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Daily Archives: October 2, 2025

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Security Issues in Platform as a Service (PaaS) Cloud Computing

Authors: Shikha Goel

Abstract: Cloud computing has transformed IT service delivery by offering scalable, on-demand resources over the internet. Among its service models—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)—PaaS provides a robust platform for developing, running, and managing applications without the complexity of maintaining the infrastructure. However, PaaS introduces a unique set of security concerns due to its multi-tenancy, abstraction layers, and reliance on third-party services. This paper explores the key security issues in PaaS environments, including data isolation, insecure APIs, platform vulnerabilities, insider threats, and compliance challenges. We also discuss mitigation strategies and emerging trends to enhance PaaS security.

DOI: https://doi.org/10.5281/zenodo.17249277

 

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Artificial Intelligence In Healthcare: Transforming Medical Practice Through Technology Integration

Authors: Tarun Krishna Mahajan

Abstract: This comprehensive review examines the current state and future prospects of artificial intelligence AI) in healthcare, with particular emphasis on implementation strategies, challenges, and outcomes. The global AI healthcare market, valued at $26.57 billion in 2024, is projected to reach $187.69 billion by 2030, growing at a CAGR of 38.62% [^62]. This study analyzes AI applications across clinical decision support systems, predictive analytics, telemedicine, and population health management. Key findings indicate that 94% of healthcare providers currently use AI in some capacity, with clinical decision support systems demonstrating significant improvements in diagnostic accuracy and patient outcomes [^65]. Machine learning approaches, particularly random forest algorithms 42% of studies) and logistic regression 37% of studies), show greatest effectiveness in disease prediction and management 1 . However, implementation faces substantial barriers including data quality issues 47% of leaders cite this concern), regulatory compliance challenges 39% , and workflow integration difficulties [^73]. The review presents the HealthWise ecosystem as a case study of comprehensive AI integration, demonstrating potential for government-scale deployment across 130 crore Aadhaar cardholders in India. Privacy and security considerations under HIPAA and GDPR regulations require careful attention, with end-to-end encryption and privacy-by-design approaches being essential for compliance [^82]. This analysis concludes that successful AI implementation requires integrated approaches combining technological innovation, regulatory compliance, stakeholder engagement, and sustainable business models to realize the transformative potential of AI in healthcare delivery.

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Implementation Of Neural Network Control Mechanism For Grid Connected Wind-Solar PV Charging Station

Authors: Manish Kumar, Ishan Sethi2

Abstract: Distributed Generators (DG) embody a multi-source microgrid amalgamated within a unified framework. These DGs are meticulously designed to calibrate voltage, current, and frequency in accordance with the load terminal’s observed power demand. Constructing an optimal control paradigm for these systems amplifies their functional efficacy. This study simulates a DG control architecture within MATLAB/Simulink, integrating photovoltaic (PV) arrays, a proton-exchange membrane fuel cell (PEMFC), and an ultra-capacitor to ensure a steady and dependable output for the grid. The PV component within this configuration utilizes a Maximum Power Point Tracking (MPPT) mechanism, which optimizes power transmission to the grid. To address PV’s inherent variability, an ultra-capacitor and PEMFC are employed, ensuring stable output. Here, the ultra-capacitor counterbalances the PEMFC’s thermodynamic fluctuations, enhancing reliability. A power-electronics-based interfacing circuit, paired with advanced control configurations, upholds power quality by regulating the grid's voltage and frequency within permissible thresholds.

DOI: http://doi.org/10.5281/zenodo.17248263

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A New Strategy For Power Management In Multisource Microgrid System With MPPT Algorithm

Authors: Manish Kumar, Ishan Sethi

Abstract: This work proposes a novel approach to enhance Grid- connected wind-solar PV charging stations face with challenges like fluctuating energy supply, inefficient resource usage, and the necessity for adaptive real-time control. Traditional control methods, like PI controllers, often fall short in optimizing system performance under these dynamic conditions, resulting in inadequate power supply for EV charging. To tackle these hurdles, this study proposes a pioneering approach employing neural network (NN) controllers to enhance grid-connected wind- solar PV charging stations' operation. NN controllers dynamically adjust charging station operations based on real- time data inputs, offering superior adaptability and efficiency. By integrating wind and solar power generation with intelligent NN control mechanisms, the system adeptly responds to varying environmental conditions and grid demands, ensuring more effective utilization of renewable energy sources. The proposed NN controller-based system targets enhancing the reliability, sustainability, and economic feasibility of grid-connected charging stations. Simulations showcase the effectiveness and stability of this approach in integrating renewable energy into transportation infrastructure. Performance evaluation can be conducted using Matlab/Simulink Software

DOI: http://doi.org/10.5281/zenodo.17248231

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