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International Conference on Manufacturing, Robotic, and Mechanical Engineering (IC-MRMEE)

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Articles

AI-Enhanced Experimental Analysis on Dairy Wastewater Treatment Using Rotatory Biological Contactor

Ms. Pallavi S.Chakole, Dr. Ajay R.Gajbhiye, Mr.S.W.Dhengare,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

one of the largest sectors in India, after the sugar business, is the dairy industry. This industry is a major contributor to the ruraal Indian economy. The presence of protein and lipids in this effluent contributes to its turbidity and color since they are organic and sustainable. While irrigation is a frequent discharge option for cleaned dairy effluent, tertiary treatment must be included as well. One biological technique that can be used to treat wastewater is the Rotary Biological Contractor (RBC). Wastewater treatment using RBC is an affordable, eco-friendly, and energy-efficient method. The current work emphasized the main parameter on which performance of RBC is based is rotational speed (rpm), detention time; influent and effluent wastewater characteristics are studied. The water sample taken for this investigation comes from dairy farms. An apparatus for testing of waste water, design the assembly of the Rotary Biological Contractor. The RBC is comprised of a horizontal shaft that runs through the centers of the revolving drums. The complete assembly is inserted into the tank so that the drum is about 40% submerged in water, with the shaft just above the liquidators’ surface. Microorganisms proliferate on the drum apos; s surface which is wounded by stainless steel. By means of this assembly, the revolving drum is in touch with liquid, facilitating the breakdown of organic waste. The model ran for ninety hours at a rotating speed of five revolutions per minute. The results show that this process has high BOD removal rate, high cod removal rate with less detention time and it also reduce odor problem.

A Novel Loss Function for MPM-Net to Improve Image Defogging Quality Using Wavelet Transform-Based Models

R Prasanthi Kumar, R Mahaveerakannan,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

We improve outdoor picture defogging using a novel wavelet-based MPM-Net loss function. Through experiments on simulated and real-world datasets for sharper and more distinct photographs, the suggested function enhances picture clarity by collecting two types of frequencies: low and high.

Artificial Intelligence-Based Chatbot withVoiceAssistance

A. Balamurugan, D. Thiruppathi, S. P. Santhoshkumar, K. Susithra,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

The use of smartphones, tablets and other portable devices have increased, and so has the use of voice- assisted chatbots such comparable to Alexa, Apple's Siri, and Google's Voice Assistant. As simple as these voice assistants are, they are very helpful in easing users’ day-to-day tasks. Now as the use of artificial intelligence (AI) based chatbots such as ChatGPT, Bard and Microsoft Bing have started to be progressively used more and more to get assistance with increasingly complicated tasks, there is a need for a chatbot that is both artificial intelligence-based and has the option to provide voice assistance. In order to realize this, need we have developed a web application that integrates both, an AI- large language model constructed using the GPT-3.5 Generative Pre-trained Transformer. model and voice assistance. The application takes in an input in the form of audio clip and converts it into text, sends the query to the GPT-3.5 model and receives the response in text form and converts that to an audio clip.

BRAIN-CONTROLLED CARS FOR THE DISABLED USING ARTIFICIAL INTELLIGENCE

Jisna JaisonT, Priyanka E Thambi, Nikita Pinheiro,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This paper describes the need for disabled individuals to have a more comprehensive comprehension of brain-controlled automobiles and AI applications. The advantages of brain-controlled automobiles, their application for the disabled, and a related theory have been discussed. The document comprises information regarding the research participants, methods of data collection, and other relevant details. It is evident that brain-controlled vehicles equipped with artificial intelligence are highly beneficial and appropriate for individuals with disabilities. The primary objective of the research is to validate the precision of the data that is predominantly linked to it.

Design and Analysis of Photonic Crystal Based Hexagonal Ring Resonator for Pressure Sensing Application

Ranjitha Krishna R, Santhosh Kumar K B, Indira Bahaddur, P C Srikanth,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Two-Dimensional Photonic Crystal (2DPC) is used in the creation of a pressure sensor; the sensor is created utilizing a hexagonal ring resonator. The functional properties of the suggested sensor are examined, including its resonance wavelength, Q factor, normalized output power, sensitivity, and dynamic range. The sensor consists of a hexagonal ring resonator and two quasi-waveguides made of photonic crystal. Generally, an increase in applied pressure results in a linear rise in the corresponding refractive index. On the other hand, the resonant wavelength of a PC-based sensor is displaced with each increase in refractive index. The PC-based pressure sensor is created and analyzed using the idea.

Exploring the Impact of Obstacles on Job Satisfaction Among Female Gig Economy Workers: A Comprehensive Investigation Utilizing AI and Mechanical Learning Technologies

Lakshmidevi.R, Dr.A.Geetha,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This study delves into the intricate relationship between job satisfaction and obstacles faced by women in the gig economy. Employing advanced AI and Mechanical Learning Technologies, our investigation provides a comprehensive explo- ration of the challenges encountered by female gig workers. By analyzing diverse data sets, we aim to unravel the nuanced dynamics influencing job satisfaction, shedding light on the unique experiences of women in this evolving work landscape. The findings from this research contribute valuable insights for both policymakers and industry stakeholders, fostering a deeper understanding of the factors shaping the professional contentment of female gig economy workers.

The IoT Security Conundrum: A Detailed Exploration of Emerging Threats

Vinay T. Patil, Dr. Shailesh S. Deore,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

While New technologies are becoming a need in our day-to-day lives. The IoT leads these technologies. We can access most things. need at any time, from anywhere, thanks to the Internet of Things (IoT).. These gadgets are able to communicate with one another, gather data, and trade it. Despite significant progress in certain domains, there are still significant challenges in controlling and Internet of Things devices and data protection gather. Finding vulnerabilities in IoT devices, implementing suitable security measures, and evaluating Security risks are necessary to protect IoT devices and data. Artificial intelligence is increasingly being used to detect and stop cyberattacks. Analysis of Palm Tree Disease Prediction Using Artificial Intelligent Techniques

A comparative analysis of AI techniques for fraud detection in financial transactions using Logistic Regression algorithm and Random forest algorithms.

Gunawan Widjaja, RADHA.T , Dr. Rupam Soni , Dr Kuldip Sharma, Ms.E.Devashree , Dr. Natrayan L ,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

With annual costs in the billions of dollars, fraud is a significant issue in the banking sector. Artificial intelligence (AI) systems may identify fraud in financial transactions by identifying patterns that point to it. Two popular techniques for AI fraud detection are random forests and logistic regression. This study compares the efficacy of random forests with logistic regression for the identification of financial transaction fraud. We assess the performance of the two techniques using a collection of real-world financial transactions that have been categorized as either legitimate or fraudulent using a variety of criteria, such as recall, accuracy, precision, and F1 score. Our results show that random forests outperform logistic regression in the detection of fraud in financial transactions. Random Forest accuracy was reached. Our results show that random forests outperform logistic regression for financial transaction fraud detection. Random forests had a 99.5% accuracy rate compared to 98.5% for logistic regression. Random forests also showed better recall and accuracy than logistic regression. These results suggest that random forests are a better option than logistic regression for financial transaction fraud detection. Index Terms: data analytics, random forest algorithms, logistic recursion algorithms, machine learning, and fraud detection

The Impact of Artificial Intelligence Methods on Agricultural Systems: An Examination of Progress in Palm Tree Disease Prediction

M.Soujanya, Dr.E. Aravind, M.Soujanya,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Investigating a range of computer science methodologies, this study investigates the domain of AI-powered palm tree disease prediction. The study evaluates the efficacy of artificial intelligence methods in forecasting and averting maladies in palm trees, thereby making a valuable contribution to the enhancement of agricultural systems. A crucial sector of the Indian economy, agriculture satisfies the demands of an expanding populace. Podiatric maladies in palm trees, which result in significant financial losses, are difficult to detect because of their concealed symptoms. At this time,

An efficient method for predicting a consumer behavior using logistic regression algorithm and apriori algorithm

Lekshmi Mohan, Monisha Devarajan, , Dr. Firas Jamil Alotoum, Dr.Majdi , Kdv Prasad, Dr. Natrayan L,

Year: 2022 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Predicting consumer behavior is a crucial step in the process of doing a business analysis and developing a strategy. Machine learning has being used to forecast customer behavior as AI technology has advanced. This paper introduced novel method for consumer prediction using Logistic algorithm and Apriorist Algorithm. We use Machine learning algorithms for best ac- curacy and prediction. This research paper aims to identify the most efficient algorithm in terms of for consumer prediction. The performance was analyzed for large data set.


International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

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