ISSN : 2583-2646
Unique Method to Detect and Dispose of Seawater Oil LeaksPirithivi C., Solaiyammal K.
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Oil slicks hurt the marine environment and marine presence's endurance. Oil ruins the protection of fur-bearing creatures like ocean otters and the water repellency of birds' quills, presenting them to the components.
Evaluating the Impact: Patient and Provider Satisfaction with EHR Systems in Oncology and the Path to Enhancement
Sarika Mulukuntla, Saigurudatta Pamulaparthyvenkata
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In the landscape of oncology, where the precision and personalization of care are paramount, the role of Electronic Health Records (EHR) systems emerges as both foundational and transformative. This study delves into the heart of oncology care, evaluating the impact of EHR systems through the lens of those it serves most intimately: the patients navigating their cancer journey and the healthcare providers dedicated to their treatment.
Envisioning the Future of Professional Services: ERP, AI, and Project Management in the Age of Digital DisruptionAmit Mangal
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The study explores the impact of digitalization on professional service firms (PSFs) amidst the rise of technologies like ERP, AI, and project management systems. It addresses the need to understand frontline workers' responses to digital disruption in auditing and public relations/communication (PR/C) consulting firms in the USA. By integrating insights from service intelligence, occupational identity, service climate, and frontline service work, the study uncovers nuanced reactions to digitalization.
Natural Refrigerants in the Future of Refrigeration: Strategies for Eco-Friendly Cooling TransitionsAnkitkumar Tejani,
Jyoti Yadav, Vinay Toshniwal, Rashi Kandelwal
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The refrigeration industry is at a new crossroads as it struggles to find a new solution that could be more environmentally friendly, given the current environmental conditions. Such social issues like global warming and depletion of the ozone layer primarily result from synthetic refrigerants largely used by the industry, which place tremendous pressure on it at present. Historical refrigerants such as CFCs and HFCs, although efficient in cooling, are found to have adverse impacts on the environment with considerably large GWP and ODP.
Artificial Intelligence in Cybersecurity: From Automated Threat Hunting to Self-Healing NetworksRahul Gupta
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Artificial Intelligence (AI) is advancing aggressively as a force multiplier in cybersecurity and threatening intelligence. This paper concerns the use of AI in cybersecurity, with a close look at automated threat-hunting and self-healing networks. Automated threat hunting is the action whereby the system looks for threats by itself without the need of the system administrator, and the AI uses machine learning algorithms to analyze data and look for indicators of compromise that could be a sign of an attack. A self-healing network is another type of network that is completely powered by artificial intelligence, making it possible to detect and fix weaknesses on its own and without relying on man’s services.
Enhancing Product Development through Continuous Feedback IntegrationVineela Komandla
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Incorporating feedback is a crucial aspect of developing a successful product that truly meets the needs of its users and aligns with business goals. Regularly gathering input from users, stakeholders, and team members allows for a continuous cycle of improvement, ensuring that the product evolves in response to real-world needs and challenges. By listening to users, companies can identify pain points, discover unexpected use cases, and prioritize features that will make the most impact. Engaging with stakeholders ensures that the product stays on track with the broader business strategy and objectives, preventing misalignment and wasted resources.
Performance Tuning Techniques for Large-Scale Financial Data WarehousesSantosh Kumar Singu
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The Bigger and denser the financial data gets, the more imperative it becomes to have good DW systems to store and analyze data from it. Another data integration issue, which has been recognized as crucial to financial institutions especially, is the ability to formulate large-scale data warehouses for intelligent decision support, reporting, and forecasting. Often, performance tuning of large-scale financial data warehouses requires adjustments to all these software levels and the systems’ hardware and database designs with reference to high availability, scalability, and velocity. In this paper, various performance-tuning strategies that enhance data acquisition, query response, and resource utilization for financial data warehouses are presented.
The Future of Pharmacovigilance: Using Data Science to Predict and Prevent Adverse Drug ReactionsRajesh Munirathnam
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Pharmacovigilance (PV), which is the study of measuring and assessing the adverse effects of drugs, has seen enhancements in the last couple of decades. The conventional systems have mainly incorporated file-based reporting, reactive monitoring, and post-event analysis of ADRs. But with the flood of real-world health information and the emergence of new data analysis methods, pharmacovigilance is going through a shift. New technology tools such as machine learning (ML), artificial intelligence (AI), and other analytical big data tools are powering PV towards a more predictive mode.
Role of AI with Authentication and Authorization for High Throughput ApplicationsSaidaiah Yechuri
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As the use of Artificial Intelligence in various domains continues to grow, there is an increasing need to ensure the trustworthiness and responsible deployment of these systems (Barclay & Abramson, 2021). Trustworthy AI is essential as AI applications become more pervasive and their impact on society becomes more significant. A key aspect of trustworthy AI is the need to identify the roles, requirements, and responsibilities of the various stakeholders involved in the development and deployment of AI systems. With the rapid advancements in artificial intelligence and machine learning, there has been a growing interest in leveraging these technologies for various applications, including security and authentication.
Data Integration in Heterogeneous SystemsNishanth Reddy Mandala
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Integrating data from heterogeneous systems is a critical challenge in modern data management. The increasing diversity of data sources such as relational databases, NoSQL databases, cloud storage, and legacy systems complicates the process of unifying data for analytics, decision-making, and machine learning. This paper reviews key challenges in heterogeneous data integration and explores traditional and modern integration techniques, including ETL, data federation, and data virtualization. We also provide a comparative analysis of these approaches and propose potential solutions to address scalability, real-time access, and schema integration. Case studies and performance evaluation are presented, highlighting real-world applications in healthcare and finance.
Extending Layer 2 Protocols in Metro Networks: A Study of L2PT for Improved Traffic EngineeringAmaresan Venkatesan
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Metro networks have become the backbone of modern communication, connecting various regional networks, data centers, and service providers. While Layer 2 technologies such as Ethernet are widely used for their simplicity and scalability, they often face limitations in terms of management, flexibility, and interconnectivity with various services. To address these challenges, the Layer 2 Protocol Tunneling (L2PT) mechanism offers a solution by enhancing the capabilities of Layer 2 protocols within metro network environments.
The Use of Federated Learning for Digital Advertising MeasurementVarun Chivukula
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Federated learning (FL) allows collaborative model training across decentralized devices or datasets without the need for raw data sharing, preserving user privacy. This paper explores FL's application in randomized control trial (RCT) measurement for digital advertising and other domains, emphasizing privacy-preserving techniques. We present a theoretical framework, demonstrate its implementation, and analyze its advantages, limitations, and recommendations.
The Impact of Real-Time App Activity Signals on Ad Effectiveness in Auction-Based Digital Ad PlatformsVarun Chivukula
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Real-time app activity signals, such as user browsing behavior, product interactions, and transactional events, enable advertisers to personalize and optimize ad delivery in auction-based digital advertising platforms. By incorporating these signals into real-time bidding (RTB) algorithms, advertisers can improve key performance indicators (KPIs) such as click-through rate (CTR), conversion rate, and return on ad spend (ROAS). This paper introduces a formal framework to evaluate the impact of real-time signals, performs quantitative analysis on ad campaigns, and presents actionable insights for advertisers.
Predictive Algorithms for EV Charging: AI Techniques for Battery OptimizationHari Prasad Bhupathi, Srikiran Chinta
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The rapid adoption of Electric Vehicles (EVs) has created a critical need for optimized charging solutions that not only reduce energy costs but also extend battery lifespan. This paper proposes novel predictive algorithms utilizing Artificial Intelligence (AI) techniques to optimize EV charging, focusing on battery life preservation and energy consumption efficiency. Through the integration of machine learning, deep learning, and reinforcement learning, our model forecasts optimal charging times, adapts to dynamic grid conditions, and incorporates real-time data to enhance battery management strategies.
Iot Based Smart Irrigation and Animal Prevention System Using ArduinoSenthil Kumar R, Ambika M, Boomika P, Haritha N, Pavithra R
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The necessity for sharp developing specifically in developing global areas like India has created to a more prominent critical confirmation. furthermore, look at in IoT based distant sensor coordinating agribusiness, for instance, seeing of natural circumstances like temperature, Humidity of enveloping and soil clamminess, etc.
ANN Based Double-T-Type Multilevel Inverter for Renewable Energy ApplicationsDellipriya K, Muniraj R
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As of late, utilization of staggered inverters in high strength applications positively should be visible. inordinate best and lower contortion of the result voltage and low barricading voltage of semiconductor switches are being given as the crucial honors of the staggered inverter contrasted with the conventional voltage supply inverter.
Fuzzy Logic Controller Based Small_Signal Stability Contidion for Inverter-Based Unbalanced Micro GridsRamya Devi R, Balasubramanian T
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The multiplication of inverter-based absolutely innovation and high level detecting, controls, and dispatch framework have worked with the sped up arrangement of miniature matrices.
A Three-Level Isolated fuzzy controlled AC-DC PFC Power Converter Topology with Reduced Number of SwitchesKanimozhi M, Krishnaveni S
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The essential objective of this work is to build an extraordinary failure esteem separated three-degree ac-dc strength converter geography with a decreased wide assortment of switches. existing three-degree converter geographies exchange ac energy to dc strength while saving necessities set by means of worldwide prerequisites for strength transformation
A Deep Learning Model For Brain Tumor Segmentation & Classification Using U-Net & Inception-NetA Deep Learning Model For Brain Tumor Segmentation And Classification Using U-Net & Inception-NetSaranya G, Azhagu kowshik A M, Cibiraj M, Hariharan P, Harish Ramana Kumar G
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Among mind cancers, gliomas are the most typical and forceful, principal to an exceptionally short presence hope of their greatest grade. Thusly, cure making arrangements is a vital stage to upgrade the excellent of presence of oncological patients.
An Efficient Optimized Mppt for Pv System Under Extremely Fast Changing Irradiance –Hybrid Flower Pollination OptimizerAsha Rakshana T , Punitha K
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In final an extended time, renewable energy belongings have gain extra hobby due to the fact the call for of strength is growing. solar energy
Automation Controlling Unit For Seed DrillKalphana KR , Subash Krishna T , Santhosh Kumar V , Praveen Kumar R , Shankar M
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In future agribusiness will resemble shrewd use computerization contraptions. Automation is the creation and utilization of headways to convey and convey work and items with immaterial human mediation.
Model Predictive Controlled Series Resonant Converter for Universal Electric Vehicle ChargerDhanalakshmi G, Krishnaveni S, Kanimozhi M
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Charging groundwork of electric vehicles (EVs) happens to importance these days as the EV market creates. This endeavor presents a Model Predictive Controlled series reverberating
Design of neural controlled boost converter for IoT devicesPalselvam R, Sarathchandran P
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Energy harvested from ambient radio waves and mild may be transformed and saved effectively sufficient to electricity IoT gadgets. . In power-harvesting gadgets, the small quantities of ambient power to be had from reassets which includes motion, self-generated heat, vibration. In power-harvesting gadgets, the small quantities of ambient power to be had from reassets which includes motion, self-generated heat, vibration
Kidney Stone Detection Using Hybrid Butterfly Net and Inception net ModelBuvaneswari R, Vinoth R
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Kidney stones are the to be expected complaint global, incurring numerous people to admit to trauma centers with outrageous agony. different imaging procedures are utilized for the guess of kidney stone ailment.
Artificial Intelligence Based Zone Detection with Vehicle Speed Control SystemShyamala K, Karthikeyan D
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Time is basic in state-of-the-art society; thus, anyone attempts to do commitments fast. to complete the work quick, we need increment the speed, including a vehicle.
A New Droop Controlled Dc-Dc Converter or Pv System Combined Cuk-Sepic ConverterRahulkannan Veerapparaj, Sarath Chandran P
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An improved downturn-controlled DC converter is proposed on this undertaking, essentially founded on the blend of the Cuk and SEPIC converters, that is appropriately legitimate for sun photovoltaic (PV) bundles. T