Category Archives: Uncategorized

Authors: Ayush Kumar, Abhendra Pratap Singh, Dr.Uma Gautam, Nandini Sharma

Abstract: Upper limb amputees face significant challenges due to the high cost and limited availability of advanced prosthetic hands. Recent advances in 3D printing, combined with electromyography (EMG) and electrocardiography (ECG) sensing, have enabled the development of affordable, customizable and functionally capable prosthetic devices. This review paper focusses on the current literature on 3d printed bionic hands controlled by EMG and ECG signals, highlighting design strategies, materials, actuations mechanism, and control system. The integration of hybrid bio signals, adaptive algorithms, and additive manufacturing has improved prosthetic performance, responsiveness and user comfort. The review also discusses the role of artificial intelligence and machine learning in enhancing signal processing, gesture recognition, and motion prediction as well as the potential of IoT-enabled monitoring and patient support. Moreover, limitations of current approaches and future directions for more intelligent, reliable and accessible prosthetic solutions are outlined for identification of scope for further advancement in this domain.

DOI: https://doi.org/10.5281/zenodo.17442105

 

Published by: vikaspatanker

Authors: Sidhant Chadha

Abstract: Vision-based object recognition has emerged as a transformative technology in modern retail, revolutionizing how products are identified, tracked, and managed across the supply chain. Leveraging computer vision and deep learning techniques, these systems enable automated product detection, shelf monitoring, customer behavior analysis, and inventory management with high precision and speed. This study explores the design and implementation of vision-based object recognition systems within retail environments, emphasizing the role of convolutional neural networks (CNNs), transfer learning, and real-time image processing frameworks. By integrating cameras, sensors, and AI-driven analytics, retailers can enhance operational efficiency, minimize human error, and provide personalized shopping experiences. The paper also examines challenges such as occlusion, lighting variation, and scalability, along with potential solutions through model optimization and data augmentation. The findings suggest that vision-based recognition systems are key enablers of intelligent retail automation, contributing significantly to the advancement of smart retail ecosystems and Industry 4.0 integration.

DOI: https://doi.org/10.5281/zenodo.17439901

 

Published by: vikaspatanker

Authors: Sarang Vehale, Ruchita Vehale

Abstract: Traditional federated learning (FL) frameworks face critical challenges in privacy, scalability, and auditability when deployed across multiple enterprises with strin- gent regulatory requirements. Quantum-secure protocols such as Quantum Key Distribution (QKD) and post-quantum cryptography can harden communica- tion channels against both classical and emerging quantum attacks. Meanwhile, variational quantum algorithms (VQAs) promise computational speedups for high-dimensional aggregation tasks that become bottlenecks in large-scale FL systems. We propose a hierarchical, multi-tier Quantum-Federated Learning (QFL) architecture in which local enterprises perform classical model training, regional “quantum hubs” execute VQA-accelerated aggregation and anomaly detection, and a global coordinator enforces UN/ISO AI governance via verifiable zero-knowledge proofs (ZKPs). By bounding quantum resource usage to interme- diate nodes and combining QKD on backbone links with lattice-based encryption at the edge, our design achieves near-term implementability, cost-effectiveness, and end-to-end privacy guarantees. Preliminary simulations demonstrate that the proposed scheme reduces communication overhead by over 60% and resists gradient-poisoning attacks with negligible impact on model accuracy. This work lays the foundation for a globally scalable, audit-ready AI governance ecosystem suitable for international deployments

DOI: http://doi.org/10.5281/zenodo.17441935

Published by: vikaspatanker

Authors: Charitidis J. Panagiotis

Abstract: The oil and gas (O&G) industry increasingly requires advanced materials capable of withstanding harsh operating environments such as deepwater, ultra-deepwater, and high-temperature/high-pressure (HTHP) reservoirs. Fibre- reinforced polymer (FRP) composites have already provided benefits in corrosion resistance, weight reduction, and fatigue performance, yet their broader adoption remains limited by challenges such as poor impact resistance and inadequate fire performance. Nanocomposites—polymers reinforced with nanoparticles, including clays, metal oxides, carbon nanotubes, and graphene—offer a pathway to overcoming these limitations. Even at low filler concentrations, they can deliver significant improvements in mechanical strength, thermal stability, fire resistance, and barrier properties, while also enabling new functionalities in drilling fluids, cementing, and enhanced oil recovery (EOR). This review examines the state of nanocomposite research in the O&G sector, evaluates their potential to enhance both structural and fluid applications, and discusses the technical, economic, and regulatory challenges that must be addressed to achieve commercial deployment.

DOI: http://doi.org/10.5281/zenodo.17439618

Published by: vikaspatanker

Authors: Sushanth.Chandrashekar, Shantanu Nagaraj, Ashish Naidu

Abstract: The tender bidding process remains a critical yet inefficient cornerstone of global procurement, plagued by manual document analysis, compliance errors, and resource-intensive workflows. This paper introduces Agentic Graph RAG, an innovative AI system that redefines bid preparation by integrating Retrieval-Augmented Generation (RAG), dynamic knowledge graph and multi-agent collaboration to automate and optimize the end-to-end bidding pipeline. Our architecture combines three transformative pillars: a cognitive document processor, a living knowledge graph, and a specialized agent framework. Validated on real-world tenders, the system demonstrates 98% clause extraction accuracy, 80% faster bid preparation, and a 6.4x ROI through compliance assurance and strategic positioning. This work bridges cutting-edge AI research with practical procurement challenges, offering a scalable blueprint for intelligent automation in competitive bidding.

Published by: vikaspatanker

Authors: Aswin S k, Dr. M Sivaprakash, Linsha Pushparaj, Vinoth M, Dan Abishek A S, Infant Mazhak

Abstract: The global transition toward sustainable mobility has increased interest in electric vehicles (EVs) as alternatives to internal combustion engine–based transportation. This work presents the design, fabrication, and performance evaluation of an electric three-wheeler prototype intended for urban commuting and short-distance goods or passenger transport. The prototype integrates a lightweight chassis, a Brushless DC (BLDC) motor drive, a lithium-ion battery pack, and a basic control system to achieve affordability, reliability, and energy efficiency. The methodology included load analysis, torque and speed requirement estimation, chassis fabrication, motor and controller integration, and testing under real operating conditions. Results demonstrated a top speed of 40 km/h, a load capacity of 300 kg, and an average operational range of 65 km per charge. Compared with conventional three-wheelers, the prototype eliminates fuel costs, reduces maintenance requirements, and achieves zero tailpipe emissions. The findings suggest that electric three-wheelers can provide a sustainable and cost-effective solution for last-mile connectivity and urban transport, especially in developing economies.

DOI: https://doi.org/10.5281/zenodo.17433866

Published by: vikaspatanker

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