Volume 9 | Issue 3 |

 Abstract

Expanding cost and request of vitality has driven numerous associations to discover savvy ways for checking, controlling and sparing vitality. A keen Energy Management System (EMS) can contribute towards reducing the expenses while as yet meeting vitality request. The rising advances of Internet of Things (IoT) what's more, Big Data can be used to all the more likely oversee vitality utilization in private, business, and mechanical divisions. This paper presents an Energy Management System (EMS) for shrewd homes. In this framework the used to energy consuming for cloud system an authenticate the stage and present real world energy data. In the results of the experiments show clearly the benefit and practicality of the proposed platform each home gadget is interfaced with an information procurement module that is an IoT object with an interesting IP address bringing about a huge work remote system of gadgets. The information obtaining System on Chip (SoC) module gathers vitality utilization information from every gadget of each shrewd home furthermore transmits the information to a concentrated server for additional preparing and investigation. This data from all private territories aggregates in the utility's server as Big Data. The proposed EMS uses off-the-rack Business Intelligence (BI) and Huge Data investigation programming bundles to more readily oversee vitality utilization and to satisfy buyer need. Since air molding adds to 60% of power utilization in Bedouin Gulf nations, HVAC (Heating, Ventilation and Air Molding) Units have been taken as a contextual investigation to approve the proposed framework. A model was assembled and tried in the lab to mirror little local location HVAC systems

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud Computing, Big Data Mining, Energy Management System (EMS), Smart Homes, System on Chip, Business Intelligent and Heating, Ventilation and Air Molding.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Psychological Wellbeing, Adolescents

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Rose apple is an underutilized mild flavoured, slightly astringent and juicy fruit. The fruits are very low in cholesterol and sodium and good source of niacin, iron, sulfur, calcium and potassium. They are high in vitamin A and vitamin C. The objective of the study was to formulate rose apple-based ice cream formulation and analyze its nutrient composition. The addition of fruits in ice cream will increase the nutritive value of the product specially minerals, carbohydrates and dietary fibre. The organoleptic parameters (i.e., color, flavor, taste, texture, overall acceptability) and chemical parameters (i.e., fat, protein, total solids, sucrose, and acidity) of rose apple ice cream was analysed. Sensory analysis was also conducted in a nine-point hedonic scale in which the overall acceptability of rose apple ice cream was found to be high in the case ice cream with 15% rose apple.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Rose apple, Ice cream, organoleptic parameters, hedonic scale

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Stream, physicochemical parameters, borehole, water quality, heavy metals, contamination

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Technology, Social network sites, Peers, Development, Student Engagement.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Through this article, we intend to describe the process of modelling real world problems into known statistical models and understand how the solutions are obtained with the help of different statistical techniques.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Data ,Modeling, Hypothesis Testing,Regression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Extracurricular Achievements, Young adult, Employment Status

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Regression analysis is an machine learning model for sale prediction.For this kind of prediction a company needs time series of data based on that it also predict the future sales.In this project we will analyze the sale data of the company based on that we predict the sales for a specific product. For this project we apply multi-variable linear regression using a straight-lined equation.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Prediction, straight-lined equation,modules

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The E-commerce websites have been emerged in a high range of marketing benefits for the users to publish or share the experience of the received product by posting review that contain useful comments, opinions and feedback on the product. Nowadays, millions of customers gain opportunities to compare similar products in online websites and pick their favorites in digital retailers, such as Amazon.com and Taobao.com. Customer reviews in social media and electronic commerce Websites contain valuable electronic word information of products. Sentiment Analysis is widely applied as voice of customers for applications that target marketing and customer service. Sentiment extractors in their most basic form categorize texts as either having a positive or negative or sometimes neutral sentiment. A common application of sentiment analysis is the automatic determination of whether an online review contains a positive or negative assessment. Hence, in this paper, with the help of the techniques on sentiment analysis, opinionated sentences referring to a specific feature are first identified from product online reviews. We have proposed deep learning method as a classification model for finding the state of review. The results showed recommended site for the customer based on the early reviews, past reviews and answer given to query review for the customer. Moreover, it is observed that the proposed technique can able to reply all the reviews with a better similarity like a human response to the customer.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-commerce, opinion analysis, sentiment analysis, deep learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords:, Internet of Things, enhanced learning, tremendous challenges, affluent.

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Creative Commons Attribution 4.0 and The Open Definition