| Dr. Harsh M. Joshi | |
| Affiliation | Assistant Professor,Smt. NHL Municipal Medical College, Ahmedabad, Gujarat. |
| Email-Id: | drharshmjoshi@gmail.com |
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Category Archives: Uncategorized
Online Health Information Behaviour
UncategorizedAuthors: Research Scholar Merin Titty D Cunha, Assistant Professor Dr. Jisha S Kumar
Abstract: In today’s digital age, the internet serves as a fast, cost-effective, and accessible medium for accessing health-related information. The availability of audiovisual content and the ability to obtain direct insights from medical experts have further enhanced the appeal of online health information among users. This study primarily aims to explore the connection between individuals’ online health information seeking patterns and the outcomes that follow after their search. To analyse these relationships, Smart PLS-SEM (Partial Least Squares Structural Equation Modelling) is employed to examine the interplay among the key variables. Findings reveal that an individual’s motivation to seek health information online significantly influences post-search actions, such as modifying health practices, consulting a healthcare provider, or disseminating the acquired information to others. The study underscores the importance for healthcare professionals to recognize the underlying motivations and behavioural intentions driving consumers’ engagement with online health resources.
Artificial Intelligence for Cybersecurity: Threats, Defenses, and Emerging Challenges in the Era of Generative AI
UncategorizedAuthors: Sonal Sinha
Abstract: Artificial Intelligence (AI) has a dual relationship with cybersecurity: it is both a powerful defensive technology and, increasingly, a high-value attack target in its own right. Machine learning, deep learning, foundation models, and large language models (LLMs) now underpin intrusion detection, malware analysis, phishing identification, and autonomous incident response. At the same time, adversaries exploit AI for automated reconnaissance, AI-generated phishing, and attacks aimed directly at AI models — adversarial evasion, data poisoning, model extraction, prompt injection, jailbreaking, and AI supply-chain compromise. This paper condenses a comprehensive survey into a conference-length treatment: it traces the evolution of AI in cybersecurity, presents a unified taxonomy of attacks across the AI lifecycle, reviews key defense mechanisms (explainable AI, federated learning, differential privacy, guardrails, zero trust), summarizes major governance frameworks (NIST AI RMF, ISO/IEC 42001, EU AI Act, OWASP LLM Top 10), and outlines open research challenges for building trustworthy, resilient AI-driven security systems.
Experimental Investigation Of Combustion, Performance, And Emissions Characteristics Of Gasoline And Ethanol In A Spray-Guided Gasoline Direct-Injection Engine
UncategorizedAuthors: Rafiu K. Olalere, Y.O Bankole, Hongming Xu, Animashahun L. A, Sheriff Lamidi
Abstract: The increasing demand for cleaner and more sustainable transportation fuels has intensified interest in renewable oxygenated fuels capable of improving the combustion and emission characteristics of gasoline direct-injection (GDI) spark-ignition engines. This study presents a comparative experimental investigation of the combustion behaviour, engine performance, and gaseous emissions of commercial unleaded gasoline (ULG95) and absolute ethanol in a spray-guided GDI engine. Experiments were conducted under stoichiometric operating conditions (λ = 1) at an engine speed of 1500 rpm over an indicated mean effective pressure (IMEP) range of 3.5–8.5 bar using optimized spark timing. Combustion characteristics were evaluated through in-cylinder pressure analysis, coefficient of variation of IMEP (COVIMEP), combustion phasing (MFB50), combustion duration, combustion efficiency, indicated thermal efficiency, and indicated specific fuel consumption. Regulated gaseous emissions comprising carbon monoxide (CO), unburned hydrocarbons (HC), and nitrogen oxides (NOₓ) were also measured and compared. The results demonstrate that ethanol produced higher peak cylinder pressures, shorter combustion durations, improved combustion stability, and higher combustion and indicated thermal efficiencies than gasoline throughout the investigated load range. The superior combustion characteristics of ethanol were attributed to its inherent oxygen content, higher octane rating, and greater resistance to knock, which enabled optimum combustion phasing without knock-limited spark retard. Ethanol also produced substantially lower CO and HC emissions than gasoline, although differences in NOₓ emissions reflected variations in combustion temperature and ignition characteristics. Overall, the study demonstrates that ethanol offers significant advantages in combustion quality and exhaust emission reduction, highlighting its potential as a sustainable fuel for future high-efficiency GDI spark-ignition engines.
DOI: http://doi.org/10.5281/zenodo.21714967
IJSRET EDITORIAL BOARD MEMBER Dr. Surapati Pramanik
Uncategorized
| Dr. Surapati Pramanik | |
| Affiliation | Assistant Professor, Department of mathematics,Nandalal Ghosh B.T. College,Panpur, Narayanpur,India. |
| Email-Id: | sura_pati@yahoo.co.in |
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Recent Advances in Turbulent Flow Past Square Cylinders: A Critical Review of Experimental and Numerical Investigations
UncategorizedAuthors: Avinash M, Manjunath S.H, Vikram C.K
Abstract: The turbulent flow past square cylinders is a fundamental problem in fluid mechanics because it governs aerodynamic loading, vortex-induced vibration, drag, and heat transfer in engineering systems such as high-rise buildings, bridge piers, offshore structures, heat exchangers, and electronic cooling devices. Despite extensive research, accurately predicting flow separation, wake development, and thermal transport under varying operating conditions remains challenging. This review critically synthesizes recent advances in both experimental and numerical investigations of turbulent flow past square cylinders. Experimental techniques, including Particle Image Velocimetry, Laser Doppler Velocimetry, hot-wire anemometry, pressure measurements, and flow visualization, are assessed alongside Computational Fluid Dynamics approaches based on Reynolds-Averaged Navier–Stokes, Large Eddy Simulation, Detached Eddy Simulation, Scale-Adaptive Simulation, and Direct Numerical Simulation. The influence of Reynolds number, blockage ratio, corner modifications, thermal boundary conditions, and multiple-cylinder arrangements on wake dynamics and heat transfer is systematically evaluated. The review shows that Large Eddy Simulation provides the most accurate prediction of vortex shedding, wake structures, and aerodynamic forces, whereas Reynolds-Averaged Navier–Stokes models remain computationally efficient for engineering applications. Corner rounding, chamfering, and passive flow-control techniques consistently reduce drag and suppress wake instability while improving thermal performance. Remaining challenges include high-Reynolds-number simulations, coupled thermo-fluid analysis, turbulence model accuracy, and systematic experimental validation. The review identifies current research gaps and highlights future opportunities in advanced turbulence modelling, high-performance computing, and data-driven approaches to support the design of safer, more efficient, and thermally optimized bluff-body engineering systems.
Heat Transfer Enhancement In Microchannel Flows Using Hybrid Nanofluids
UncategorizedAuthors: Dr. G. Sugendran, Surinder Kumar
Abstract: The continuing shrinking trend of electronics along with growing power densities has resulted in many heat dissipation difficulties. Microchannel heat sinks are promising and compact heat sinks but limited by thermal performance due to thermal capabilities of traditional coolant fluids. This work examines the prospect of using hybrid nanofluids, i.e., a mixture of several different nanoparticles, to improve the convective heat transfer coefficients of microchannel flow. A detailed numerical analysis based on the two-phase Eulerian-Eulerian approach is performed to assess the thermohydrodynamic properties of aluminum oxide-copper/water hybrid nanofluid through rectangular microchannels under Reynolds numbers between 200 and 1000 and nanoparticle volume fractions between 0.5% and 2.0%. The simulations reveal a considerable heat transfer enhancement where the Nusselt number rises up to 38.4% at 1.0% volume fraction while reducing the thermal resistance by 29.6% and achieving the highest thermal efficiency ratio of 1.31. Although there is an increased pressure drop (18.7%), the thermal-hydraulic performance proves the feasibility of hybrid nanofluids as a new coolant.
DOI: http://doi.org/10.5281/zenodo.21697150
Identifying Decayed Fruits And Vegetables From Large Food Retailers Utilizing Machine Learning And Deep Learning, And Transforming Them Into Biogas
UncategorizedAuthors: Dr.Sumbul Alam
Abstract: Food waste management is a contemporary global issue. According to UNDP, food waste constitutes 40-51% of the waste in the Kingdom, followed by paper, cardboard, plastics, and other materials. Consequently, an effective waste segregation system is essential to address this problem. This research proposal aims to develop a mechanism for the segregation of decayed fruits and vegetables from the shelves, storage, and inventories of retailers such as Hyper Panda, Carrefour , and Lulu hypermarkets, utilising a hybrid machine learning algorithm comprising Linear SVM and PCA, alongside YOLO for real-time detection. Following segregation, this organic waste may be transported to a biorefinery where, using anaerobic digestion technology, it can be turned into methane gas. Currently, the door-to-door accessibility of processed foods, consumer products, and groceries is in great demand. Consequently, this methane gas may be utilised by their own delivery trucks and vehicles, so minimising food waste reduction in retail, promoting energy sustainability, and decreasing pollution.
DOI: http://doi.org/10.5281/zenodo.21676317
Decentralized Identity Management System Using Blockchain For Privacy-Preserving Digital Authentication
UncategorizedAuthors: Mrs.Aruna C, Rajeswary Nair
Abstract: With the advent of digital services, various vulnerabilities in centralized identity management systems such as Single Point of Failure (SPOF), data leakage, and user privacy invasion are evident. In this paper, an architecture framework for designing Decentralized Identity Management System (DIDMS) by leveraging blockchain technologies is proposed for privacy preserving authentication in digital age. The DIDMS framework makes use of Decentralized Identifier (DID) with Verifiable Credentials (VC) and Zero Knowledge Proof (ZKP) techniques to implement the concept of self-sovereign identity. Four phases of framework including registration, credential issuance, authentication and storage is designed and tested. The performance results obtained from the experimentation indicate that the proposed framework gives an authentication latency of 320 ms, storage overhead reduction of 42%, and verification accuracy of 98.6% with 31% gas optimization over conventional smart contract approaches. The comparative evaluation with existing frameworks indicates improvement in the areas of privacy protection, scalability and user control.
DOI: http://doi.org/10.5281/zenodo.21676274
Performance Enhancement Of Internal Combustion Engines Using Alternative Biofuels
UncategorizedAuthors: Dr. R. Bhaskar Reddy, Dr. A. Kumaraswamy
Abstract: Due to the increasing demands for energy in the world coupled with increased environmental regulations, it is now necessary to use sustainable energy sources instead of the traditional fossil fuels for internal combustion engines. In this paper, a study on performance improvement in compression ignition engines through the use of alternative biofuels has been presented. The study focuses on hydrotreated vegetable oil (HVO), biodiesel blends and the use of dual fuel where the two fuels used include biogas and hydrogen. The results of experimental and computer simulations show that the use of HVO leads to reduction of NOx and CO by 9.0% and 38.7%, respectively, compared to fossil diesel. Turbocharged B20 biodiesel blends lead to fuel consumption reduction of 20% and brake torque increase of 75%. The canola biodiesel gives brake thermal efficiency of 31.2% and brake-specific fuel consumption of 0.26 kg/kWh.
DOI: http://doi.org/10.5281/zenodo.21675388