Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition. Atypical communication mostly occurs in tandem with ASD. We compared voice pitch of 16 Marathi children and adolescents with ASD of age of 7 to 18 with 27 Typically Developing (TD). Speech samples have been recorded and stored in .wav format with sampling frequency of 48000 Hz. For analysis we used PRAAT, a program for speech analysis, manipulation and synthesis. We divided the ASD and TD group into total 4 groups on basis of age and gender for comparison. We found that differences in voice pitch are present in these comparison groups, and male ASD group have more pitch variation than respective comparison groups. In future we look forward to include more ASD participants in study to increase the Marathi speech database for ASD.

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A traditional attendance system requires a cumbersome and time consuming process requiring unnecessary paper work and higher maintenance efforts. The problem with this approach is that it requires lots of paper which are the part of our non-renewable natural resources. We are in the age, where we have to think about sustainable development. Managing the attendance using mobile phone's fingerprint scanner will provide an alternative way in this direction.The project emphasize on the development of a standalone system that can track the attendance of the employee with the help of Wi-Fi Communication and fingerprint scanning between the employee and the management. In this project, we offer a convenient novel attendance checking method to take advantage of Wi-Fi 802.11x technology. Our application initiates AP mode Wi-Fi service for recording attendance of employee using cell phone's fingerprint scanner and for calculating salary of the employee. This smart application will connect and report to attendance server.

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