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Review Paper

The Cognizance of Implant Abutments selection: A Review

Dental implants have been one of the highly demanding treatment modalities in the field of dentistry since last few decades due to its various benefits such as its longevity, maintaining the integrity of oral tissues and structure and prevention of bone loss. Implant abutments are main components which serves in restoring dental implants. An abutment is that part of a dental implant which assembles a prepared tooth and is designed to be screwed into the implant body. It is the principal component which gives retention to the prosthesis. The parts of implant abutment are – The base, head and the collar. The base is that part of abutment which engages into the internal part of implant. The head acts as a prosthetic retainer and collar connects base and head. Thus, this review article mainly focuses on the implant abutments, its classification and abutment connection.

Published by: Dr. Rajat Chaudhari, Dr. Kishor Mahale, Dr. Smita Khalikar, Dr. Vilas Rajguru, Dr. Sonali Mahajan, Dr. Ulhas Tandale

Author: Dr. Rajat Chaudhari

Paper ID: V10I3-1158

Paper Status: published

Published: May 17, 2024

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Research Paper

Probe Method for Stock Price Prediction using Machine Learning Techniques

A novel approach, referred to as the "Probe Method," for predicting stock prices by leveraging advanced Machine Learning (ML) techniques. In the dynamic and unpredictable world of financial markets, accurate forecasting of stock prices remains a challenging task. The Probe Method integrates a sophisticated ML framework to uncover patterns, relationships, and trends within historical market data, offering a promising avenue for improved prediction accuracy. The methodology begins by formulating the stock price prediction as a supervised learning problem, where historical stock prices, technical indicators, and relevant economic factors collectively form the input features. The Probe Method introduces a unique twist by employing a diverse set of ML algorithms, acting as "probes," to extract valuable insights from the data.

Published by: Parnandi Srinu Vasarao, MIDHUN CHAKKARAVARTHY

Author: Parnandi Srinu Vasarao

Paper ID: V10I3-1157

Paper Status: published

Published: May 17, 2024

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Research Paper

News Data Classification using Natural Language Processing and Large Language Models

In order to arrange and evaluate this enormous amount of data, effective categorization techniques are now essential due to the exponential growth of digital news material. This study investigates the use of Large Language Models (LLMs) and other Natural Language Processing (NLP) approaches for the classification of news data. We study how well LLMs do automatic news article classification into predefined classes or subjects. We show through experimental evaluation that LLM-based techniques are capable of effectively classifying news data, providing valuable information about future directions and possible applications in this field.

Published by: Prabhanjay Singh, Gurpreet Kour

Author: Prabhanjay Singh

Paper ID: V10I3-1156

Paper Status: published

Published: May 15, 2024

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Research Paper

Centralized street light monitoring system using IoT

The importance of solar LED street lighting systems in reducing the significant energy consumption of conventional street lights is described in this abstract. It emphasizes how solar panels and IoT technology may be combined for effective energy management and conversion. The primary goals of the system are intelligent light control with motion sensors, problem detection through GSM technology, and real-time monitoring of solar panel and battery performance. Energy efficiency and the use of renewable energy sources are provided by this system, which uses solar radiation during the day to power LED lights at night. It also highlights the project's role in facilitating effective IoT integration and data transfer, which makes real-time energy management and monitoring possible.

Published by: Suriya. A, Vetri. J, S. Chanthini

Author: Suriya. A

Paper ID: V10I3-1148

Paper Status: published

Published: May 14, 2024

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Research Paper

Intelligent navigation through recommended floor plans

Navigation is essential in the working of a helper robot. Lack of floor plan hinders the training of the helper bots. A floor plan recommender system will help solve this concern. Creating building floor plans is also very essential in the planning and construction of a building. Moreover, the integration of robotic mobility would provide a real-time understanding of the spatial layouts, which contributes to a more efficient and dynamic design implementation. The goal of this project is to develop a SimGNN-based recommendation system that suggests floor plans that satisfies the client requirements about the spatial relationship. The SimGNN-based model calculates similarity between the graphs after transferring the spatial relationship in the floor plan to the graph. We aim to utilize the recommended floor plans to enable the autonomous navigation of a robot. By mentioning the start and the finish point of the robot, a path is created and the robot will maneuver through the obtained path. Through this integration of recommendation system with the robotic mobility, we aim to optimize the training process of helper bots along with improving the design and construction process of a building.

Published by: Ananya Babu, Jawhara Fathima, Khrithikesh M U, Dr. Elizabeth Isaac

Author: Ananya Babu

Paper ID: V10I3-1146

Paper Status: published

Published: May 14, 2024

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Research Paper

The Impact of Artificial Intelligence on Business Growth: A Comprehensive Analysis

Business has been revolutionized by artificial intelligence (AI) as machines can do what was once assigned to the human brain. We examine the effect of AI on productivity improvement and growth in various sectors through this research paper. The document evaluates the impact of AI on optimizing operations, enhancing decision-making, and fostering innovation by arguing that it affects all these areas. For instance, Amazon has made use of AI techniques to improve its efficiency by reducing costs and increasing customer satisfaction levels. In addition to that, this essay also discusses upcoming trends where AI is expected to change a lot about business practices including its uses in politics, education, and the fashion industry. This essay brings out the many-sided advantages of using AI for growing business and maintaining competitiveness with empirical evidence and statistical insights.

Published by: Manhar Shankar

Author: Manhar Shankar

Paper ID: V10I3-1149

Paper Status: published

Published: May 8, 2024

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