ASSESSMENT OF WATER QUALITY ANALYSIS USING PHYSICO-CHEMICAL PARAMETERS: A CASE STUDY OF BHIMA RIVER IN DAUND TAHSIL, PUNE DISTRICT, MAHARASHTRA.

Objective: Our objective is to examine the previous and current physical and chemical properties of the water in Bhima river in the study area as well as to assess the change in physical and chemical properties of the study area. Materials and Methods: The physico-chemical characteristics of Bhima river water in Daund Tahsil (Pune district) have been studied. The stretch of Bhima river in Daund Tahsil is extending downstream from Dahitane to Malthan. Bhima River was assessed at three various stations in terms of critical pollution parameters in the year 2010-11 and 2011-12. Three sampling stations viz., Station A-near Dahitane (Towards the West side), Station B-near Rahu (in the middle), and Station C-near Daund (towards East side) were established for the collection of water samples during April, 2011 to March, 2012. The water quality parameters namely transparency, colour, (transparent-very turbid), turbidity, total dissolved solids pH ,dissolved oxygen, free carbon dioxide, total alkalinity, Biochemical Oxygen Demand, Chemical Oxygen Demand, total hardness, chloride, nitrate, nitrite, sulphate, phosphate , silicate, sodium, potassium, Calcium and Magnesium reflects on the nature of the river in the study area. Results: On the basis of various parameters studied it was found that the rivers receive industrial effluents from various industries, which are situated on the bank of river, along with the heavy loads of agriculture run off. Conclusion: The conclusion also deals with community response about Bhima river out of the many problems perceived by the river bank residents, the priority problem observed by maximum is that of the mosquitoes and habitants, Agriculture, including commercial livestock and poultry farming. is the source of many organic and inorganic pollutants in surface waters and ground water. Hence the river water quality is needed to be improve

Big data, cognitive computing and the future of Learning Management Systems

Since the early years, when they started to enter the market, Learning Management Systems (LMSs) demonstrated their utility inside learning environments, contributing to the diffusion of e-learning especially in those Institutions with a low budget or no internal knowledge for developing e-learning initiatives. Today, they have reached a high maturity level, providing professional solutions to almost any educational need referring to distance learning. However, in our opinion, there are two important evolutions that should profoundly change the architecture of these pillar software tools. First, the acquisition of an enormous amount of data related to educational tasks will be very interesting for all the actors involved in educational processes (teachers, students, researchers, administrative personnel), and this will be particularly evident when standards like Experience-API (xAPI) will help to provide a more pervasive experience for learners. Second, we are observing the rise of new era for software platforms, characterized by machine learning, deep learning, cognitive computing and many other technologies that substantially give the computer a much more active role in the respective processes. We believe that this new paradigm will apply to education too. What this will entail is mainly related to exponential learning, a process of exponential growth of training demand because new knowledge and skills must be delivered at a speed never seen before, and where big data contexts are fundamental. In this paper, we present an analysis of how LMSs should evolve in the future, in our opinion and according to our experience, in terms of functionalities and services provided to users. We believe that current LMSs and their software architectures, mainly based on traditional multi-tier, relational database-oriented architectures will not be enough to stand the impact of these two new paradigms for modern learning environments. We are in the process of re-designing a virtual community platform that we have created and developed along the years, used in our universities and in several public and private organizations. The platform is oriented towards the support of collaborative processes, where of course e-learning is one of the most important, but not the only one, and where we are adding new services supporting collaboration in different ways. In this paper we will present the software architectural changes and evolution according to the advent of big data and cognitive computing