Browse
Recent Submissions
Item Scope of big data in healthcare analysis(NHCE, 2023) MANOJ S M 1NH21MC048Health care analysis using big data has revolutionized the way information is collected, analyzed, and utilized in the health care industry. The vast amount of data generated from electronic health records, wearable devices, and other sources has opened new possibilities for improving patient outcomes and optimizing health care processes. Big data analytics techniques, such as data mining, machine learning, and natural language processing, are employed to explore patterns, trends, and correlations within massive datasets. These insights enable health care providers and researchers to make informed decisions, enhance clinical decision-making, and personalize patient care. Moreover, big data analytics plays a crucial role in population health management. By analyzing large-scale datasets, health care organizations can identify public health trends, predict disease outbreaks, and allocate resources effectively. This facilitates the implementation of targeted interventions, health promotion campaigns, and preventive measures to improve population health outcomes. Additionally, big data analytics contributes to the optimization of health care operations and cost management. By analyzing data related to resource utilization, patient flow, and billing, providers can identify inefficiencies, streamline processes, and reduce costs. Fraud detection algorithms can also be employed to ensure accurate billing and reimbursement.Item Multimedia based content protection system using cloud technology(NHCE, 2023) SHARANYA A 1NZ19MCA25Anonymous fingerprint has been suggested as a convenient solution for the legal distribution of multimedia contents with copyright protection whilst preserving the privacy of buyers, whose identities are only revealed in case of illegal re-distribution. However, most of the existing anonymous fingerprinting protocols are impractical for two main reasons: • the use of complex time-consuming protocols and/or homomorphic encryption of the content. • a unicast approach for distribution that does not scale for a large number of buyers. This paper stems from a previous proposal of recombined fingerprints which overcomes some of these drawbacks. However, the recombined fingerprint approach requires a complex graph search for traitor tracing, which needs the participation of other buyers, and honest proxies in its P2P distribution scenario. This paper focuses on removing these disadvantages resulting in an efficient, scalable, privacy-preserving and P2P-based fingerprinting system.Item Software data reduction for effective bug triage(NHCE, 2023) SARATH C MURALI 1NH21MC120Software problems cost software businesses more than 45 percent of their revenue. Bug triage is an unavoidable stage in the bug-fixing process, and it seeks to accurately allocate a developer to a new problem. Text categorization algorithms are used to conduct automatic bug triage to reduce the time cost of manual labor. We address the topic of data reduction for bug triage in this work, i.e., how to minimize the scale and increase the quality of bug data. We integrate instance and feature selection to minimize data size on both the bug and word dimensions at the same time. We gather variables from prior bug data sets and develop a prediction model for a new bug data set to decide the sequence of applying instance selection and feature selection. We empirically analyze data reduction efficiency on 600,000 bug reports from two big open-source projects, Eclipse and Mozilla. The findings suggest that our data reduction may efficiently reduce the data size while improving bug triage accuracy. Our study proposes a method for utilizing data processing techniques to generate reduced and high-quality bug data in software development and maintenance.Item Access control system using nucleus and hid reader(NHCE, 2023) PRAJWAL G C 1NH21MC119This project report presents a comprehensive study on access control systems implemented in a company using RFID technology. The objective of the project was to enhance security and monitor employee access within the company premises. The system utilizes sensors to collect data from each access card, which is then transmitted to dedicated controllers known as V1000. Each V1000 controller is capable of configuring and managing access for two doors. To efficiently manage and analyze the collected data, an application named HR View was employed. The HR View application interacts with the V1000 controllers through the HR View API, allowing seamless integration and real-time access control management. Additionally, a new version of the REST API was implemented to develop a bespoke application called Nuclues, which acts as an interface for administrators to configure access rights, monitor access logs, and generate relevant reports. The project report highlights the design and implementation of the access control system, detailing the integration of the RFID sensors, V1000 controllers, HR View application, and the Nuclues application. The report delves into the technical aspects of the system, including the hardware and software components utilized. Moreover, it describes the protocols, APIs, and communication channels employed to ensure smooth data flow and system operationItem Authorized redundant check support in a hybrid cloud environment(NHCE, 2023) ATHIRA M V 1NH21MC118Cloud computing promises to increase the rapidness of application deployment and delivery. Authorized Data De-duplication in cloud computing deals with elimination of excessive usage storage space due to duplicated data and providing privacy for user's .Each authorized user will get an individual token to access their file in the cloud and can perform duplicate check based on the privileges. Authorized user is able to use his/her own private keys to generate query and hence attributes are attached along with the file. Attributes are found in the private cloud; so, control immediately passes to the private cloud, where duplicate check can be performed. Data stored in the public cloud is accessed only by the authorized users with the help of different individual encryption privilege keys. Convergent and Symmetric encryption techniques produce identical cipher text that results in minimum overhead. Proof of reliability assures a verifier via an acknowledgment that a user's file is available.Item Detect andriod malware using multiple linear regression models(NHCE, 2023) ABHISHEK S 1NH21MC117The objective of this internship project is to analyze and predict a framework for Android malware detection based on permissions is presented. This framework uses multiple linear regression methods. Application permissions, which are one of the most critical building blocks in the security of the Android operating system, are extracted through static analysis, and security analyzes of applications are carried out with machine learning techniques. Based on the multiple linear regression techniques, two classifiers are proposed for permission-based Android malware detection. These classifiers are compared on four different datasets with basic machine learning techniques such as support vector machine, k-nearest neighbor, Naive Bayes, and decision trees. In addition, using the bagging method, which is one of the ensemble learning, different classifiers are created, and the classification performance is increased. As a result, remarkable performances are obtained with classification algorithms based on linear regression models without the need for very complex classification algorithms. This paper proposes and investigates a parallel machine learning based classification approach for early detection of Android malware. Using real malware samples and benign applications, a composite classification model is developed from parallel combination of heterogeneous classifiers. The empirical evaluation of the model under different combination schemes demonstrates its efficacy and potential to improve detection accuracy. More importantly, by utilizing several classifiers with diverse characteristics, their strengths can be harnessed not only for enhanced Android malware detection but also quicker white box analysis by means of the more interpretable constituent classifiers.Item A fullstack ecommerce app built in react(NHCE, 2023) VARATHALAMBEDU RAKESH 1NH21MC116Software problems cost software businesses more than 45 percent of their revenue. Bug triage is an unavoidable stage in the bug fixing process, and it seeks to accurately allocate a developer to a new problem. Text categorization algorithms are used to conduct automatic bug triage to reduce the time cost of manual labor. We address the topic of data reduction for bug triage in this work, i.e., how to minimize the scale and increase the quality of bug data. We integrate instance and feature selection to minimize data size on both the bug and word dimensions at the same time. We gather variables from prior bug data sets and develop a prediction model for a new bug data set to decide the sequence of applying instance selection and feature selection. We empirically analyze data reduction efficiency on 600,000 bug reports from two big open-source projects, Eclipse and Mozilla. The findings suggest that our data reduction may efficiently reduce the data size while improving bug triage accuracy. Our study proposes a method for utilizing data processing techniques to generate reduced and high-quality bug data in software development and maintenance.Item Data Visualization Using Blue Prism and Power Bi(NHCE, 2023) SINGH NAVNIT DHIRENDRA 1NH21MC115This project aims to automate the data processing and reporting workflow using Blue Prism, SQL, and Power BI. The project involves extracting data using Blue Prism, storing it in a SQL database, transferring it to a specific server, and generating reports that will be visualized in Power BI. The project begins with the identification of data sources and the development of Blue Prism workflows to extract, clean, and transform the data. The processed data is then stored in a SQL database, where appropriate tables and relationships are created using SQL queries and stored procedures. Next, the data is transferred from the SQL database to a designated server using SQL commands or other suitable methods. Error handling and data validation checks are implemented during the transfer process to ensure the integrity of the data. Once the data is successfully transferred, reports are generated in Power BI by connecting it to the SQL database. Interactive dashboards and reports are designed and developed in Power BI, leveraging its visualization capabilities to provide meaningful insights. Users can explore and analyze the data effectively using filters, slicers, and drill-down options. Automation and scheduling are set up in Blue Prism to initiate the data extraction, processing, and transfer tasks at specific intervals. Power BI is configured to automatically refresh the data from the SQL database, ensuring the reports and dashboards are always up to date. Thorough testing and validation are conducted to ensure data accuracy and integrity throughout the workflow. Training is provided to end-users on how to interpret and utilize the generated reports and dashboards in Power BI. By implementing this project, the organization achieves automated data processing, efficient data transfer, and insightful reporting in Power BI. This enables real-time data visualization and empowers data-driven decision-making based on accurate and up-to-date information.Item Understanding consumer behavior through adobe analytics(2023) SERENE MATHEW 1NH21MC114Adobe Analytics is a toolset that helps small or big businesses understand how people interact with their digital platforms, such as websites or mobile apps. It collects data about user actions, such as page views, clicks, or form submissions, and provides valuable insights into user behavior. By implementing Adobe Analytics, businesses can track and measure various metrics that are important for their success, such as conversion rates, engagement levels, or the effectiveness of marketing campaigns. This data can be used to make informed decisions, improve user experiences, and optimize business strategies. The implementation process involves installing a small code on the digital platform, defining what actions to track, and configuring variables and metrics that capture specific information about user interactions. Rules can be set up to ensure data accuracy and relevance. Once implemented, the tool collects and processes the data, allowing businesses to access reports and visualizations that provide valuable insights. Adobe Analytics implementation enables businesses to gather and analyze data about user behavior, which indicates them make to data-driven decisions to improve their digital platforms and achieve their goals.Item Reliable access under dual provenance for public storage cloud(NHCE, 2023) HARISH KUMAR P 1NH21MC113In public cloud storage systems, data access control is a difficult problem to solve. A promising method known as Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has been developed to offer flexible, fine-grained, and secure data access control for cloud storage with honest but sceptic cloud servers. A CP-ABE method is used in a large-scale cloud storage system, however because the sole attribute authority in existing CP-ABE schemes is required to carry out the cumbersome user legitimacy verification and secret key distribution, this results in a single-point performance bottleneck. Users might spend a lengthy time waiting in queue to get their secret keys, which would reduce the system's efficiency. Despite the fact that multiauthority access control systems have been put forth, they are still limited by the single-point bottleneck and their low efficiency since each authority still handles a disjoint attribute set individually. In this research, we provide a brand-new heterogeneous framework to solve the single-point performance bottleneck issue and to offer a more effective access control system with an auditing mechanism. To distribute the workload of user authenticity verification, our architecture makes use of various attribute authorities. In the meanwhile, a CA (Central Authority) is added to our system to create secret keys for users whose validity has been established. In contrast to existing multiauthority access control techniques, our scheme gives each authority unique control over the whole collection of attributes. In order to increase security, we also provide a technique for identifying which AAs (Attribute Authorities) carried out the validity verification process deceptively or wrongly. Analysis reveals that our solution significantly improves key generation performance while simultaneously guaranteeing the security requirements.Item Prediction of h1n1 vaccination(NHCE, 2023) DEVA MAHESH 1NH21MC112The objective of this internship project is to analyze and predict vaccination rates based on historical data and relevant factors. By examining past vaccination campaigns and understanding the impact of various factors, this project aims to provide insights into potential vaccination trends for outbreaks. This research will utilize historical data on vaccination campaigns, including vaccination counts, demographic information, and relevant epidemiological factors. The analysis will involve exploring the relationships between vaccination rates and factors such as the prevalence and severity of the virus, vaccine availability and accessibility, public awareness campaigns, and the effectiveness of vaccines. By examining the historical context and patterns, this project will develop predictive models to estimate future vaccination rates. Machine learning algorithms will be employed to identify significant predictors and forecast vaccination counts based on various scenarios. Furthermore, this research will delve into understanding vaccine hesitancy and its potential influence on vaccination rates. By exploring reasons behind vaccine hesitancy and examining successful strategies employed in previous campaigns, this project aims to provide recommendations for addressing hesitancy and improving vaccination uptake. The outcomes of this internship project will contribute to the field of public health and inform policymakers, health organizations, and community leaders about potential vaccination trends for outbreaks. The results will also provide insights into effective strategies for boosting vaccination rates and addressing vaccine hesitancy, thereby enhancing public health response efforts and preparedness for future outbreaks. Note: It is essential to consult with supervisors, experts in public health, or epidemiology to ensure the accuracy and relevance of the analysis and findings.Item Intelligent automation testing(2023) CHANDAN HP 1NH21MC111Nowadays, number of software has been implemented as web-based application, those application are very complex, it is very difficult to test such complex web application. Before any Web application or software is made available to generic public, it goes through a process called Testing. It checks for security, compatibility, functionality and performance of the software or web application. Automation testing uses automation tool to reduce human intervention and repeatable tasks. In this project I have designed and implemented automation testing framework for testing web application. This automation testing has been implemented using selenium Web Driver tool. With the help of this framework, testers may quickly and effectively write their test cases. This framework produces the customized test report. it’s very easy to maintain and repair the test suite for new release of the application using this framework. In this project I have done automation testing on “E commerce” application. E commerce is an, online retailer, manufacture of electronic book renders, and web service provider that became the iconic example of electronic e commerce. E commerce application is vast internet-based enterprise the sells books, music, movies, house wares, electronics, toys, and many other goods. This project tests the application by prototyping tool for building test scripts by using Selenium tool. Selenium Web driver is a prototyping tool for building test script.Item Drug classification using state of the art ml algo(NHCE, 2023) BASTTY PREM 1NH21MC110Drug classification plays a crucial role in the field of pharmaceutical research, drug discovery, and healthcare management. Traditionally, drug classification has relied on manual inspection and expert knowledge, which can be time-consuming and prone to human error. With the advancements in machine learning algorithms and the availability of large-scale drug data, automated drug classification using state-of-the-art ML algorithms has emerged as a promising approach. This research aims to explore the application of state-of-the-art machine learning algorithms for drug classification. We begin by compiling a comprehensive dataset consisting of various drug properties, such as chemical structure, molecular descriptors, and biological activity. The dataset encompasses a wide range of drugs belonging to different therapeutic classes. We then apply and compare several state- of-the-art machine learning algorithms for drug classification. These algorithms include but are not limited to random forest, support vector machines (SVM), convolutional neural networks (CNN), and recurrent neural networks (RNN). We utilize various feature engineering techniques to extract relevant features from the dataset and optimize the performance of the models. To evaluate the effectiveness of the ML algorithms, we employ metrics such as accuracy, precision, recall, and F1 score. We also conduct cross-validation experiments to assess the models' robustness and generalizability. Furthermore, we compare the performance of the ML algorithms with traditional manual classification methods to showcase the advantages of automated drug classification.Item Driving Business Intelligence: Azure SQL Database Collaboration for Visual Analytics Driving Business Intelligence: Azure SQL Database Collaboration for Visual Analytics(NHCE, 2023) Yuvraj Kaswan 1NH21MC109This study investigates the collaborative utilization of Azure SQL Database and Power BI for driving business intelligence through visual analytics. Azure SQL Database provides a scalable and secure cloud-based platform for storing and managing business data, while Power BI offers powerful data visualization and analysis capabilities. By integrating these two technologies, organizations can enhance their business intelligence capabilities and gain valuable insights from their data. This abstract explores the benefits and challenges of leveraging Azure SQL Database and Power BI in a collaborative setting for visual analytics. The study examines case studies, implementation strategies, and best practices to demonstrate the potential impact of this collaboration on driving business intelligence. The findings highlight the effectiveness of combining Azure SQL Database and Power BI in enabling data-driven decision-making and improving business performance. This research contributes to the growing body of knowledge on business intelligence and provides practical insights for organizations seeking to leverage Azure SQL Database and Power BI for visual analytics. Azure SQL Database offers a robust and scalable cloud-based platform for storing and managing business data, while Power BI provides advanced visualization and analytics capabilities. By integrating these technologies, organizations can leverage the power of data to gain valuable insights and make informed business decisions. This study examines the benefits, challenges, and implementation strategies associated with utilizing Azure SQL Database and Power BI in a collaborative manner for visual analytics. Through the analysis of case studies and best practices, the research showcases the potential impact of this collaboration on enhancing business intelligence. The findings emphasize the effectiveness of Azure SQL Database and Power BI in enabling data-driven decision-making, improving operational efficiency, and identifying business opportunities. This research contributes to the existing body of knowledge on business intelligence and provides practical insights for organizations seeking to harness the potential of Azure SQL Database and Power BI for visual analytics to drive their business success.Item Intelligent enhanced employee Performance evaluator(NHCE, 2023) YANADANNAGARI SWAPNA 1NH21MC108This project aims to explore the impact of monetary incentives on employee performance in the workplace. Monetary incentives, such as bonuses, commissions, and performance-based pay, have long been used as a means to motivate employees and improve their performance. However, there is a need to understand how different types of monetary incentives influence employee behavior, job satisfaction, and overall productivity. Through an extensive review of existing literature and conducting surveys and interviews with employees, this project seeks to provide insights into the effectiveness of monetary incentives and offer recommendations for organizations to enhance employee performance.The purpose of this research is to determine the relationship between monetary incentives and their impact on employee performance the essence or purpose is also to confirm that monetary incentives are good motivational tool for employee performance in a society like ours where the cost of living is very high employees are a priceless asset when it comes to achieving the company’s goals and to ensure that all employees are on deck,they need to be motivated and inspired because one of the tools that management uses to motivate inspired employees is incentives Thematic analysis of the role of monetary incentives to enhance employee performance is described critically in this particular study paper. This report clarifies the aim of this research paper to understand about monetary incentive system in the area of the competitive business market, the major responsibilities of the incentive process enhancing the power of employee performance, the process to increase business productivity through financial rewards, and important tool orprocess to analysis positive effect of employee incentive method in the business market, authentic data and information to relate with business improvement through the effect of monetary incentive process and finding future scope or more opportunities to provide a safe platform for the employee. This analysis study focuses on all those areast o clarify importance to provide employee incentives to achieve the best performance as well as business productivity. incentives and how they are linked to employee motivation, influencing emerging economies. This study addresses two gaps as outlined in previous studies.Item Q&A hub-usingmern stack(NHCE, 2023) Vinayak D 1Nh21MC107The "Q&A Hub-Using MERN Stack" project aims to develop a comprehensive question and answer platform using the MERN (MongoDB, Expressis, React is. Node is) stack. The system provides a user-friendly interface for users to ask questions, receive answers, and engage i discussions on various topics, The project involves the integration of several technologies and framewodes to build a robust and scalable web application. The MERN stack is chosen for im flexibuitry, efficiency, and of use in developing modern web applications. MongoDB is used as the database to share and mmage user data, questions, and answers Express is handles the server-side logic and API development, while Nodejs provides the runtime environment The frontend of the application is built using React is, a popular JavaScript library fir bolding user interfaces. React.js allows for the creation of reusable components, ensuring a modular and efficient development process. The frontend interacts with the backend through RESTfal APIs, enabling seamless data exchange between the client and the server The key features of the Q&A Hub include user registration and authentication, creating and editing questions, providing answers, upvoting and dowuvating answers, and comment functionalities. The platform also includes a search functionality, allowing users to easily find relevant questions and answers based on keywords or tags. Throughout the development process, best practices in software engineering, such as version control with Git and collaborative development, were followed. The project emphasizes the use of clem code, efficient algorithms, and responsive design principles to provide an optimal user experience across vadous devices In conclusion, the Q&A Hub-Using MERN Stack project showcases the implementation of a feature-rich question and answer platform using the MERN stack. The project demonstrates the effective utilization of the MERN technologies, along with best practices in software development, to create a robust and scalable web applicationItem Sofie bot – rapid awareness(NHCE, 2023) VIKASH KUMAR 1NH21MC106The Sofie BOT - Rapid Awareness project is aimed at developing a bot on top of the Microsoft Teams platform to enhance cybersecurity awareness among employees in corporate organizations. The project addresses the critical need for proactive measures to combat cyber threats and keep employees informed about emerging security risks. The existing systems for disseminating cybersecurity information often lack real-time alerts and personalized content delivery. Therefore, the objective of this project is to design and implement a bot that can effectively send alerts related to cybersecurity threats and provide up-to-date information about new threats in the market. The proposed system, the Sofie BOT - Rapid Awareness, utilizes Microsoft Teams as the communication platform and incorporates features such as real-time alerts, personalized content recommendations, and reporting and analytics capabilities.Item Bot to Copy Data from Excel to Database(NHCE, 2023) VIKSAH KUMAR 1NH21MC105Automating the process of transferring data from Excel spreadsheets to databases in the context of web development. It highlights the limitations of manual data entry and emphasizes the need for a more efficient and reliable solution. The report explores the advantages of using a bot or automation script to perform this task, including time-saving benefits, improved accuracy, scalability, and enhanced overall efficiency. By automating the data transfer process, developers can dedicate more time to critical tasks while reducing the risk of human errors. The report outlines the step-by-step process involved in building a bot for copying data from Excel to a database, covering aspects such as environment setup, programming language and framework selection, and the implementation of necessary functionalities. It emphasizes how automation enables developers to handle large datasets seamlessly, ensuring consistent and error-free data migration. Ultimately, the adoption of automation in data transfer contributes to the optimization of web development projects, resulting in improved productivity and streamlined workflows. Manual data entry is time-consuming and prone to errors, making it inefficient for large datasets. The report discusses the benefits of using a bot or automation script for this task, including time-saving, accuracy, scalability, and efficiency. It outlines the process of building a bot to copy data from Excel to a database, which involves preparing the development environment and implementing the necessary steps. Automating data transfer not only streamlines the workflow but also ensures the accuracy and reliability of the migrated data, ultimately improving the efficiency of web development projects.Item Online voting system(NHCE, 2023) VARSHITHA A 1NH21MC104The word “vote” means to choose from list ,elect or to determine.The main goal of voting in a scenario involving the citizens of a given country is to come up with leaders of people’s choice.Most countries have problems when it comes to voting.Some of the problems involved include rigging votes during election,insecure or inaccessible polling stations,inadequate polling materials and also inexperienced personnel. This online voting/polling system seeks to solve the above issue.It should be noted that with this system in place,the users,citizens in this case shall be given ample time during voting period.This type of voting system will increase voter turnout because of convenience.Item Azure sql database integration for powerful power bi reports(NHCE, 2023) VARMA NITIN SHIVANANDJI 1NH21MC103In the modern business landscape, data-driven insights play a crucial role in decision-making processes. To harness the full potential of data, organizations rely on robust analytics and reporting tools. Microsoft Power BI has emerged as a leading business intelligence platform, enabling users to create interactive reports and dashboards. However, the effectiveness of Power BI reports heavily relies on the underlying data source. This abstract focuses on the integration of Azure SQL Database with Power BI to enable the creation of powerful reports. Azure SQL Database, a fully managed cloud database service by Microsoft Azure, offers a scalable and efficient solution for data storage and management. By integrating Azure SQL Database with Power BI, users gain numerous benefits for developing impactful reports. This integration facilitates seamless data connectivity, allowing Power BI to directly query and retrieve data from Azure SQL Database. Real-time data updates and dynamic connections ensure that reports always reflect the latest information. The integration of Azure SQL Database and Power BI unlocks advanced querying and modeling capabilities. Users can leverage the rich SQL querying capabilities of Azure SQL Database to perform complex calculations, aggregations, and transformations directly within the database. This enhances report performance and enables efficient analysis of large datasets. Another advantage is the scalability and performance offered by Azure SQL Database. With its ability to handle growing data volumes and adapt to changing demands, organizations can confidently scale their database resources based on analytical needs. This ensures that Power BI reports deliver optimal performance even with expanding datasets.