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Research Paper

Build an Amazon Connect call center

The purpose of this paper is to investigate how Amazon Connect and Amazon Lex may be integrated to create a state-of-the-art customer contact center system that will enhance customer service operations. The study entails a thorough analysis of the advantages, disadvantages, and best practices related to establishing a customer contact center with Amazon Connect and Amazon Lex in terms of technology. It contains case studies, a summary of pertinent research, and helpful implementation advice. Significant advantages of the Amazon Connect and Amazon Lex connection include enhanced productivity, Scalability, cost-effectiveness, and personalized customer experiences. Nevertheless, there are obstacles including complicated chatbot training and regulatory compliance. To solve these issues, solutions and practical implementation insights are given. The conclusions are also supported by prior research and real-world experiences. Businesses may use the information in this paper to improve customer service operations by putting Amazon Connect and Amazon Lex into practice as part of a contemporary contact center solution. The useful advice and best practices provided can aid in resolving issues and maximizing the advantages of this integration, eventually enhancing general client happiness and loyalty

Published by: Ismail Emad Sakerde, Khan Mohammed Umer, Rathod Mihir Visabhai, Reena Kothari

Author: Ismail Emad Sakerde

Paper ID: V10I2-1159

Paper Status: published

Published: April 19, 2024

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Research Paper

Multi-scale Deep Learning for Histopathological Image Analysis: The Deep-Hipo Approach

The digitization of whole-slide imaging within digital pathology has propelled the advancement of computer-assisted tissue examination utilizing machine learning methodologies, particularly convolutional neural networks (CNNs). Numerous CNN-based approaches have been proposed to effectively analyze histopathological images for tasks such as cancer detection, risk prediction, and cancer subtype classification. While many existing methods have relied on patch-based examination due to the immense size of histopathological images, such small window patches often lack sufficient information or patterns for the tasks at hand. Pathologists routinely inspect tissues at various magnification levels to scrutinize complex morphological patterns through microscopes. In response to these challenges, we propose a novel deep-learning model for histopathology, named Deep-Hipo, which concurrently utilizes multi-scale patches for precise histopathological image analysis. Deep-Hipo simultaneously extracts two patches of identical size from both high and low magnification levels, enabling the capture of intricate morphological patterns within both large and small receptive fields of a whole-slide image.

Published by: Keerthana M., Dr. Y. Md. Riyazuddin

Author: Keerthana M.

Paper ID: V10I2-1146

Paper Status: published

Published: April 19, 2024

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Research Paper

Role of Consumer Psychology in Sales and Marketing

This paper examines the role of consumer psychology in sales and marketing in the contemporary context. It is essential to understand the hows and whys of consumer decisions, and factors that influence their buying behavior and their purchasing patterns. This is critical knowledge to understand the target audience to develop effective marketing strategies for optimum sales and revenue. The existing market is highly competitive and the key players need to know how to create the right product for the right consumers. Insights into and perceptions of consumer psychology enable the designing of an effective marketing strategy to attract consumers, designing, and producing new products. This is a crucial skill and knowledge for successful sales and marketing.

Published by: Ishaan Sagar

Author: Ishaan Sagar

Paper ID: V10I2-1157

Paper Status: published

Published: April 19, 2024

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Research Paper

3D Dense CNN for Hyperspectral Imaging-Based Bloodstain Classification

Blood is a crucial piece of evidence in forensic science for reconstructing and solving crimes. Although numerous chemical procedures are utilized to recognize the blood at a crime scene, these various chemical-based methods might affect DNA analysis. One potential application of bloodstain detection and classification using hyperspectral imaging (HSI) is in forensic science for crime scene investigation. In this paper, we developed a deep learning classifier 2D CNN, 3D CNN and Dense for blood stain detection in the field of forensic science. We conduct experiments using a publicly available Hyperspectral-based Bloodstain dataset for experimental and validation purposes. This dataset contains a variety of chemicals, including blood and blood-like compounds such as ketchup, artificial blood, beetroot juice, poster paint, tomato concentrate, acrylic paint, and questionable blood. With the initial training/testing ratio set to 90/10 of the data samples, we compare the results with state-of-the-art three different CNN architecture with PCA, as preprocessing techniques. The result demonstrates that the 3D Dense CNN can offer improved classification accuracies, smoother classification maps, and more discriminable features for hyperspectral image classification.

Published by: Tejaskumar B. Sheth, Dr. Milind S.Shah

Author: Tejaskumar B. Sheth

Paper ID: V10I2-1150

Paper Status: published

Published: April 16, 2024

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Research Paper

Buyer’s Perception of Starbucks

This document provides an analysis of the buyer's perception of Starbucks, a leading global coffeehouse chain. The study aims to understand the factors influencing consumers' perceptions of Starbucks and their preferences regarding its products and services. Utilizing a mixed-methods approach, including surveys and interviews, data was collected from a diverse sample of Starbucks customers across different demographics and locations. Key findings reveal that Starbucks customers perceive the brand positively, associating it with quality, convenience, and a welcoming atmosphere. The analysis delves into the factors driving these perceptions, such as product quality, customer service, brand image, and social responsibility initiatives. Additionally, the study explores the impact of factors like pricing, competition, and cultural influences on consumer perceptions and purchasing behavior. Implications of the findings suggest opportunities for Starbucks to further enhance customer satisfaction and loyalty through targeted marketing strategies, product innovation, and community engagement initiatives. The document concludes with recommendations for Starbucks and other businesses in the coffee industry to leverage consumer perceptions effectively and maintain competitive advantage in the market

Published by: Yerravelli Nikhil Moses, Dr. Y. Md. Riyazuddin

Author: Yerravelli Nikhil Moses

Paper ID: V10I2-1147

Paper Status: published

Published: April 16, 2024

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Research Paper

Optimizing Government Grants for Startups: Encouraging Growth of Technology Startups Within the U.S. Entrepreneurial Ecosystem

The entrepreneurial landscape in the United States thrives on innovation, with tech startups playing a pivotal role in driving change and economic expansion. This article explores the symbiotic relationship between government grants and technology startups, examining the impact, challenges, and evolution of grant programs in fostering innovation. Beginning with a historical overview, it traces the trajectory of government support, highlighting milestones such as the Small Business Innovation Research (SBIR) program and legislative reforms. Through a comprehensive literature review, it evaluates the multifaceted impact of government grants on startup ecosystems, encompassing economic effects, innovation output, and spillover impacts. Moreover, it delves into the challenges faced by startups, including funding constraints, regulatory complexities, and market entry barriers, emphasizing the need for sector-specific tailoring of grant programs. The article concludes with an evaluation framework that scrutinizes procedural efficacy, outcome metrics, sector-specificity, and long-term sustainability, providing insights into enhancing the effectiveness of government grant initiatives for fostering technological innovation.

Published by: Ibukunoluwa Okunnuga, Prah Maame Korkor, Folorunsho O. Fatai, Njoku K. Tochukwu, Adeboye O. Elisha

Author: Ibukunoluwa Okunnuga

Paper ID: V10I1-1304

Paper Status: published

Published: April 16, 2024

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