Category Archives: Uncategorized

Authors: Dr.Mukesh Verma, Prof.Amandeep Kaur, Prof.Jasleen Kaur, Prof.Amneet Kaur

Abstract: Have you observed the rapid pace at which technology is evolving around us? One moment, the focus is on mobile applications, and the next, it’s all about artificial intelligence. If you are deeply involved in this field, particularly as a product manager, you are aware that AI is revolutionizing businesses more swiftly than one can utter the phrase "artificial intelligence." But what implications does this hold for you and your position? Let us explore how product management has progressed and why it is essential to adapt to AI-driven transformations in order to remain relevant and lead effectively.The transformation of creative ideas into actual innovations is a central issue in creativity and innovation management (Van de Ven, 1986; Sarooghi et al, 2015). Scholars have often assumed the existence of a relationship between creativity and innovation, arguing that creative individuals are more likely to innovate (Baron & Tang, 2011; Plsek, 1997; Soroa, Balluerka, Hommel, & Aritzeta, 2015). Nonetheless, many creative ideas, although original, don’t find a place in the market. While some other extremely valuable ideas are never implemented. Situations such as these suggest that the path from creativity to innovation is not (always) a straight line. Cognition plays an essential role in the whole process of innovation, as entrepreneur’s ability to innovate is shaped by the their perception and interpretation of external world (Barbosa, 2014; Mullins & Forlani, 2005). From this cognitive perspective, we propose a theoretical model that elucidates how and when individuals are capable of transforming creative ideas into implemented innovation. To do so we built on a definition of innovation as a process that encompasses: the generation of novel ideas, their evaluation and their implementation in the business world (Baer, 2012). We explore how cognitive factors influences each stage of the process and how their interaction may increase the chances that an individual implements a creative idea. This framework offers potentially valuable new insights to both academics wishing to understand deeper the process of innovation in entrepreneurs and practitioners working to assist entrepreneurs in their effort to create innovative ventures.

Published by: vikaspatanker

Authors: Subanila V

Abstract: Speech Emotion Recognition (SER) plays a crucial role in enhancing human-computer interaction by enabling machines to understand and respond to human emotions. In this study, we propose a lightweight and efficient SER model that integrates Random Forest and Multi-layer Perceptron (MLP) classifiers within a VGGNet framework. Unlike traditional deep learning models that require extensive computational resources and hyper-parameter tuning, our approach optimizes performance while significantly reducing complexity. We extracted Mel Frequency Cepstral Coefficient (MFCC) features from three widely-used speech emotion datasets—TESS, EMODB, and RAVDESS—covering 6 to 8 distinct emotions including Sad, Angry, Happy, Surprise, Neutral, Disgust, Fear, and Calm. The proposed model achieved remarkable accuracy rates of 100%, 96%, and 86.25% on the TESS, EMODB, and RAVDESS datasets, respectively. These results indicate superior or comparable performance to state-of-the-art deep learning architectures such as InceptionV3, ResNet, MobileNetV2, and DenseNet, while maintaining lower computational demands. Our findings demonstrate that the hybrid lightweight model effectively balances resource efficiency and emotion recognition accuracy, making it well-suited for deployment on resource-constrained devices without compromising performance.

Published by: vikaspatanker

Authors: Mrs. B. Kavitha, Dr. V. Senthil Kumar

Abstract: Public libraries play a crucial role in establishing the foundations of democracy and contribute to the welfare and growth of the societies they serve. They assist in achieving the goals of the community. A public library is a temple of learning, and its services are vital for raising awareness and empowering society, particularly for disadvantaged and marginalized groups. One of the primary functions of public libraries is the dissemination of information, especially regarding environmental knowledge and protection. Information technology significantly enhances public awareness in this area. Currently, the global environment faces significant threats from pollution resulting from various human activities essential for livelihoods and other needs. It is essential for the entire population of India—and indeed the world—to be aware of the provisions of the Environment Protection Act of 1986, in order to ensure a safe life and provide a healthy environment for future generations. Awareness camps conducted at public libraries aim to help social groups and individuals gain understanding about environmental protection. This paper highlights the importance of environmental awareness and presents findings from a sample survey conducted at the Central City Library in Chikkadapalli, Hyderabad. A questionnaire was used as a survey tool to collect data on users' responses and satisfaction levels regarding their awareness of environmental pollution. The analysis reveals that many respondents at the Central City Library feel a lack of awareness about environmental protection. The survey results also illustrate the benefits of promoting environmental protection through awareness campaigns at public libraries

DOI: http://doi.org/10.5281/zenodo.17433063

Published by: vikaspatanker

Authors: Mrs. M. Deepthi, Jannu Sahithi, P. Vikhyath Reddy, Polapally Srinidhi

Abstract: In the era of wireless communication, the demand for compact and high-performance antenna with ultra-wideband capabilities has been increased, particularly in 5G and Internet of Things (IoT) applications. This paper presents the design, simulation, and comparative analysis of novel Multiple Input Multiple Output (MIMO) antenna structures- Circular, Hexagonal and Hybrid of both patch configurations. The primary objective is to develop a compact MIMO antenna with low mutual coupling, wide bandwidth, improved gain and directivity. Advanced hybrid techniques and ground plane modifications were employed to improve the performance. Simulation and optimization were conducted using Ansys HFSS, with a focus on key performance metrices such as S-parameters, radiation pattern and gain. The hybrid MIMO antenna structure demonstrated superior results in terms of isolation, directivity, and bandwidth offering a promising solution for UWB applications in future wireless technologies.

Published by: vikaspatanker

Authors: Miss . Chilantharajula Tejasri, Dr. K.Venkata Rao

Abstract: The opioid crisis, a pressing global public health issue, has led to a significant rise in overdose deaths, particularly among individuals under 50, with profound social and economic impacts. This study proposes a comprehensive forecasting system to predict drug use and overdose trends by integrating diverse data sources, including police reports, social network data, medical records, and sewage-based drug epidemiology. Utilizing Recurrent Neural Networks (RNNs), the system aims to identify individuals at risk of opioid abuse by analysing demographic information, medical histories, and prescription records, while distinguishing between therapeutic and harmful usage. Emphasizing privacy protection, ethical data handling, and model interpretability, this approach seeks to enhance the accuracy and timeliness of overdose risk predictions. The findings have the potential to inform clinical decision-making, shape public health policies, and drive targeted interventions to mitigate the opioid epidemic.

DOI: https://doi.org/10.5281/zenodo.17430579

Published by: vikaspatanker

Authors: Shamli Gaikwad, Dixsha Wasnik, Stuti Tripathi, Shubhangi Rahangdale, Prof. Pooja H. Rane

Abstract: A web-based interactive platform called The Virtual Herbal Garden was created to close the knowledge gap between conventional medical procedures and contemporary digital accessibility. The platform, which has its roots in the AYUSH (Ayurveda, Yoga & Naturopathy, Unani, Siddha, and Homeopathy) healthcare system, uses multimedia integration, 3D visualization, AI chatbot support, and sharing and bookmarking tools to educate users about medicinal plants.This study describes how the project was developed and put into use utilizing cutting-edge web technologies like React.js, MongoDB, and APIs like Sketchfab and OpenAI. One major gap in the current digital herbal databases, according to the research, is the absence of easily accessible, interactive, and multilingual resources. To overcome these obstacles, an agile development methodology and user-centered design were applied.Improved user engagement, efficient plant discovery using search and filters, and improved instruction through interactive features are some of the main outcomes. Future improvements are suggested, such as mobile apps, AR integration, and AI-driven plant identification, while limitations like internet dependence and content scope are examined. In the end, this project shows how technology can be used to support natural health education, preserve indigenous knowledge, and stimulate interest in sustainable, traditional healing methods.

Published by: vikaspatanker

Authors: Ali Akbar, Komal Sarwar

Abstract: Heavy metals, prevalent in various environmental matrices due to industrial and agricultural activities, pose significant health risks, including the promotion of cancer through the induction of oxidative stress. This paper reviews the mechanisms by which heavy metals such as arsenic, cadmium, chromium, and lead contribute to oxidative stress, leading to cellular damage and cancer development. We explore the complex interplay between heavy metal exposure, oxidative stress, and the activation of key signaling pathways involved in carcinogenesis. Understanding these mechanisms is crucial for developing effective strategies to mitigate the health impacts of heavy metal exposure and improve cancer prevention efforts.

DOI: https://doi.org/10.5281/zenodo.17424408

Published by: vikaspatanker

Authors: S.Gayathri, Dr.S.Siva Ranjani, Dr.B.Lalitha

Abstract: This project presents an AI-based thermographic weld joint inspection system designed to automatically detect defects in weld joints using deep learning models, specifically Convolutional Neural Networks (CNN) and the YOLO (You Only Look Once) object detection algorithm. By leveraging thermographic imaging, which captures the thermal profile of welded joints, this system aims to identify inconsistencies and anomalies indicative of defects such as cracks, porosity, and lack of fusion. The proposed approach utilizes CNN for image classification to determine whether a weld is defective or not, while YOLO is employed for precise localization and detection of defects within the thermographic images. The dataset comprises labeled thermographic images of weld joints, preprocessed and augmented to enhance model performance. The CNN model is trained to distinguish between defective and non-defective welds, achieving high classification accuracy. Simultaneously, YOLO is trained to detect multiple types of defects in real-time with high precision and recall. The combination of CNN and YOLO ensures both robust classification and efficient object detection. Evaluation metrics such as accuracy, F1-score, mean Average Precision (mAP), and Intersection over Union (IoU) are used to assess model performance. Experimental results demonstrate the effectiveness of deep learning in automating weld inspection, reducing human error, and increasing inspection speed. The system is scalable and adaptable to various welding processes and materials. Deployment of this AI solution can significantly improve quality assurance in manufacturing.

Published by: vikaspatanker

Authors: Abeshin Ayodele

Abstract: The integration of Artificial Intelligence (AI) is transforming strategic operations across global industries, yet its impact on multi-channel distribution networks particularly in complex sectors like heating, ventilation, and air conditioning (HVAC) remains underexplored. This study explains a theoretical framework for understanding the strategic implications of AI integration within the multi-channel networks of multinational HVAC manufacturers. The traditional HVAC distribution network comprising direct sales, retailers, contractors, digital platforms and third-party service providers; has been characterized by manual processes and legacy systems. AI's emergence introduces predictive analytics, automated CRM systems, intelligent routing, and real-time data integration that collectively shift how firms manage and interact with their channel partners. These changes, while beneficial, raise critical challenges such as channel conflict, role redundancy, partner resistance, and uneven digital maturity across regions. Thus, there is a pressing need for a structured theoretical framework that captures the complexity and strategic relevance of AI’s role in reshaping these networks. To address this gap, the study draws on four complementary theoretical lenses: the Resource-Based View (RBV), Actor-Network Theory (ANT), Technology- Organization-Environment (TOE) framework, and Diffusion of Innovation (DOI) theory. The RBV positions AI as a valuable, rare, and inimitable resource that, when aligned with internal capabilities and existing assets, can provide a sustainable competitive advantage through differentiated channel management strategies. ANT broadens this view by conceptualizing AI not just as a technological tool but as an active agent within the distribution network. It highlights how human and non-human actors (e.g., AI systems, managers, distributors) negotiate roles and power relations, co-creating new channel configurations and organizational behaviors. The TOE framework provides a holistic understanding of how technological, organizational, and environmental factors interact to influence AI adoption. It explains how firms' internal readiness, market pressures, and regulatory environments shape the pace and depth of AI integration within channel strategies. Finally, the DOI theory offers insights into the diffusion process of AI across channel partners, emphasizing how adoption is influenced by the perceived attributes of AI technologies and the social systems through which innovation spreads. It identifies early adopters within the network and highlights strategies to accelerate diffusion through communication, training, and observable results. Together, these theoretical perspectives present a robust framework for examining the strategic transformation of multi-channel networks in the HVAC industry due to AI. The study contributes to scholarly understanding of digital transformation in B2B networks while offering practical guidance for HVAC manufacturers aiming to align AI capabilities with channel strategy

DOI: https://doi.org/10.5281/zenodo.17414506

Published by: vikaspatanker

Authors: Arun Prabhu S, Dr. chetan V Hiremath

Abstract: Kerala, known as the “Spice Garden of India,” plays a vital role in India’s spice trade, with Small and Medium Enterprises (SMEs) forming the backbone of the sector. However, these SMEs face significant sustainability challenges due to climate variability, market volatility, certification hurdles, and infrastructural limitations. This study aims to analyze the key risk factors affecting the supply chains of Kerala’s spice SMEs and their impact on sustainable supply chain performance (SSCP). Using a structured questionnaire and descriptive analysis, the study identifies five major risk dimensions—climate and environmental risks, market price volatility, certification and regulatory compliance, financial constraints, and logistics and infrastructure gaps. Findings reveal that climate and environmental risks and price volatility negatively influence SSCP, while certification and compliance contribute positively. Financial and infrastructural challenges show limited but notable effects on resilience. The study concludes that effective risk management, improved access to finance, climate adaptation training, and sustainable practice adoption are essential for enhancing supply chain resilience and competitiveness. Recommendations include establishing price stabilization mechanisms, upgrading infrastructure, and promoting sustainability certifications. The research offers valuable insights for policymakers and SMEs to strengthen Kerala’s spice supply chain against sustainability risks.

Published by: vikaspatanker