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The Various Challenges Involved in Sensor Based Cloud System to Protect the Data and to Avoid Attacks: A Technical Review
In these studies, we introduce a unique protection framework for the integration of Wireless Sensor Networks (WSN) with cloud computing, aimed closer to enhancing statistics-centric programs consisting of far-flung healthcare structures. The framework's cornerstone is a robust, bendy safety version that ensures immoderate-degree information confidentiality, integrity, and terrific-grained get proper of access to control, addressing the important protection demanding situations in WSN-Cloud integration. By the use of a hybrid encryption mechanism that mixes the strengths of symmetric and uneven encryption techniques, our method gives a entire safety answer that protects information during transmission and garage. Furthermore, the version includes an efficient key manipulate gadget, facilitating the dynamic era and relaxed distribution of encryption keys. This contemporary framework is designed to mitigate common safety threats, such as Man-in-the-Middle (MITM) and Denial of Service (DoS) attacks, even as preserving the overall performance and standard performance of the blanketed gadget. Our research offers a massive contribution to securing statistics-centric packages in WSN-Cloud ecosystems, making sure dependable and comfortable facts verbal exchange and get right of entry to for a way off healthcare programs and past. 2024 IEEE. -
Machine Learning-Driven Energy Management for Electric Vehicles in Renewable Microgrids
The surge in demand for sustainable transportation has accelerated the adoption of electric vehicles (EVs). Despite their benefits, EVs face challenges such as limited driving range and frequent recharging needs. Addressing these issues, innovative energy optimization techniques have emerged, prominently featuring machine learning-driven solutions. This paper reviews work in the areas of Smart EV energy optimization systems that leverage machine learning to analyse historical driving data. By understanding driving patterns, road conditions, weather, and traffic, these systems can predict and optimize EV energy consumption, thereby minimizing waste and extending driving range. Concurrently, renewable microgrids present a promising avenue for bolstering power system security, reliability, and operation. Incorporating diverse renewable sources, these microgrids play a pivotal role in curbing greenhouse gas emissions and enhancing efficiency. The review also delves into machine learning-based energy management in renewable microgrids with a focus on reconfigurable structures. Advanced techniques, such as support vector machines, are employed to model and estimate the charging demand of hybrid electric vehicles (HEVs). Through strategic charging scenarios and innovative optimization methods, these approaches demonstrate significant improvements in microgrid operation costs and charging demand prediction accuracy. The Authors, published by EDP Sciences, 2024. -
Mediating role of teacher confidence between support system and satisfaction
Online education in India has witnessed a shift due to the ongoing pandemic, compelling the Indian education sector to adapt to new advancements. The study's main purpose has been to find the relationship between the support systems of institutions, teachers support and students, leading to instructors' satisfaction. It further analyses the mediating role of educators' confidence in linking support systems and leading to teachers' satisfaction. The sample for our research consisted of 129 teachers from Higher Educational Institutions (HEIs). We found that there is a significant relationship between support systems and teacher satisfaction. Among the three support systems, institutions support had a significant influence. On the other hand, teachers' confidence had a partially mediating effect on their satisfaction, even though they could translate to higher effectiveness in online teaching. Further, this study inferred that educational institutions are quick to adapt to online teaching due to the ongoing pandemic. Copyright 2022 Inderscience Enterprises Ltd. -
Green synthesis of zirconium phosphate by combustion method: photocatalytic application and microwave-assisted catalytic conversion of aldehyde to nitriles
Water pollution has increased swiftly, especially the dyes from industries that have disturbed aquatic eco-system. Photocatalytic degradation (PCD) is one of the attractive methods to eliminate dyes from industrial effluents. Zirconium phosphate (ZP) nanoparticles were synthesized by combustion method using zirconyl nitrate and phosphorous pentoxide as precursors. The obtained ZP was characterized by powder X-ray diffractogram, Fourier transform infrared, scanning electron microscopy, high-resolution transmission electron microscopy, Raman spectroscopy, photoluminescence spectroscopy, BrunauerEmmettTeller surface area. PCD was carried out using methylene blue as a model pollutant in aqueous medium in the presence of UV light irradiation with different concentrations of dye, catalyst and pH. Higher degradation efficiency was observed in basic medium. ZP is employed as a catalyst to form nitrides from aldehydes using different solvents with different aldehydes. Graphic abstract: [Figure not available: see fulltext.]. 2021, Indian Academy of Sciences. -
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High Gain Miniature Antenna Arrays for 2.4 GHz Applications
In this paper, miniature corporate feed Four Element Array (FEA), Eight Element Array (EEA) and Sixteen Element Array (SEA) are presented. The proposed antenna arrays are created on Rogers Duroid 5880 substrate with permittivity 2.2 and thickness of 0.782 mm. Initially, a single element antenna was created, then it was used in a corporate feed network designed for the 4-element array. As an extension, the 4-element array was used as a template and created an 8-element array and 16-element array to achieve high gain and directivity at 2.4 GHz. The proposed FEA, EEA, and SEA exhibit reflection coefficients of -25.55 dB, -37.14 dB, and -30.61 dB respectively. The peak gains obtained are 11.5 dB, 13.67 dB, and 16.76 dB respectively for FEA, EEA, and SEA. Also, the directivity has improved corresponding to the increase in the number of elements. Therefore, it can be a suitable candidate for applicationswhere extended range and coverage with better signal quality and higher data transfer rates is a priority. 2024 IEEE. -
Antenna Array Miniaturization using a Defected Ground Structure
A novel Defected Ground Structure (DGS) is proposed to miniaturize a 2 Modified Corporate Feed Planar Antenna Array (M-CFPA) with a modified corporate feeding network. The DGS altered the surface current distribution and shifted the resonance frequency to the lower side. After running a parametric sweep of length and width of the patch antenna element, achieved the miniaturized antenna array resonating at 2.4 GHz frequency. The proposed antenna array is designed using Rogers/RT Duroid 5,880 (2.2) substrate with a thickness of 1.6 mm. The overall dimensions of the proposed Planar Array with DGS (PA-DGS) is 25.2723 % lesser than M-CFPA. The M-CFPA has a peak gain of 11.53 dB with a-10 dB reflection coefficient bandwidth of 118 MHz. The proposed PA-DGS array exhibits a peak gain of 9.51 dB with 100 MHz-10 dB bandwidth. 2022, Walailak University. All rights reserved. -
Novel hybrid metamaterial to improve the performance of a beamforming antenna
This paper investigates the design and implementation of a novel hybrid metamaterial unit cell to improve a beamforming Wi-Fi antenna's performance. The proposed metamaterial unit cell is created on an FR-4 substrate (?? = 4.4) and a thickness of 1.6 mm. The metallization height of the unit cell is maintained at 0.035 mm. The designed metamaterial unit cell is simulated using HFSS Ver. 18.2 to verify the double negative behaviour. The unit cell consists of five Split Ring Resonators (SRR's) at the bottom and a hexagonal ring of six triangles. Initially, a conventional inset fed microstrip patch antenna is designed then an array of the proposed unit cell is created and used as a superstrate to study the performance. A Three Element Antenna Array (TEAA) is designed to operate at 2.4 GHz Wi-Fi band, and the superstrate created out of the proposed unit cell is used to study its effect. Metamaterial superstrate improved the conventional Single Element Antenna (SEA) gain by approximately 2 dB. Superstrate with TEAA exhibited an improved gain of 1 dB over TEAA. Published under licence by IOP Publishing Ltd. -
Gain and bandwidth enhancement by optimizing four elements corporate-fed microstrip array for 2.4GHz applications
This paper presents the performance analysis of an optimized corporate-fed Rectangular Microstrip Antenna Array of four elements and Rectangular Microstrip Antenna array with Semi-Circular Tabs on the nonradiating edges of each element of the array to operate at 2.4 GHz, with detailed steps of the design process. The proposed antenna structures have been designed using FR4 dielectric substrate having a permittivity ?r of 4.4 with a thickness of 1.6 mm. The simulations have been carried out by using Antenna simulator HFSS version 15.0.0 and performance was analyzed for gain, bandwidth, VSWR, return loss and radiation pattern. The gain of these simulated antenna arrays is 2.4381 dB, 8.2684 dB and 8.5621 dB with a return loss of ?22.4123 dB, ?14.1095 dB and ?15.7621 dB for Single-Element patch, conventional Rectangular Microstrip array and Rectangular Microstrip Antenna array with semicircular tabs respectively at 2.4 GHz. Bandwidths exhibited by Single-Element patch, RMSACT and RMSA are 59.8 MHz, 83.9 MHz, and 212.7 MHz, respectively. 2020, Springer Nature Singapore Pte Ltd. -
Miniaturization of Microstrip Antenna with Enhanced Gain Using Defected Ground Structures
The rapid advancement and growth in the wireless technology demands miniaturized communication equipment's. Microstrip antennas attracted many researchers over the past decades because of its various features like small in size, light weight, low cost and conformability. These antennas can operate at high frequencies and multiple bands with high gain and larger bandwidths if suitably designed. This work presents a Rectangular Microstrip Antenna (RMSA)performance improvement using defected Ground Structures (DGS). The simulation results revealed that the creation of Complementary Split Ring Resonator (CSRR)and Phi as a defect in the ground of proposed antenna has improved its gain. Introduction of DGS improved the gain by 27% and reduced the size by approximately 3.35%. Proposed Rectangular Microstrip Antenna with Defected Ground (RMSA-DGS)exhibits gain of 3 dB at 2.4 GHz with S11 response of -30.44 dB. In addition to this the antenna also shows one more resonance at 4.66 GHz with S11 of -14.29 dB and gain of -1.24 dB. RMSA-DGS has an overall dimension of 37.2 47.23 mm2. 2019 IEEE. -
A Smart Academic Ecosystem Framework for Enhancing Digital Skills and Startup Success Among Potential Women Entrepreneurs
Lack of digital literacy is still a significant impediment for women entrepreneurs to participate and succeed in sectors that rely on technology infrastructure, as mentoring and incubation support is uneven, even for those who are skilled. Conventional academic programs tend to lack well-defined links between structured digital education and entrepreneurial careers, and, as a consequence, gaps between learning outcomes and startup success result. This paper introduces a Smart Academic Ecosystem (SAE) Framework, with tailored and interactive digital adaptation, AI-based mentorship, and dedicated startup incubation, pleading for a standard, one-size-fits-all system. The framework is implemented with a layered architecture comprising data ingestion (from learning management systems), feature stores (learner profiling), and algorithmic modules (knowledge tracing, contextual learning path recommendations, graph-based mentor matching, and venture readiness scoring). Fairness-enabling interventions and privacy-preserving analytics are built into the system to support fairness and trust. A pilot evaluation with early-stage women entrepreneurs identified substantial gains: digital skills mastery increased by more than 20%, startup initiation improved by 12 percentage points, and equity gaps in digital confidence and access were significantly narrowed. Findings emphasize that the SAE model leads not only to faster development of digital capability but also to higher chances of entrepreneurial success. This paper provides a replicable, standards-based, and computer-science-centred framework for academic institutions to encourage women entrepreneurs and innovation ecosystems. 2025 IEEE. -
Delving into the Bubble Detection of Specific NSE Sector Indices
This study meticulously examines market bubbles within specific sectors of the National Stock Exchange (NSE) over the period from January 2017 to December 2023, employing robust methodologies like RADF, SADF, and GSADF tests. The analysis, centered on 11 sectoral indices, integrates GSADF values with RADF and SADF, offering nuanced perspectives that underscore the sector-specific nature of bubbles. Notably, the study highlights bubble occurrences during the 2020 global crisis due to pandemic, emphasizing their dynamic and diverse manifestations amid the pandemic. Exclusive identification of bubbles in NSE IT, NSE Metal, and NSE Pharma enriches the strategic insights available to investors, facilitating informed decision-making and risk management. The sector-wise approach contributes to a holistic understanding of market dynamics, providing investors with valuable tools to navigate the intricacies of the financial landscape. Future research avenues may delve into regulatory impacts on sector-specific bubbles and explore the interplay between macroeconomic indicators and sectoral bubbles, offering deeper insights into market dynamics. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Analyzing Risk-Return Trade-Offs Using ARCH and GARCH Models of the BRICS Countries
This study investigates financial markets in BRICS nations (Brazil, Russia, India, China, and South Africa) from 2003 to 2023. It examines mean returns, volatility, skewness, and kurtosis, assessing normality and data stationarity. ARCH-GARCH models uncover conditional heteroskedasticity and volatility clustering. It also explores mean reversion and momentum effects in the Nifty and MOEX indices. Findings show negative, near-zero mean returns, except for SSEC, which is modestly positive. Serial correlation suggests past values impact current returns. Volatility varies, with MOEX and SSEC having higher levels. ARCH-GARCH models indicate volatility clustering and non-normal return distributions. Mean reversion and momentum effects are identified in Nifty and MOEX, benefiting investors, financial institutions, and policymakers. This research informs investment strategies, risk management, and financial forecasts in BRICS economies, contributing to the understanding of the global financial landscape and potential contagion effects. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Interconnected Dynamics of Gold, Nifty, Crude Oil, and USD/INR: Insights from a Panel Data VAR Analysis
This study utilizes a panel data vector autoregression (PVAR) model to examine the relationships between Gold, Nifty, Crude Oil, and USD/INR, drawing from 3105 observations sourced from Yahoo Finance. Descriptive statistics reveal notable volatility, particularly in Gold and Crude Oil. Unit root tests confirm stationarity, crucial for time series analysis. Optimal lag selection recommends a lag order of 2, balancing model accuracy and complexity. Granger causality tests indicate limited predictive power, with gold influencing USD/INR unidirectionally. Impulse response function analysis and variance decomposition underscore Golds relative independence. Robustness tests affirm stability, highlighting USD/INRs endogeneity. This study enhances understanding of financial dynamics, offering insights for risk management, portfolio diversification, and monetary policy. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Forecasting Market Turbulence: A Multi-model Study Using GARCH, Random Forest, and LSTM in the Indian Stock Market
The dynamic and unpredictable nature of the Indian stock market presents significant challenges in forecasting return behavior and managing financial risk. This study explores market turbulence through a comparative analysis of three distinct modeling approaches: the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, Random Forest, and Long Short-Term Memory (LSTM) networks. By analyzing historical return data from Indian Nifty indices, the research captures both linear dependencies and complex nonlinear patterns associated with market volatility. The results highlight the GARCH models strength in modeling conditional volatility, while the machine learning and deep learning techniquesRandom Forest and LSTMexhibit enhanced predictive power in capturing intricate fluctuations in stock returns. The findings suggest that integrating traditional econometric methods with data-driven approaches offers a more comprehensive and accurate understanding of market dynamics. This multi-model framework is valuable for investors, financial analysts, and policymakers aiming to anticipate and navigate periods of heightened market uncertainty. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Unveiling Dynamics of Structural Breaks in Global Stock Markets and Implications for Forecasting Accuracy
This research investigates structural breaks in global stock markets, employing the Chow test on major indices from January 2013 to November 2023. Results reveal significant breaks in NYSE (November 2020) linked to the US election and positive vaccine trials, Nasdaq (May 2020) amidst global concerns over COVID-19, and Euronext 100 (February 2021), suggesting market shifts. Notably, Shanghai Stock Exchange experienced a robust break in December 2014, contrasting with SZSE's non-significant break. HKEX experiences a significant shift in June 2020, possibly influenced by US regulatory policies and COVID-19. The Nifty index shows a profound break in December 2020, correlated with pandemic severity. LSE Group evidences a break in July 2019, while the Saudi Exchange shows non-significant evidence in March 2021. The study underscores the importance of considering structural breaks for accurate market forecasting and decision-making. Descriptive statistics provide insights into market characteristics. The methodology integrates the Chow test and CUSUM squares for break detection. Findings contribute to understanding global market dynamics and emphasize the impact of external events on structural stability. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Interconnected Dynamics of Gold, Nifty, Crude Oil, and USD/INR: Insights from a Panel Data VAR Analysis
This study utilizes a panel data vector autoregression (PVAR) model to examine the relationships between Gold, Nifty, Crude Oil, and USD/INR, drawing from 3105 observations sourced from Yahoo Finance. Descriptive statistics reveal notable volatility, particularly in Gold and Crude Oil. Unit root tests confirm stationarity, crucial for time series analysis. Optimal lag selection recommends a lag order of 2, balancing model accuracy and complexity. Granger causality tests indicate limited predictive power, with gold influencing USD/INR unidirectionally. Impulse response function analysis and variance decomposition underscore Golds relative independence. Robustness tests affirm stability, highlighting USD/INRs endogeneity. This study enhances understanding of financial dynamics, offering insights for risk management, portfolio diversification, and monetary policy. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Tamarindusindica Mediated Combustion Synthesis of BiOCl: Photocatalytic Degradation of Dyes and Synthesis of ?-Enaminones
Environmental pollution due to dyes has been increasing continuously due to the large number of textile industries, which affects living systems. Photocatalytic degradation (PCD) is one of the most efficient methods to expel organic dyes in wastewater. In this respect, synthesizing photocatalytic nanoparticles to degrade organic dyes by a simple and cost-effective method is the real challenge. In this article, a carcinogenic dye, methylene blue, is considered for our study as it releases highly toxic species into the ecosystem and causes severe health problems such as cancer, skin and kidney problems, etc. Bismuth oxychloride has been synthesized by simple, low cost and rapid combustion method using low cost, easily available Tamarindusindica as a fuel at 500 C for ~10 min. The obtained BiOCl has been characterized by x-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), UV-Vis spectroscopy, photoluminescence spectroscopy and surface area by BrunauerEmmettTeller (BET). The XRD pattern shows a tetragonal phase and the FT-IR spectrum shows the presence of Bi-Cl at 1109 cm?1. SEM shows a flake-like morphology and HR-TEM displays d-spacing values of 0.13 nm. Photoluminescence studies show a green emission peak at 530 nm. Synthesis of ?-enaminones was also examined using analogues of aniline and dimedone in presence of BiOCl as a photocatalyst. 2021, The Minerals, Metals & Materials Society. -
Brinkman-Forchheimer flow of SWCNT and MWCNT magneto-nanoliquids in a microchannel with multiple slips and Joule heating aspects
Purpose: The microfluidics has a wide range of applications, such as micro heat exchanger, micropumps, micromixers, cooling systems for microelectronic devices, fuel cells and microturbines. However, the enhancement of thermal energy is one of the challenges in these applications. Therefore, the purpose of this paper is to enhance heat transfer in a microchannel flow by utilizing carbon nanotubes (CNTs). MHD Brinkman-Forchheimer flow in a planar microchannel with multiple slips is considered. Aspects of viscous and Joule heating are also deployed. The consequences are presented in two different carbon nanofluids. Design/methodology/approach: The governing equations are modeled with the help of conservation equations of flow and energy under the steady-state situation. The governing equations are non-dimensionalized through dimensionless variables. The dimensionless expressions are treated via Runge-Kutta-Fehlberg-based shooting scheme. Pertinent results of velocity, skin friction coefficient, temperature and Nusselt number for assorted values of physical parameters are comprehensively discussed. Also, a closed-form solution is obtained for momentum equation for a particular case. Numerical results agree perfectly with the analytical results. Findings: It is established that multiple slip effect is favorable for velocity and temperature fields. The velocity field of multi-walled carbon nanotubes (MWCNTs) nanofluid is lower than single-walled carbon nanotubes (SWCNTs)-nanofluid, while thermal field, Nusselt number and drag force are higher in the case of MWCNT-nanofluid than SWCNT-nanofluid. The impact of nanotubes (SWCNTs and MWCNTs) is constructive for thermal boundary layer growth. Practical implications: This study may provide useful information to improve the thermal management of microelectromechanical systems. Originality/value: The effects of CNTs in microchannel flow by utilizing viscous dissipation and Joule heating are first time investigated. The results for SWCNTs and MWCNTs have been compared. 2018, Emerald Publishing Limited. -
Entropy generation analysis of radiative Williamson fluid flow in an inclined microchannel with multiple slip and convective heating boundary effects
The main theme of the current work is to investigate the flow and heat transport characteristics of non-Newtonian Williamson fluid in an inclined micro-channel along with entropy generation analysis. The significance of the thermal radiation, convective boundary condition, and multiple slip effects is explored. The entropy generation of the system has been analyzed by adopting the 2nd law of thermodynamics. The rheological expressions of the Williamson fluid model are also taken into account. The nonlinear system is tackled by using the finite element method. An appropriate comparison has been made with previously published results in the literature as a limiting case of the considered problem. The comparison confirmed an excellent agreement. Detailed discussion of the significance of effective parameters on Bejan number, entropy generation rate, temperature and velocity is presented through graphs. The numerical results portray that the entropy generation and Bejan number have escalating behavior to the higher value of angle of inclination. Furthermore, the Bejan number changing its behavior at two points for different values of Reynolds number. IMechE 2021.