images processing aspects and particular using texture features. With the help of Gabor filter features and some statistical feature of texture images we form a feature vector for extraction of features. For retrieval of images these features are useful. The most accurate result is obtained using Gabor features applied on Brodatz texture database. For comparing and finding similarity between features of query image and another image in the database is done by using Euclidean distance, Vector cosine angle distance and Manhattan distance. To analyze the better performance of retrieval of images these distances we plot the precision and recall graph with number of retrieved images respectively.
Published by: Vaishnavi Gadewar, Apoorva Deshmukh, Akshay Ekurge, Ashok Shinde
Author: Vaishnavi Gadewar
Paper ID: V3I3-1463
Paper Status: published
Published: June 6, 2017
Traffic Monitoring System Using IR Sensors
The project deals with counting the vehicle direction wise and also to alert the driver if there is any road block further ahead.system is implemented using two IR sensors in each signals and main roads.when the vehicle is sensed using first sensor the counter is incremented. When the second sensors sense the vehicle the counter is added to “vehivle count” list and the previous counter is decremented .it also stores the details of direction and location.the vishicle owner is informed about the traafic jam through a display screen placed in every main roads with the details of an alternate deviation
Published by: Deekshitha, Disha D, Malavika, Soumya
Author: Deekshitha
Paper ID: V3I3-1449
Paper Status: published
Published: June 6, 2017
Age Estimation Using Classifier Artificial Neural Network and Support Vector Machine Based On Face Images.
The most prominent challenge in the facial age estimation is lack of sufficient and incomplete training data. Aging is slower and gradual process therefore faces near close ages look quite similar this can allows us to utilize the face images at neighbouring ages with modelling to particular age. There are many potential applications in age specific human computer interaction for security control and surveillance monitoring. In the last few years biologically inspired features are used for human age estimation for face images but recently more focus put on method like scattering transform. The propose approach exploits scattering transform gives more information about features of the facial images. An efficient descriptor consisting scattering transform which scatters the gabor coefficients and pulled with Gaussian smoothing in multiple layer and is evaluated for facial feature extraction. These extracted features are classified using support vector machine and artificial neural network. Results for face based age estimation obtain by artificial neural network is more effective than support vector machine.
Published by: Rajan Vishnu Parab, Prof. Dattatray S. Bade
Author: Rajan Vishnu Parab
Paper ID: V3I3-1477
Paper Status: published
Published: June 6, 2017
