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Analytical and Systematic Study of Artificial Neural Network

Artificial Neural Network may be a neural network motivated by the biological neural network where numbers of neurons are interconnected with each other. The neurons in artificial neural network are operating and arranged in such a way that they invigorate the basic construction of the neurons within the human cerebrum. the basic rationale behind the factitious neural network is to implement the structure of the biological neuron in an exceedingly way that the regardless of the function that the human brain perform with the help of biological neural network, that thusly will the machines and frameworks can likewise perform with the help of artificial neural network. This paper gives a concise outline of a man-made neural network with its working, architectures, and general organization, and so forth. This paper additionally express some advantage and disadvantage , application of the artificial neural network in some most vital areas like image processing, signal processing, pattern recognition, function approximation, forecasting supported the past data and a few more.

Published by: Shreyas Barge

Author: Shreyas Barge

Paper ID: V8I2-1321

Paper Status: published

Published: April 25, 2022

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Research Paper

Leveraging a convolutional neural network for developing a hand-written text recognition system

The explication revolving around the digital outlook of Hand-written Text has been carried out widely with the upsurge of Technological Advancements in the field of Artificial Intelligence. Automation in daily chores has made human life more consistent and yet stable. Machine Learning and Deep Learning modus operandi has been actuated for contemplating the automated outlook. Hand-written Text Recognition has been a well-scrutinized domain wherein the incorporation of different paradigms of learning has been elucidated. The escalation into the digitization of almost everything necessitates the prevalence of the same in assuaging the Text Recognition System as well. In this articulation, we’ve consummated Convolutional Neural Networks (CNNs) i.e., 03-Layered, 04-Layered, and 05-Layered Convolutional Neural Networks (CNNs) which are trained over Hand-written Characters which include Alphabets (A-Z), Digits (0-9) and widely utilized Symbols and thereby detecting the Text from a Dataset of diverse Hand-written words consisting of Names and Surnames. The proposed Hand-written Text Recognition System is structured in the Offline method, as the scarcity of proficient outcomes revolves around it when compared to Online prospects. The proposition also gave us a comparative insight into the impact of layers in models. The efficacy we achieved was phenomenal, which gave us a potent resolution for contemplating it in real-time.

Published by: Likith Pulluri, Yashwanth Konakanchi, Divya Prabha, Asima Nayak, Pradeep Kumar Mishra

Author: Likith Pulluri

Paper ID: V8I2-1319

Paper Status: published

Published: April 23, 2022

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Research Paper

Solar power plant with MPPT algorithm

This Document presents the Solar Power plant with the MPPT algorithm. The increase in usage of Electrical energy has encouraged the growth of different types of conventional power generating systems like hydroelectric, thermal, wind, solar, nuclear, geothermal, etc. In this project, we developed solar panels with the MPPT algorithm to operate the photovoltaic modules in a manner to extract the maximum power from the system. This method can increase the tracking efficiency.

Published by: M. Divya

Author: M. Divya

Paper ID: V8I2-1314

Paper Status: published

Published: April 23, 2022

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Research Paper

Visitor information management and analysis system: Neeri-pass

The visitor entry system is designed to close the visitor registration center and visitor information management services, it will be able to speed up the visitor registration process, determine who is on the premises after the meeting and inform the system. This is a review paper in which the system solves the problem of appointments and it electively captures all-relevant information about the visitors and that information is recorded in the centralized database server, which provides data management and manipulation through searching for future purposes in the organization. The benefits of the Visitor Gate pass Management System are enhancing the level of security enforced on-premises, providing an organized view of visitor records, and reducing the time spent on managing visitor information.

Published by: Barkha Ramteke, Dr. Sonali Ridhorkar

Author: Barkha Ramteke

Paper ID: V8I2-1316

Paper Status: published

Published: April 23, 2022

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Research Paper

Hydrochemical analysis and assessment of groundwater quality in and around Yadadri district, Telangana, India.

This study looks at the types of groundwater and water quality in a semi-arid watershed in southern India that includes 35 settlements. In both seasons, cation concentrations (Na+> Ca2+> Mg2+> K+) and anions (HCO3- > Cl > NO3-> SO 2-> PO43-) follow a consistent pattern across most of Peninsular India. The sodium-bicarbonate-chloride (Na+-HCO3-Cl-) classifies the groundwater. The influence of natural sources on groundwater composition across the watershed's communities is demonstrated by a Pearson correlation study of important ions. The water composition of these communities, according to Gibb's plot, is the result of rock and water interaction during infiltration and aquifer storage. Due to a severe water deficit in this region, particularly during the pre-monsoon season, deep bore wells have been drilled for both home and agricultural purposes. All of the physical dimensions and chemical contents exceed the World Health Organization (WHO) and Bureau of Indian Standards (BIS) permissible limits, rendering it unsafe for drinking, domestic, or agricultural use. Around 54 percent of groundwater samples, regardless of season, are found to be unfit for irrigation (KR 1). During the post-monsoon season, groundwater from villages near the local river (Bukleru river) is only acceptable for irrigation (KR>1).

Published by: Bharath Kumar Punna, Botla Amarender, K. Praveen Reddy, G. Prabhakar

Author: Bharath Kumar Punna

Paper ID: V8I2-1315

Paper Status: published

Published: April 23, 2022

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Research Paper

Vison-based human activity recognition

There have been substantial advances in HAR (Human Activity Recognition) in the past several years due to the advancement of the IoT (Internet of Things). HAR may be used in a range of contexts, including elder care, surveillance systems, and anomalous behavior detection. Different machine learning techniques have been used to anticipate human actions in a particular circumstance. Feature engineering techniques, which may pick an ideal collection of features, have outperformed typical machine learning techniques. Deep learning models, like CNN (Convolutional Neural Networks), on the other hand, are known to extract features and minimize computing costs automatically. We employ the CNN model for predicting actions from the Weizmann Dataset in this article. To extract deep image features and trained machine learning classifiers, transfer learning is used in particular. We found that VGG-16 has an accuracy of 96.95 percent in our experiments. We also found that VGG-16 outperformed the rest of the CNN models that were used in our experiments.

Published by: M. Madhusudhan, B. Manish Kumar, P Rohit, V. Sri Ram Reddy, V. Sai Chandana

Author: M. Madhusudhan

Paper ID: V8I2-1320

Paper Status: published

Published: April 23, 2022

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