Medical information contains a great deal of personal data and is quite sensitive to privacy concerns. Given the increasing volume of information in the healthcare sector, medical data must be appropriately and safely kept in this big data era. However, sharing current medical information can be risky and challenging because of the potential for privacy violations. To solve these issues, this study proposes a blockchain framework-based storage solution for healthcare information security along with attribute-based access control. The concept uses attribute-based access management to enable dynamic and granular access to medical data, which can be made secure and impenetrable before being stored in the blockchain system by creating related crypto contracts. Moreover, IPFS technology is incorporated into this solution to ease the blockchain's storage burden. Experiments demonstrate that the suggested system in this study, which combines Demonstrations reveal that the scheme proposed in this paperwork on the combination of access control of attributes and blockchain technology will not only takes care of the storage and uprightness of medical data but also have more productivity while accessing the medical information.

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Nanomaterial-based biosensors have emerged as a revolutionary approach to detecting biological and chemical analytes, offering unparalleled sensitivity, selectivity, and versatility. This study explores the integration of advanced nanomaterials, such as graphene, carbon nanotubes, and metal nanoparticles, into biosensor technologies. Employing theoretical modeling techniques, including Density Functional Theory (DFT), the research elucidates the interaction mechanisms between nanomaterials and target analytes, providing critical insights into adsorption energy, charge transfer, and electronic structure modifications. The experimental phase synthesizes and characterizes nanomaterials, focusing on optimizing their structural, chemical, and electronic properties for biosensing applications. These materials are incorporated into electrochemical, optical, and field-effect transistor (FET) sensor platforms, demonstrating enhanced performance metrics, including ultra-low detection limits, rapid response times, and exceptional specificity. Applications span healthcare diagnostics, environmental monitoring, and food safety, addressing pressing global challenges such as disease detection, pollutant monitoring, and quality control. The study highlights the scalability and reproducibility of nanomaterial-based biosensors and discusses integration with emerging technologies like artificial intelligence for real-time data analysis. This work establishes a comprehensive framework for designing next-generation biosensors, leveraging the unique properties of nanomaterials to achieve breakthroughs in sensitivity, miniaturization, and multifunctionality.

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This paper presents the cloud computing environment setup without any prior experience with the cloud. It provides a good understanding of concepts like virtualization, Kubernetes, Databases and Compute Engines it also discusses what future studies on this topic could be done and what the scope of growth in this field so that researchers can contribute to cloud computing and finds a new innovative way to do things. Beyond the technical setup, this paper explores the potential for future research and growth in the cloud computing field. With the rapid evolution of cloud technologies, there are numerous opportunities for researchers to innovate and develop new solutions. This paper aims to inspire further investigation into the potential of cloud computing, highlighting areas where contributions can lead to breakthroughs and novel approaches that enhance the efficiency, security, and scalability of cloud services. Result section presents the comparison of cloud service providers, their services, and models.

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Earthquake considerations are vital in the design of every structure. Many researchers have reported research works aiming to understand the impact of structures with various irregularities. This study focuses on the behavior of structures with irregularities and compares G+20 models of regular and irregular structures. The response spectrum analysis method is used for analysis, and all structures are assumed to be in Zone V with medium soil type. The ground motion data of the El-Centro earthquake in 1940 is used for the study. The analysis is conducted using the Etabs software. The study examines the structures' responses to ground motion in terms of story displacement, story drift, and base shear. The responses of each type of building are studied and compared. The results indicate that ground motions with low-frequency content have a significant impact on both regular and irregular reinforced concrete structures. It is observed that irregularly shaped structures lead to an increase in displacement, drift, story acceleration, time-period, and member forces, while reducing the base shear. This study suggests that when planning for earthquakes, irregularly shaped structures require extra attention to avoid further losses.

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This paper focuses on controlling a stepper motor using infrared (IR) signals transmitted through an IR remote. The entire system is managed by the 8-bit microcontroller AT89S52. The system operates within a range of up to 10 meters. The microcontroller receives the IR signal from the transmitter, processes it, and uses it to control the motor's movement. A stepper motor is an electromechanical device that converts electrical pulses into discrete mechanical movements. The motor's shaft rotates in fixed increments when the proper sequence of electrical pulses is applied. The rotation direction of the motor is determined by the pulse sequence, while the speed is controlled by the frequency of the pulses. The motor's rotation length is determined by the number of pulses sent.

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This abstract provides an overview of the methodology and significance of sentiment analysis in regard to WhatsApp discussions. Finding out more about the overall tone of WhatsApp conversations is the aim. This analysis has applications in a wide range of domains, including public opinion analysis, brand reputation management, market research, and even mental health monitoring. The project finds commonly used phrases and emojis, creates word clouds, analyzes user behavior over time, computes response times, and extracts useful information using a variety of data pretreatment and analysis approaches. Sentiment analysis is often used to determine the emotional tone of discussions. In this abstract, we review several methods and tools for sentiment analysis of WhatsApp Chat, such as feature extraction and text pre-processing. Additionally, we highlight the challenges and limitations of sentiment analysis on WhatsApp, including the inability to understand idioms and cultural irritants.

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Information about the past has always been simple to get, which means it has been stolen. Intellectual property rights are one place where old and new scientific facts can come together. It's important to know that TRIPS don't accept or support traditional knowledge. There is a "sui generis" scheme phrase in the TRIPS text. This is the case because their views are based on very different culture and social norms. To keep indigenous information safe, a method should be used that is both unique and tailored to the needs of the area. The one-of-a-kind model has some good points, but it doesn't have a good way to share those points and include common information, just like the IP tools in TRIPS. Having something is the main reason to protect your IPR. It's the point of this paper to show that Traditional information can't be protected by IPR laws since it's general information that wasn't created by a single person but by many. People in the developing world are very worried about patents being given for ideas that aren't really new and are based on things that people there already know. It also says that the main problem with Patent by Traditional Knowledge is that there aren't enough complete records that all patent offices can use. Researchers have found that it's not always clear who owns knowledge systems that are passed down from one generation to the next or that come from group work. This is one of the main issues with putting traditional information under patent. People often tell each other traditional stories, so the information isn't always new or clear. Over time, it changes to fit new needs and goals. This is why Patents haven't worked well for societies that have been around for a long time. This paper talks about more than just biopiracy and biomedicines. It also talks about what the Indian government has done to make things better.

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The presence of heavy metals such as arsenic, cadmium, and lead in wastewater poses significant environmental and health risks. This study explores the effectiveness of iron-impregnated activated carbon (Fe-AC) as an adsorbent for the removal of these toxic contaminants from synthetic wastewater. The preparation of Fe-AC involved impregnating activated carbon with iron salts, resulting in a highly efficient adsorbent with enhanced adsorption capacities. Batch experiments were conducted to investigate the effects of various parameters, including adsorbent dose, contact time, and pH, on the removal efficiency of arsenic, cadmium, and lead ions. The results indicated that optimal conditions for heavy metal removal were achieved at specific adsorbent doses and contact times, revealing Fe-AC's potential for significant arsenic, cadmium, and lead reduction from wastewater. Characterization of the adsorbent demonstrated a stable and uniform distribution of iron, contributing to high adsorption efficacy. The experimental data closely followed the Langmuir isotherm and pseudo second-order kinetics, confirming the suitability of Fe-AC for wastewater treatment. This research highlights the potential of using low-cost, iron-impregnated agricultural waste-derived activated carbon as an effective and sustainable solution for addressing heavy metal contamination in aqueous environments, thereby providing insights into practical applications for industrial effluent management and environmental remediation strategies.

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The project titled "Gesture Recognition and Virtual Control with Voice Assistance Bot using AI" aims to revolutionize human-computer interaction by creating a system that allows users to control devices using hand gestures and voice commands. This innovative approach enhances usability by eliminating the need for physical contact with traditional input devices, offering a more intuitive, seamless, and hygienic experience. The system leverages advanced AI techniques to recognize specific hand gestures and interpret voice commands, translating them into corresponding actions on digital devices. By integrating gesture recognition with a voice-assisted bot, the project enables users to interact with smart devices and applications more naturally, enhancing accessibility and convenience. The system's AI algorithms are designed to learn and adapt to different users' gestures and speech patterns, ensuring accuracy and responsiveness. Additionally, this technology holds potential applications in various fields such as home automation, healthcare, and entertainment, where touchless control is advantageous. Overall, the project contributes to the ongoing evolution of human-machine interaction, reducing reliance on physical devices while improving efficiency and inclusivity.

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Solid waste management in India represents a significant challenge owing to rapid urbanization, a burgeoning population, and insufficient waste management infrastructure. This paper explores the current state of solid waste management in India, its environmental impact, and the various technological, policy, and community-based solutions that have been proposed to mitigate the crisis. Through a review of existing literature, government initiatives, and case studies, this research aims to highlight both the obstacles and opportunities within India's waste management framework.

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