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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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Research Paper

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 Sarvaiya

Author: Nayak Himanshukumar Dinanath

Paper ID: V10I3-1136

Paper Status: published

Published: May 2, 2024

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Research Paper

Brain Tumor Classification Leveraging CNNAnd Grad-CAM For Accurate Tumor Type Identification

Brain tumour segmentation in medical image analysis is a challenging task because precision is crucial in the process of diagnosis and treatment. The current research applies a sophisticated method that utilizes Convolutional Neural Networks (CNNs) in conjunction with gradient-weighted Class Activation Mapping (Grad-CAM) to enhance the detection accuracy of brain tumours. By virtue of the implemented complex architecture of EfficientNetB1, our technique shines at solving the complex problems of medical image data processing. Grad-CAM makes a precious input into CNN by supplying visual interpretations of the attention-paying areas of CNN, empowering doctors to make the right diagnoses. We introduce a model that is based on a great number of brain tumour images with confirmed labels and learns to differentiate different tumour types based on their specific patterns. From our comparative analysis, we can see that there is a significant improvement in tumour detection accuracy, with our model reaching even as high as 99.67%. This one is more effective than the VGG16 model that delivers 85%-90% accuracy and ResNet50 model that has 90%-97% accuracy. In particular, the EfficientNetB1 model provides an accuracy range in the interval of 96%-98%, which clearly shows the efficiency of our proposed technique, since this would result in better treatment outcomes for patients.

Published by: Balamurali Besetty, B. Harshitha, A. Chandu, P. Nandini, D. Jayanth, Sreelahari Vallamsetla

Author: Balamurali Besetty

Paper ID: V10I2-1172

Paper Status: published

Published: May 2, 2024

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Research Paper

Smart Agricultural Pesticide Spraying Robo

This paper introduces an autonomous pesticide spraying robot designed for precision agriculture applications. With the escalating demand for sustainable farming practices, the need for efficient pest management solutions has become paramount. The proposed robot employs a combination of advanced technologies, including artificial intelligence, robotics, and sensing capabilities, to optimize pesticide application while minimizing environmental impact. Through real-time data collection and analysis, the robot identifies pest-infested areas and precisely administers the required amount of pesticide, thereby reducing chemical usage and increasing crop yield. Additionally, the robot's autonomous navigation system enables it to manoeuvre through complex terrain with minimal human intervention, enhancing operational efficiency and reducing labor costs. The integration of Internet of Things (IoT) connectivity facilitates remote monitoring and control, allowing farmers to manage spraying operations and receive actionable insights for decision-making remotely. Overall, the autonomous pesticide spraying robot represents a promising solution for sustainable agriculture, offering increased productivity, reduced environmental footprint, and improved crop health.

Published by: Adesh, Nikhil V.S, Pratik Kate, Om Jogdhand

Author: Adesh

Paper ID: V10I2-1169

Paper Status: published

Published: May 2, 2024

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Research Paper

Empowering the Visually Impaired: The Innovative Reader

The intent of this study is to present a new Smart Reader system, to improve accessibility for those with visual impairments. Leveraging the versatile capabilities of Raspberry Pi, the system integrates both hardware and software components to facilitate real-time text recognition and audio output. Its hardware setup comprises a Raspberry Pi microcontroller, a camera module, and audio peripherals, ensuring a portable and efficient design. By employing computer vision techniques, the system extracts text from various textual materials, such as books, documents, and signs, and converts it into sound. Machine learning algorithms contribute to accurate text recognition, while natural language processing ensures coherent audio delivery. Future enhancements may concentrate on bolstering system resilience, broadening language support, and incorporating additional features to cater user requirements.

Published by: Akhilesh N, Harsath Vijayakumar, Nikhil S, Rahul MR, Suhasini

Author: Akhilesh N

Paper ID: V10I2-1174

Paper Status: published

Published: May 1, 2024

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Research Paper

Parent-Adolescent Psychology

This research paper comes to various conclusions about the Parent-Adolescent relationship which has an impact on both the parent and the adolescent in different contexts. This research paper sheds light on the importance of Communication of Adolescents with the family members that is necessary to maintain a Healthy Relationship with the members of the family. This paper talks about Communication and the Circumplex model, the Effects of parent-adolescent relationship, and the effect of parental separation on an adolescent’s well-being. Adolescent sexuality, parent Alcoholism, Adolescent egocentrism identity,parent-adolescent processes, parent personality, and its effects, parent influences on adolescent peer orientation, Family Economic Hardship, Parental Support, and Adolescent self-esteem are also examined. It also talks about Disclosure and Secrecy in parent-adolescent relationships. Various cause and effect factors were also examined.

Published by: Hunar Khanna

Author: Hunar Khanna

Paper ID: V10I2-1167

Paper Status: published

Published: May 1, 2024

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