Informatics Publishing Limited

S. Mumtazuddin ¹, A. K. Azad ¹, Manoj Kumar ¹

Affiliations
1 University Department of Chemistry, B.R.A. Bihar University, Muzaffarpur-842 001, Bihar, IN

Abstract

This paper presents quality of water samples from bored tube wells at different sites along the Budhi Gandak belt from Akharaghat to Musahari in Muzaffarpur district of Bihar state during monsoon season of 2011. The parameters such as pH, conductivity, TDS, DO, total hardness, alkalinity, sodium, potassium, calcium, magnesium and chloride as well as heavy metals such as Cu, Zn, Fe and As have been studied. TDS of almost all samples exceeded the maximum permissible limit of WHO. Iron was also found much above the maximum permissible limit in nearly all the samples. The water samples along Budhi Gandak belt under study have arsenic contamination in some samples which even much exceeded the maximum permissible limit at certain sites. The arsenic contamination in the groundwater of this area is serious concern for human health.

Keywords

Groundwater Quality, Heavy Metals, Budhi Gandak Belt, Muzaffarpur.

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A. K. Azad ¹, M. A. Rashid ¹, M. S. Hossain ¹

Affiliations
1 Electronics & Telecommunication Engineering Department, Northeastern University, Boston, US

Abstract

The smart classroom of the future we envision will greatly enhance the learning experience and achieve seamless communication between students and teachers through real-time detection and machine intelligence. Additionally, facial recognition can capture student emotions such as happiness, sadness, neutrality, anger, nausea, surprise, and more. From this sentiment we analyze it and in the analysis derive the final overall student behavior of a particular speech. So, you can also get results in the form of teacher feedback and student feedback from student behavior. The three main parts of the student attendance system are then described in detail using two deep learning facial recognition algorithms. Behavioral analysis model based on facial recognition neural network or Haar classifier. iii) Automatic teacher feedback based on student behavior analysis.

Keywords

Face Detection, Face Recognition, Face Identification, Behaviour Analysis.

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