Water management is one of the crucial topics discussed in most of the international forums. Water harvesting and recycling are the major requirements to meet the global upcoming demand of the water crisis, which is prevalent. To achieve this, we need more emphasis on water management techniques that are applied across various categories of the applications. Keeping in mind the population density index, there is a dire need to implement intelligent water management mechanisms for effective distribution, conservation and to maintain the water quality standards for various purposes. The prescribed work discusses about few major areas of applications that are required for efficient water management. Those are recent trends in wastewater recycle, water distribution, rainwater harvesting and irrigation management using various Artificial Intelligence (AI) models. The data acquired for these applications are purely unique and also differs by type. Hence, there is a dire need to use a model or algorithm that can be applied to provide solutions across all these applications. Artificial Intelligence (AI) and Deep Learning (DL) techniques along with the Internet of things (IoT) framework can facilitate in designing a smart water management system for sustainable water usage from natural resources. This work surveys various water management techniques and the use of AI/DL along with the IoT network and case studies, sample statistical analysis to develop an efficient water management framework.

In recent years, Sentimental Analysis is used in all online product firms. The number of users using the particular product has increased which makes the industry to improvise the characteristics of the product. These days, many users who are using websites, blogs, online shopping tends to review the products they used. These reviews were taken into consideration by other users during their search for products. Hence the industry has found the root of delivering the correct product searched by the user based on the reviews of the users using the concept of sentimental analysis. Sentimental Analysis is the concept of data analysis where the collections of reviews are taken into consideration, and those reviews are analyzed, processed and recommended to the user. The reviews given are longer and which consist of a few paragraphs of content. In this paper, the dataset is collected from the official product sites. Initially, these reviews must be pre-processed in order to remove the unwanted data’s such as stop words, be verbs, punctuations, and conjunctions. Once, the pre-processing is over the trained dataset is classified using Naive Bayes and SVM algorithm. These existing algorithms provided the accuracy which is not worth enough. Hence, an ensemble approach has been applied to enhance the accuracy of the given reviews. An ensemble is a classification approach by combining two or more algorithms and calculate the mode value based on the vote reference for every algorithm which is used. In this paper, Naive Bayes, SVM, and Ensemble algorithm are combined. We proposed an Ensemble method that helps in providing better accuracy than the current existing algorithm. Once the accuracy is calculated, based on the reviews, the particular product is recommended for the user.

This paper summarizes the findings from an empirical study carry out the online learning. The impact of information technology in our day-to-day life has been profound. Among many cross disciplines that have been enriched (or benefited) by information technology, educational media is not an exception. MOOC (Massive Open Online Courses brings learning, teaching and assessment. MOOC is a Web-based distance-learning program that is designed for the participation of large numbers of geographically dispersed students. In addition, Google and other companies are involving to design and fund to low-cost eLearning. Niche market provides nine certification courses via MOOC, to satisfy the employees specific needs. However, in the present day context the opinion on embracing MOOC by an University has been quite debatable. Addressing this debate on both sides, this papers presents the opinion expressed by the stakeholders in education towards embracing MOOC. Based on the findings from the study, the paper will discuss the challenge and broad concerns applicable to eLearning. The survey is focused on providing a consolidated fact that based on penetration of eLearning. This paper is aimed at providing a solid analysis of eLearning with the help of IT infrastructure in India. The survey contains demographic distribution of faculties; student and system administrator ratio is 39.6. Among a total of 792 of 2000 participants. It is focused that eLearning strategy in India.

People have disorder of liver that require medical care at correct time. It is utmost important to find the disease before it elapse the curable stage. Significantly, much of understanding of organ development has arisen from analyses of patients with liver deficiencies. Data mining is beneficial to find the disease at early stage based on the factors that can be gathered by performing test on the patient. Nowadays, around 65 % of the population in India are eating junk foods which minimize the metabolism rate and effect liver in many ways. In recent years, liver disorders have excessively increased and are still considered to be life threatening because it has caused low survivability. Still the patients having liver diseases are increasing and the symptoms of the diseases are difficult to identify. The doctors often failed to identify the symptoms which can cause severe damages to the patient and it requires utmost attention. So, we are applying Medical Data Mining (MDM) for predicting the liver disease by using the historical data and understanding their patterns. Here we are using prediction model i.e. Support Vector Machine (SVM) to achieve the goal.

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