Volume 9 | Issue 10 |

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Internet, Textbooks, Trends, English Language.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Upliftment, outcastes

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Religious tourism remains an unstrapped sector by the hospitality industry despite it being very popular among the devotee.The region of Nagpur dotted with various spiritual and religious destination that can be explored and develop into popular tourist destinations. Entire territory is bless with scenic beauty and remains a hotspot for tourist. Adding religious places to tourism sector can help the region make a fortune.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Religion, tourism, survey, literature, Budha stupa

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Crimean-Congo Hemorrhagic Fever (CCHF), Viral disease, Afghanistan.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The term crptocurrency is marvel of late years representing computerized money dependent on standards of cryptography. Overall population might befuddle this term bitcoin, however numerous other crptocurrency emerged. The essential standards of all crptocurrencies are comparative and momentarily presented in this paper. The current review is centered around surveying the effect of crytocurrency. Crptocurrency are the new item in economy. The review responds to the inquiry 1.the crytocurrency is legitimized? 2. Is making an interest in crptocurrency is actually similar to making an interest in shares?. Besides fundamental plan of crytocurrency are examined.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cryptocurrency, Bitcoin, Digital currency, Blockchain Technology.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Healthy food habits in girls during adolescence are of utmost importance as practices followed during this age are carried out in the future and influence the food habits and thus the health of their families and community. So, the present study was carried out to assess the food and nutrient intake, anthropometric measurements, nutritional knowledge and dietary practices of hostel girls studying in Teerthanker Mahaveer University, Moradabad. A total of 100 girls staying in the hostel of Teerthanker Mahaveer University were selected using random sampling, and the data was collected regarding socio-economic profile, food and nutrient intake, anthropometric subjects, nutrition knowledge and dietary practices using survey schedules by interview method. The results revealed that the intake of mostly nutrients was deficient except for fat and vitamin C, which was 187.4 and 121.4 per cent 50-75% of the RDA. Only 68% of girls were normal according to BMI, and the rest were malnourished, with 18 per cent undernourished and 14 per cent over nourished. The reason for this was faulty food habits which were judged by their attitude and dietary practices. The majority of the population 55 per cent of girls had high knowledge level, 41 per cent had a medium level, and only 4% had low nutrition knowledge. The result of nutrition knowledge depicts that nutrition knowledge was not poor, but the population followed the wrong practices for food consumption. So, it is recommended to carry out campaigns in order to motivate the girls to follow good dietary practices.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As the speed of innovation increases at an accelerating rate, Individuals' ways of sharing their views on different websites is also expanding. On social media sites like Facebook, Twitter, and Yelp, there are various reviews and opinions. Scores are normally provided on a range of 1 to 5 stars. Assessment of opinions through textual information analysis has shown an important impact in analytic research because this offers useful options to emotions mining. Review is an evaluation of a product or service by someone who has used the product or service or has experience with it. The ranking of any e commerce site is heavily influenced by the opinions of its users. The purpose of this paper is to explain how a Machine Learning (ML) set of rules works on Yelp's database to evaluate, anticipate, and advocate brands. With the sentimental analysis algorithm, we analyzed Support Vector Machines, K- Nearest Neighbor, Multilayer Perceptron classifiers, Naive Bayes, , Decision Tree and Random Forest. The best result of the multi-layer perceptron classifier is 93.40 percent.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Sentimental Analysis, Opinion Mining, Natural Language Processing, Review rating prediction

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Capsaicinoids, chillies, ointment, pepper spray, dermal patch.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project introduces a framework for appropriately adapting and adjusting machine learning (ML) techniques used to construct electrocardiogram (ECG)-based biometric authentication schemes. It can help define the boundaries of required datasets and get training data with good quality. Use case analysis is adopted to determine the boundaries of datasets. Based on various application scenarios on ECG-based authentication, three different use cases are developed. With more qualified training data given to corresponding machine learning schemes, the precision on ML-based ECG biometric authentication mechanisms are increased in consequence. The ECG time slicing technique with the R-peak anchoring is utilized in this framework to acquire ML training data with good quality. In the proposed framework four new measure metrics are introduced to evaluate the quality of the ML training and testing data. In addition, a MATLAB toolbox, containing all proposed mechanisms, metrics, and sample data with demonstrations using various ML techniques, is developed. For developing ML-based ECG biometric authentication, the proposed framework can guide researchers to prepare the proper ML setups and the ML training datasets along with three identified user case scenarios.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Authentication, ECG Time Slicing, ECG Biometric Authentication, Machine Learning, R-peak Anchoring.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sign language is a somewhat complex language for normal people as they are no longer aware. Therefore, this can be quite difficult when a person is trying to talk to someone with physical disabilities such as the mute and the deaf. So imagine a technique that will allow you to recognize sign language. without knowing the actual language. This can help people recognize those who are facing physical challenges, a set of rules that uses image processing to detect how the hands are aligned, where this alignment is diagnosed from predefined data sets that we create and the textual content is diagnosed and then immediately displayed on the screen. it will make them less difficult to see.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deep Learning, Sign Language, Convolution Nueral Network

  License

Creative Commons Attribution 4.0 and The Open Definition