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• Design and Fabrication of Electrostatic Precipitator for Removal of Activated Carbon during Coal Burning
  Dileepan .N ; Manikandan .R; MohanKumar .S; NandhaKumar .R; Poovarasan .S
  Mechanical Engineering
  Year: 2019, Volume:5, Issue : 10
  Pages: 50 - 53

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  The process of removing dust particles in non-flammable gases and removing activated carbon from coal burning ash the electrostatic precipitator is used. It can be almost filter the dust particles from using ESP. An ESP uses a high voltage electrostatic field to separate Dust particles are removed from collecting electrodes. Cleaning is done while on the still online method for filtering process ESP for using in about 99.5% of particulate matter removed by this method. That is can be using three stage method for finding the particles precipitator can be one of the collecting the storage.

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  IJIRST Dileepan .N, Manikandan .R, MohanKumar .S, NandhaKumar .R and Poovarasan .S. "Design and Fabrication of Electrostatic Precipitator for Removal of Activated Carbon during Coal Burning" International Journal for Innovative Research in Science & Technology Volume 5 Issue 10 2019 Page 50-53 MLA Dileepan .N, Manikandan .R, MohanKumar .S, NandhaKumar .R and Poovarasan .S. "Design and Fabrication of Electrostatic Precipitator for Removal of Activated Carbon during Coal Burning." International Journal for Innovative Research in Science & Technology 5.10 (2019) : 50-53. APA Dileepan .N, Manikandan .R, MohanKumar .S, NandhaKumar .R and Poovarasan .S. (2019). Design and Fabrication of Electrostatic Precipitator for Removal of Activated Carbon during Coal Burning. International Journal for Innovative Research in Science & Technology, 5(10), 50-53. Chicago Dileepan .N, Manikandan .R, MohanKumar .S, NandhaKumar .R and Poovarasan .S. "Design and Fabrication of Electrostatic Precipitator for Removal of Activated Carbon during Coal Burning." International Journal for Innovative Research in Science & Technology 5, no. 10 (2019) : 50-53.

  

• A Dynamic Trust Computation Model for Secured Communication in Multi-Agent Systems
  Mrs. R. SudhaPriya ; Khirthi Vas G; Manoj Kumar R. P; Balaji Arunachalam K. K; Gowthaman R
  Computer Science and Engineering
  Year: 2019, Volume:5, Issue : 10
  Pages: 54 - 56

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  A Wireless Sensor Network (WSN) is a wireless network consisting of spatially distributed independent devices using sensors to monitor physical or environmental conditions. A data has to transferred between peer to peer transmission in more investigate performance by increasing the number of inserted branch. When increasing the number of branch to Increase the time consumption of end to end data delivery. A Transport Protocol is needed in Wireless Sensor Networks to control congestion and ensure reliable delivery of messages from the sensor nodes to the end to end data delivery. Transport Protocol to handle congestion and packet loss recovery in Wireless Sensor Network has been debated to Peer to Peer transmission. The proposed method using a Buffer Bloat Nagle algorithm is used to automatically concatenate a number of Network Buffer. This process increases the efficiency of a network application system by decreasing the number of packets that must be sent. The algorithms rely on measuring the occurrence of packet drops to determine the available bandwidth between two ends of a connection. The peer to peer transmission there is no Centralized Server between sources to destination. With this method, it is shown that even without a Network Buffer, it is possible to achieve better reliability in harsh environments than others well-known methods. In this way, this protocol guarantees the end-to-end data delivery, using a minimum amount of device memory.

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  IJIRST Mrs. R. SudhaPriya, Khirthi Vas G, Manoj Kumar R. P, Balaji Arunachalam K. K and Gowthaman R. "A Dynamic Trust Computation Model for Secured Communication in Multi-Agent Systems" International Journal for Innovative Research in Science & Technology Volume 5 Issue 10 2019 Page 54-56 MLA Mrs. R. SudhaPriya, Khirthi Vas G, Manoj Kumar R. P, Balaji Arunachalam K. K and Gowthaman R. "A Dynamic Trust Computation Model for Secured Communication in Multi-Agent Systems." International Journal for Innovative Research in Science & Technology 5.10 (2019) : 54-56. APA Mrs. R. SudhaPriya, Khirthi Vas G, Manoj Kumar R. P, Balaji Arunachalam K. K and Gowthaman R. (2019). A Dynamic Trust Computation Model for Secured Communication in Multi-Agent Systems. International Journal for Innovative Research in Science & Technology, 5(10), 54-56. Chicago Mrs. R. SudhaPriya, Khirthi Vas G, Manoj Kumar R. P, Balaji Arunachalam K. K and Gowthaman R. "A Dynamic Trust Computation Model for Secured Communication in Multi-Agent Systems." International Journal for Innovative Research in Science & Technology 5, no. 10 (2019) : 54-56.

  

• Review on Art of States of Augmented Reality Technology in Education
  Karolina Piotrowski ; Tomasz Jankovski; Yulia Danilenko
  Education
  Year: 2019, Volume:5, Issue : 10
  Pages: 57 - 60

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  Technology-assisted learning getting more and more critical in delivering up to the date learning environment. Augmented Reality known for its infinite possibilities and areas of use is gaining more and more popularity and a wide range of research, articles, and books are published outlining technology’s use in different domains including healthcare, advertisement, mechanical assembling etc. Last decade seen the most attention of researchers towards the use of the technology as the technology become available to be used on portable and mobile devices, broadening the possible implementation of the technology. Within this period of time, numerous research regarding the use of technology in learning, teaching, and training environments were published. With this review article, we aim to highlight the potential of the novel Augmented Reality technology’s current implementations in the learning process. Particularly, we discuss the impact of the technology is such complex subjects as Physics, Biology, and Anatomy.

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  IJIRST Karolina Piotrowski, Tomasz Jankovski and Yulia Danilenko. "Review on Art of States of Augmented Reality Technology in Education" International Journal for Innovative Research in Science & Technology Volume 5 Issue 10 2019 Page 57-60 MLA Karolina Piotrowski, Tomasz Jankovski and Yulia Danilenko. "Review on Art of States of Augmented Reality Technology in Education." International Journal for Innovative Research in Science & Technology 5.10 (2019) : 57-60. APA Karolina Piotrowski, Tomasz Jankovski and Yulia Danilenko. (2019). Review on Art of States of Augmented Reality Technology in Education. International Journal for Innovative Research in Science & Technology, 5(10), 57-60. Chicago Karolina Piotrowski, Tomasz Jankovski and Yulia Danilenko. "Review on Art of States of Augmented Reality Technology in Education." International Journal for Innovative Research in Science & Technology 5, no. 10 (2019) : 57-60.

  

• Security and Challenges in Big Data: A Survey
  Jignesh Solanki ; Vijaysinh Jadeja; Chirag Patel; Shaktisinh Parmar; Sohil Gadhiya
  Computer Engineering,
  Year: 2019, Volume:5, Issue : 10
  Pages: 61 - 63

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  The big data explosion has given rise to a host of information technology tools and capabilities that enable organizations to capture manage and analyze large sets of structured and unstructured data for actionable insights and competitive advantage. But with this new technology comes the challenge of keeping sensitive information private and secure. Big data that resides within a Hadoop environment can contain sensitive financial data in the form of credit card and bank account numbers. It may also contain proprietary corporate information and personally identifiable information (PII) such as the names, addresses and social security numbers of clients, customers and employees .Due to the sensitive nature of all of this data and the damage that can be done should it fall into the wrong hands, it is imperative that it be protected from unauthorized access. To that end, here is a look at some common Hadoop security issues along with best practices to keep sensitive data safe and secure.

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  IJIRST Jignesh Solanki, Vijaysinh Jadeja, Chirag Patel, Shaktisinh Parmar and Sohil Gadhiya. "Security and Challenges in Big Data: A Survey" International Journal for Innovative Research in Science & Technology Volume 5 Issue 10 2019 Page 61-63 MLA Jignesh Solanki, Vijaysinh Jadeja, Chirag Patel, Shaktisinh Parmar and Sohil Gadhiya. "Security and Challenges in Big Data: A Survey." International Journal for Innovative Research in Science & Technology 5.10 (2019) : 61-63. APA Jignesh Solanki, Vijaysinh Jadeja, Chirag Patel, Shaktisinh Parmar and Sohil Gadhiya. (2019). Security and Challenges in Big Data: A Survey. International Journal for Innovative Research in Science & Technology, 5(10), 61-63. Chicago Jignesh Solanki, Vijaysinh Jadeja, Chirag Patel, Shaktisinh Parmar and Sohil Gadhiya. "Security and Challenges in Big Data: A Survey." International Journal for Innovative Research in Science & Technology 5, no. 10 (2019) : 61-63.

  

• A Review on Artificial Intelligence with Concept of Deep Learning
  Prof. Chirag R. Patel ; Prof. Vijaysinh K. Jadeja; Prof. Jignesh N Solanki; Prof. Shaktisinh S. Parmar; Prof. Sohil A. Gadhiya
  Computer Engineering
  Year: 2019, Volume:5, Issue : 10
  Pages: 64 - 68

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  Artificial intelligence (AI) is a branch of computer science dealing with the simulation of intelligent behaviour in computers. It is fast growing technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of most of country’s economy and it used to solve various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication technology (ICT) and robot technology (RT). Machine learning is a subset of AI. That is, all machine learning counts as AI, but not all AI counts as machine learning. For example, symbolic logic – rules engines, expert systems and knowledge graphs – could all be described as AI not as machine learning. Deep learning is a subset of machine learning. Usually, when people use the term deep learning, they are referring to deep artificial neural networks. This paper summarizes overview of artificial intelligence Technology. Furthermore, it presents how deep learning work.

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  IJIRST Prof. Chirag R. Patel, Prof. Vijaysinh K. Jadeja, Prof. Jignesh N Solanki, Prof. Shaktisinh S. Parmar and Prof. Sohil A. Gadhiya. "A Review on Artificial Intelligence with Concept of Deep Learning" International Journal for Innovative Research in Science & Technology Volume 5 Issue 10 2019 Page 64-68 MLA Prof. Chirag R. Patel, Prof. Vijaysinh K. Jadeja, Prof. Jignesh N Solanki, Prof. Shaktisinh S. Parmar and Prof. Sohil A. Gadhiya. "A Review on Artificial Intelligence with Concept of Deep Learning." International Journal for Innovative Research in Science & Technology 5.10 (2019) : 64-68. APA Prof. Chirag R. Patel, Prof. Vijaysinh K. Jadeja, Prof. Jignesh N Solanki, Prof. Shaktisinh S. Parmar and Prof. Sohil A. Gadhiya. (2019). A Review on Artificial Intelligence with Concept of Deep Learning. International Journal for Innovative Research in Science & Technology, 5(10), 64-68. Chicago Prof. Chirag R. Patel, Prof. Vijaysinh K. Jadeja, Prof. Jignesh N Solanki, Prof. Shaktisinh S. Parmar and Prof. Sohil A. Gadhiya. "A Review on Artificial Intelligence with Concept of Deep Learning." International Journal for Innovative Research in Science & Technology 5, no. 10 (2019) : 64-68.

  

• Sentiment Analysis and Opinion Mining: A Review
  Shaktisinh S. Parmar ; Vijaysinh K. Jadeja; Sohil A. Gadhiya; Chirag R. Patel; Jignesh N. Solanki
  Computer Engineering
  Year: 2019, Volume:5, Issue : 10
  Pages: 69 - 73

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  In recent years, the enormous growth of web tools, lead to massive quantity of user generated information in online systems. This large amount of information on web makes them viable for use as data sources, in applications based on opinion mining and sentiment analysis. Social media such as twitter, blogs, Facebook etc. have become the main channel of communication. People share their view and opinion on different people and products on internet. Opinion mining is natural language processing which could track the mood of the people on any products by tacking their reviews. We have can find the sentiments (or sentimental words) from given document by using Natural Language Processing and then by analyzing it we can classify it in different category (i.e. News can be categorized in positive and negative). In this paper we have discussed procedure of opinion mining and different techniques for sentiment analysis and opinion mining.

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  IJIRST Shaktisinh S. Parmar, Vijaysinh K. Jadeja, Sohil A. Gadhiya, Chirag R. Patel and Jignesh N. Solanki. "Sentiment Analysis and Opinion Mining: A Review" International Journal for Innovative Research in Science & Technology Volume 5 Issue 10 2019 Page 69-73 MLA Shaktisinh S. Parmar, Vijaysinh K. Jadeja, Sohil A. Gadhiya, Chirag R. Patel and Jignesh N. Solanki. "Sentiment Analysis and Opinion Mining: A Review." International Journal for Innovative Research in Science & Technology 5.10 (2019) : 69-73. APA Shaktisinh S. Parmar, Vijaysinh K. Jadeja, Sohil A. Gadhiya, Chirag R. Patel and Jignesh N. Solanki. (2019). Sentiment Analysis and Opinion Mining: A Review. International Journal for Innovative Research in Science & Technology, 5(10), 69-73. Chicago Shaktisinh S. Parmar, Vijaysinh K. Jadeja, Sohil A. Gadhiya, Chirag R. Patel and Jignesh N. Solanki. "Sentiment Analysis and Opinion Mining: A Review." International Journal for Innovative Research in Science & Technology 5, no. 10 (2019) : 69-73.

  

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