ISSN : 2583-2646
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Smart Traffic Management System Using IoTS. Duraipandi, R. Divyadharshini, M. Janani, P. Samyuktha
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The increasing number of vehicles on roads has led to traffic congestion and delays, which have become a significant problem in many urban areas. This study proposes an IoT-based traffic density updation system using IR sensors and controlling traffic signal timing based on density. The system aims to provide real-time traffic density information to traffic management authorities and optimize traffic flow by controlling traffic signal timings.
APPLICATION OF SYSTEMS THINKING FOR INNOVATION USING CONVENTIONAL TOOLSDr. Julia Taylor
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Implementing the use of systems thinking for innovation in organizations, especially large established organizations, is difficult. Too often efforts at implementation end up being too linear and limited in scope and do not really take advantage of systems thinking. This paper describes a theoretical process that attempts to embed systems thinking, so that broader scopes of considerations are included.
ANALYSIS OF VARIOUS TECHNIQUES AND METHODOLOGIES FOR HEART DISEASE PREDICTION A REVIEW Rajendra L.Gaike,
Dr. Vandana Malode
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One of the most important organs for the normal operation of our body is the heart. A WHO investigation revealed that cardiovascular diseases consistently account for 31% of deaths worldwide (CVDs). Additionally, low- and middle-income nations like India account for more than 75% of these deaths. Predicting whether or whether CVDs will occur inside a mortal body is the key challenge.
Differential Transformation in Numerical Study: A Case Study Differentiability Equation Jyoti V Dighole, Mangal P Kale
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Differential equations play a crucial role in understanding many events in technology and generation. Transformation techniques are one of the numerical approaches that mathematicians have devised to provide a numerical solution of differential equations with the least amount of error. There is currently no transformation method that claims to solve the supplied differential equations numerically or accurately without error.
An Analysis of the Privacy and Security Related Problem with Social Networks Saptarshi Kumar Sarkar, Amitava Podder, Piyal Roy
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Social networking is becoming more and more important as a result of the development in online communication over the last few years. Computer network operation, information flow patterns in societies, and emergent behaviour of physical and biological systems can all be studied using social network analysis. Social networks are now widely used, which has made it simpler for people to communicate with one another and share data online.
Implementation of Smart Online Shopping Application for Idhaya Hostellers Jansi Sophia Mary C, Harinitha J, Bhuvneshwari M
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Smart Online Shopping Application for Idhaya hostellers is a web-based application. The students of Idhaya Engineering College for Women, who belong to the Entrepreneurship Development Cell (EDC) are running Idhaya Hostel Canteen. In order to develop the Entrepreneur mindset, the interested students join and run the canteen. Stationery items, Toilet things, Costumes, Snacks, Fresh Juice and Food items are sold in the canteen.
An AC-DC Interleaved ZCS-PWM Boost Converter with Reduced Auxiliary for High-Voltage EV Battery Systems A.Mathavan,
K.Gokulraj
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This work presents a novel approach for the design of a single-stage AC/DC isolated adaptive-network-based fuzzy inference system (ANFIS) controller for board chargers in electric vehicles (EVs) with high-voltage (HV) battery systems. The proposed converter utilizes a modular stacked switches structure with interleaved control, combining modular interleaved bridgeless AC/DC boost converters and modular CLL resonant circuits.
Health-Care Recommender System Using Collaborative Filtering Algorithm Ubani Chinyere, Mark Uvietesiri, Syvester Akhetuamen,
Morgan Obi
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Presently, there are thousands of hospitals offering several types of services to patients. It becomes challenging for a patient to make an informed decision on which hospital to visit for treatment for a particular ailment. Recommender systems have been used in diverse areas to solve the problem of decision making by providing several options for users based on certain attributes of the user that are similar to that of other users with similar attributes.
Smart Electricity Demand Forcasting by Using Improved LSTM Algorithm H. Jeyalakshmi, M. Mariammal
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Demand forcasting, which concerns the estimation of future electricity demand, is needed for the operation and management of power systems. Effective Electricity demand forecasting can relieve the conflict between power supply and demand. Furthermore, effective load forecasting can improve the efficiency of power stations and ensure the safety of the grid.
IoT Based Air Pollution Monitoring System Dr. Jayasundar S A, A.Yashwini, I.Sneka
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Our day-to-day activities and quality of life are impacted by air pollution. It threatens the planet's ecosystem and standard of living. Due to increased industrial activity in recent years, the urgent need to monitor air quality is very obvious. People need to be aware of how much their activities affect the quality of the air.
5G and AI-Driven Process Control: Digital Transformation Boosting Agility and Effectiveness in Supply Chains,
Manufacturing Systems & Telehealth Delivery Sharda Kumari, Viraj Lele, Deepak Singh, Dhruval Shah
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The Fourth Industrial Revolution has initiated a digital transformation, marked by the integration of 5G, Artificial Intelligence (AI), and the Internet of Things (IoT). This paper investigates the potential of 5G and AI-driven remote process control to revolutionize manufacturing systems, enhancing their agility and effectiveness.
An Efficient FIR filter Design Technique using Graphical Interface Nutan V. Bansode, Hemant L. Jadhav
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Spectrum analysis using digital filters is crucial for both signal and picture processing. In this article, all sorts of FIR responses are generated as well as analyzed using windowing techniques. Based on the provided criteria, a window is chosen, and the filter's properties are studied. The design of a FIR filter is described in the second part of this work, which also shows how to put it into practice by simulating it on the MATLAB GUI platform using various windowing strategies for different orders of filter.
Study of the Cryogenic Treatment For Different Cutting tools S. R. Rathoda1, N. V. Kalyankarb2, Y. M. Khanc, S. S. Tarwaded
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Nowadays, cryogenic treatment of materials used in cutting devices is well recognised as a correlative procedure used to improve the material's mechanical and physical properties. For various grades of hardware preparations and tungsten carbide embeds, reports have been made regarding improvements in wear resistance, sturdiness, break obstruction, expanded hardness, improved warm conductivity, lower synthetic corruption, and fantastic remaining pressure condition.
KNN Model for Cancer Prediction Using Stem Cells P. Mahalakshmi, P. Sangeetha, G. Harikrishnaveni, C. Dhivya
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To develop a method for detecting and identifying the type of cancer using the k-nearest neighbor (KNN) algorithm. The KNN algorithm is a simple machine learning algorithm that classifies [1]-[3] an input sample based on the majority of its nearest neighbor in the training data. The KNN algorithm is trained on a large dataset of cancer patients and their corresponding diagnosis, and is then used to predict the type of cancer for a new patient based on their clinical and laboratory test results.
Recent Trends of Artificial Intelligence in the Internet of Things Amitava Podder, Shyamalendu Paul
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The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is rapidly transforming various industries and enabling innovative applications. In recent years, several trends have emerged in the application of AI in the IoT, including edge computing for real-time analysis, predictive maintenance, intelligent automation, smart homes and cities, and security.
Real-Time Decision Making in Wealth Management: The Role of AI and Predictive AnalyticsHitesh P. Rai, Uday Padyana, Gireesh Patil
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In the dynamic landscape of wealth management, real-time decision-making is paramount for maximizing investment returns and minimizing risks. This paper explores the transformative role of artificial intelligence (AI) and predictive analytics in enhancing real-time decision- making processes within the financial sector. By leveraging vast datasets and advanced algorithms, AI-driven systems provide unprecedented insights and forecasts, enabling wealth managers to make informed decisions with greater speed and accuracy.
Smart Semiconductor Wafer Inspection Systems: Integrating AI for Increased EfficiencyJyothi Swaroop Arlagadda Narasimharaju
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The semiconductor industry has received the pressure of the need to develop techniques for higher efficiency and accuracy of wafer inspection processes. It has been a problem to inspect the complexity of the semiconductor wafers with traditional inspection systems and therefore sophisticated solution is required. This paper looks at the evaluation of Artificial Intelligent (AI) in semiconductor wafer inspection systems to improve the outcome.
Zero Trust Identity and Access Management (IAM) in Multi-Cloud EnvironmentsHariprasad Sivaraman
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With multi-cloud strategies being adopted globally, managing identity and access across cloud platforms is a problem that can longer be ignored. The single environment Identity and Access Management (IAM) solutions can hardly enforce the same policy (consistency) and the inter-cloud/gen interoperability between clouds or agility in complex threats landscapes, and are non-multi cloud (non-support). This research paper presents a Zero Trust IAM model designed for multi-cloud ecosystems, with identity verification, unified governance, continuous authentication in Watchful Security Zones (WSZs), and micro-segmentation to break identities up into separate segments that can be isolated.
Cross-Functional Team Dynamics and Their Impact on Product Development and Market SuccessFaiz Mohiuddin Mulla
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As a result, businesses are demanding more and more multi-channel marketing campaigns to meet customers where they're at in this digital-filled world. Only through a decent, data-oriented analysis and evaluation can it be known if such campaigns are successful. A viable examination of the viability of a multi-funnel advertising effort is one such illustrative at last sought-after view that can be acquired by and large utilizing various devices. It focuses on how businesses can use approaches like A/B tests, attribution models, and sophisticated analytics platforms to analyze campaign performance across multiple touchpoints, including social media, email, search engines, or websites.
Investigating the Impact of Linguistic Errors of Prompts on LLM AccuracyPraneeth Vadlapati
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Large Language Models (LLMs), such as GPT-3.5, have demonstrated exceptional abilities in processing text by understanding and generating text. Language models are trained on diverse data, which is typically free of linguistic errors such as spelling and grammatical mistakes. However, in real-world scenarios, the queries from the users commonly include linguistic errors. This research systematically examines the robustness of LLM in handling uncommon linguistic errors. The study utilizes original error-free text, text with errors in spelling, and text with errors in grammar.
AI-Powered Secure Software Development: The Future of Safe and Efficient CodingNitesh Upadhyaya
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Generative AI tools like GitHub Copilot are transforming software development by providing intelligent code assistance, enhancing developer productivity, and introducing innovative approaches to secure software development. This paper explores the role of generative AI in improving secure coding practices and reducing vulnerabilities in software. It examines how AI-powered coding tools assist developers in adhering to security standards, detecting and mitigating potential vulnerabilities, and fostering secure development practices. The analysis highlights the benefits of integrating generative AI into the Secure Software Development Lifecycle (SSDLC), such as automated code suggestions, real-time feedback on potential security issues, and adherence to secure coding patterns.
Enhancing Agile Software Development through Behavior-Driven Development: Improving Requirement Clarity, Collaboration,
and Automated TestingMohnish Neelapu
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Behavior-Driven Development (BDD) has become an Agile software development technique of choice for closing the communication gap between technical and non-technical stakeholders. This research tries to investigate the effects of BDD on Agile teams by analyzing its value in quality of software, efficiency of testing, and clarity of requirements. Empirical evidence is sought from collaboration, automation, and removal of ambiguity in software requirements. Surveys, interviews, case studies, and comparative experiments were qualitative and quantitative methods used in the research to form success factors, challenges, and best practices of the BDD implementation.
Diversity, Equity, and Inclusion Analytics in HR: How Workday Enables Data-Driven Decision-MakingHonie Kali
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As part of the quickly changing business environment, Diversity, Equity, and Inclusion (DEI) have turned out to be strategic things for Human Resource (HR) management, moving beyond parity with, however at the same time, essential drivers of organizational accomplishment and the survive. In this paper, they examine the critical role data-driven decision-making plays in advancing DEI efforts in the organization, specifically what Workday provides as a Human Capital Management (HCM) platform. As a result of integrated DEI analytics, Workday’s tools give human resource professionals access to the centralized collection, storage and analysis of employee data so they can draw actionable insights about employee demographics, pay equity, hiring practices, and promotion trends.