Volume-10, Issue-3

May-June, 2024

Research Paper

1. Hybrid Approach Involving Deep Learning Techniques for Recognition Facial Emotions Efficiently

Facial emotion recognition holds paramount importance in various human-centric applications, particularly in human-computer interaction (HCI) systems. This paper delves into the realm of machine vision and artificial intelligence (AI) to explore the methodologies and advancements in facial emotion identification. Leveraging computer vision technologies, coupled with AI algorithms, the research focuses on the recognition of human emotions through facial expressions. In human communication, facial expressions serve as a vital channel for conveying emotional states, playing a significant role in interpersonal understanding. Understanding emotions expressed through facial cues aids in effective decision-making and tailored interactions in human-machine interfaces. Emphasizing the relevance of non-verbal communication, this study investigates the significance of facial expressions in conveying emotional nuances. Deep learning techniques, particularly convolutional neural networks (CNNs), have revolutionized facial emotion recognition by enabling end-to-end learning from raw image data. By minimizing reliance on handcrafted features and pre-processing techniques, CNN-based approaches demonstrate superior performance in emotion detection and classification. Researchers have made substantial strides in developing intricate neural network architectures to enhance the accuracy and efficiency of facial emotion recognition systems. Through a comprehensive review of existing literature and methodologies, this research contributes to the ongoing discourse surrounding facial emotion recognition. Insights gleaned from this study pave the way for the continued advancement of HCI systems, facilitating more nuanced and responsive human-machine interactions.

Published by: Nayak Himanshukumar Dinanath, Dr. Ashish SarvaiyaResearch Area: Deep Learning, Facial Expression Recognition

Organisation: Gujarat Technological University, Ahmedabad, GujaratKeywords: Deep Learning, CNN, FERC, AI and SSD

Full Details View PDF Search on Google
Full Details View PDF  Google
Research Paper

2. 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 ShankarResearch Area: Computer Science

Organisation: Scottish High International School, Gurugram, HaryanaKeywords: Artificial Intelligence, Business Growth, Automation, Data Analysis, Innovation

Full Details View PDF Search on Google
Full Details View PDF  Google
Research Paper

3. 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 IsaacResearch Area: Data Science

Organisation: Mar Athanasius College of Engineering, Kothamangalam, KeralaKeywords: Floorplan Recommendation, Autonomous Navigation

Full Details View PDF Search on Google
Full Details View PDF  Google
Research Paper

4. 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. ChanthiniResearch Area: IoT

Organisation: IFET Collage of Engineering, Gangarampalaiyam, Tamil NaduKeywords: Street Light, Real-world Problem, IoT

Full Details View PDF Search on Google
Full Details View PDF  Google
Research Paper

5. 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 KourResearch Area: Computer Science Engineering

Organisation: SRM Institute of Science and Technology, Ghaziabad, Uttar PradeshKeywords: News Classification, Natural Language Processing, Large Language Models, Machine Learning, Text Classification

Full Details View PDF Search on Google
Full Details View PDF  Google
Research Paper

6. 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 CHAKKARAVARTHYResearch Area: Data Science

Organisation: Lincoln University College,MalaysiaKeywords: Forecast, Patterns, Supervised, Economic, Finance, Features, Relationship, Trends

Full Details View PDF Search on Google
Full Details View PDF  Google
Review Paper

7. 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 TandaleResearch Area: Prosthetic Dentistry

Organisation: Government Dental College and Hospital, Aurangabad, MaharashtraKeywords: Dental implants, Abutment, Abutment connection, Implant Abutment

Full Details View PDF Search on Google
Full Details View PDF  Google
Research Paper

8. What are Quantum Computers and Why do we Need them?

Quantum computers represent the forefront of technological advancement, promising revolutionary applications across various fields. This paper explores the fundamental mechanics of quantum computing, the limitations of classical computers, and the superior capabilities of quantum computers. Additionally, it examines practical applications of quantum computing in real-world scenarios. The goal is to provide a comprehensive understanding of why quantum computing is essential for future technological progress and to highlight its potential to transform industries such as agriculture, artificial intelligence, cybersecurity, and finance.

Published by: Aarnav ChhikaraResearch Area: Quantum Computers

Organisation: The British School, New Delhi, IndiaKeywords: Quantum, Quantum Computing, Probability, Possibility, Sycamore, Application, Shor’s algorithm, Classical computers, Data, Cyber Security, Quantum mechanics, Superposition, Quantum entanglement, Quantum Tunneling, AI, Business

Full Details View PDF Search on Google
Full Details View PDF  Google
Research Paper

9. Exploring the Gender Pay Gap in India: Assessing its Implications on Economic Growth and Development

This research aims to look into unequal pay among India’s male and female employees, utilizing information obtained from the National Sample Survey Organization (NSSO) as well as the Labour Bureau Ministry of Labour and Employment Government of India. The main idea is to examine women’s workforce participation in different Indian states between 2006 and 2014 while also comparing wages between men and women doing similar jobs. The study of gender inequality in salaries is important because it hampers economic growth, promotes social injustice, and undermines efforts for gender balance. This thesis will therefore use reliable government sources that have collected large amounts of data to reveal what causes wage imbalances between males and females within Indian labor markets. This inclusion of data covering almost a decade allows for long-term assessment regarding shifts or patterns vis-à-vis female workers’ job rates as well as earnings compared with those earned by their male counterparts. Consequently, through detailed statistical analysis based on various parameters, this investigation intends to find out why the difference in pay exists among different states in India and whether there are any linkages with education levels achieved; types of industries engaged in, or even cultural practices followed within these areas. By shedding light on the magnitude and determinants of the gender pay gap in India, this study aims to inform evidence-based policy interventions aimed at promoting gender equality and fostering inclusive economic development. The findings of this research hold implications not only for policymakers and governmental agencies but also for employers, civil society organizations, and advocacy groups striving to address gender-based disparities in the workplace and promote greater gender parity. This research contributes to the existing body of knowledge on the gender pay gap in India by conducting a rigorous analysis of empirical data collected from reputable sources. By elucidating the complexities of this issue and exploring potential avenues for intervention, this study seeks to advance our understanding of gender inequality in the Indian labor market and advocate for policy measures aimed at achieving greater economic justice and gender equity.

Published by: Punnya SethiResearch Area: Economics. Gender Studies

Organisation: Pathways School Gurgaon Faridabad - Gurgaon Rd, Baliawas, Gurugram, Bandhwari, Haryana, IndiaKeywords: Gender Parity , Equality , Glass Ceiling, Indian Economy

Full Details View PDF Search on Google
Full Details View PDF  Google

Online paper publication is ongoing for the current issue and authors can submit their paper for this issue until Ongoing Submissions.