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Development of Quantum True Random Number Generators and Implementation on IBM Cloud Lab
No full textRandom numbers are the lifeline of any cryptographic operation in modern computing. Quantum mechanics has the intrinsic ability to generate truly random numbers, making it an ideal alternative for scientific applications that require high-quality randomness. Quantum True Random Number Generators (QTRNGs) can yield real random data to replace random-looking periodic sequences. To construct such a random number generator, this work uses the IBM Q Experience platform called Qiskit.
This research focuses on the development and analysis of quantum-based TRNGs along with their prime characteristics. Qubits and quantum gates are the predominant sources of true randomness on quantum platforms. These inherent quantum properties are explored in this study to develop statistically strong QTRNG architectures on Qiskit. The Hadamard gate applied to a single qubit generates random numbers with equal probability. An alternative QTRNG architecture is also implemented using rotation and phase gates instead of the Hadamard gate.
In this work, the Hadamard operation is achieved through rotation gates Rx(π), Ry(π/2) and phase gates Ph(π/2). Additional QTRNG designs are generated using X and Z gates with and without phase gates—such as Rx(π/2) Rz(π/2) P(π/2) and Rx(π/2) Rz(π). The angle parameters are optimized to achieve equal superposition. Another QTRNG architecture uses SX (square-root-of-X) gates and CNOT (Controlled-Not) gate combinations from IBM Quantum Experience. By applying the SX gate on all qubits followed by measurement, the architecture produces high-quality random bits with prime characteristics. The presence of primes in the generated sequences is also discussed.
Furthermore, genuine randomness is verified through repeated experimentation, and the statistical properties of the TRNG are evaluated using autocorrelation analysis and NIST SP 800-90B and 800-22 tests. The proposed quantum keys show no pattern or repeatability, exhibit strong randomness, and are highly unpredictable—making them suitable for secure quantum algorithms
Enhancement of Ambient Air Quality Index Forecasting using Optimized Ensemble Model
No full textForecasting ambient air quality is essential for environmental sustainability and public health, especially in heavily populated regions such as China, India, and the United States where air pollution remains a serious concern. Traditional forecasting models often struggle to accurately represent air quality data because of its complex patterns and nonlinear interactions. To address these challenges and improve forecast performance, this research proposes a comprehensive strategy that integrates parallel heterogeneous ensemble modeling with Bayesian optimization.
The study begins with a seasonal machine learning–based imputation technique (SeasonalMLImpute) designed to handle missing data in meteorological and air quality parameters. This method is evaluated against conventional imputation approaches such as MissForest, k-nearest neighbours (KNN), and median imputation. The comparison highlights the ability of SeasonalMLImpute to better capture seasonal variations, thereby improving the overall quality and reliability of the dataset.
Next, a novel Weight Guided Feature Selection (WGFS) algorithm is introduced to identify the most influential meteorological and air quality variables for predicting the Air Quality Index (AQI). The performance of WGFS is assessed against existing feature selection techniques, including sequential forward selection and sequential backward elimination. The comparison demonstrates that WGFS enhances both model interpretability and prediction accuracy by selecting more relevant features.
After identifying the most significant features, the Parallel Heterogeneous Weighted Average Voting Ensemble (PH-WAVE) model is employed for AQI prediction. This ensemble model combines multiple base learners to capture the complex relationships between meteorological conditions and air quality measures. By integrating diverse prediction models—each focusing on different aspects of air quality variability—and using parallel processing, PH-WAVE offers improved scalability, computational efficiency, and forecasting precision.
Finally, Bayesian optimization is applied to fine-tune the hyperparameters of the heterogeneous base models, resulting in the optimized ensemble model (BOPH-WAVE). Through systematic exploration of the hyperparameter space, Bayesian optimization enhances the predictive performance of the ensemble. The optimized model is validated using real-world air quality datasets from China, India, and the United States. The results demonstrate substantial improvements in forecast accuracy, error reduction, and computation time compared with traditional forecasting techniques and existing ensemble methods. Moreover, the model exhibits strong robustness to environmental fluctuations, making it adaptable for diverse forecasting scenarios and geographic regions
Thermo-Structural Analysis of Stiffened FGM Panels With Cutout Under Non Uniform and Localized In-Plane Edge Loadings
No full textMost aerospace applications involve structural components with a high stiffness-toweight ratio and excellent resistance to high temperatures. Buckling, vibration as well as other forms of instability are the consequences of a non uniform stress field caused by non uniform, localized edge loadings and the presence of discontinuities. In order to improve structural properties and increase load bearing capacity, designers concentrate on structural integrity, especially in high-temperature applications. The adaptability and customizable nature of functionally graded material (FGM) make it valuable in addressing these challenges.
Metal-ceramic FGM is an advanced composite material that integrates the distinctive qualities of metal and ceramic in a single volume and has mechanical properties that vary continuously and smoothly in spatial coordinates from one location to another. FGM technologies are still being researched and developed, which is expanding their potential and uses in the development of aerospace systems and technology. This work attempts to numerically evaluate the buckling and vibration characteristics stiffened and unstiffened FGM plates/shells with cutout under various mechanical and thermal load.
The buckling and vibration characteristics of both FGM plate and FGM shell are deteriorated by the influence of cutout and three stiffener patterns are introduced to enhance the characteristics. The ring stiffener provides good buckling characteristics and a maximum of 42% increase for the SSSS-edged FGM plate with k = 1, a/h = 10, and a cutout ratio of 0.5 when exposed to uniaxial UVL inplane compressive loads. Even though the straight stiffener exhibits good vibration characteristics than other stiffener patterns, the natural frequency is reduced by all stiffener patterns.
Additionally, the buckling load parameter, natural frequency parameter and critical buckling temperature decrease with an increase in temperature irrespective of the stiffener patterns and quantified the same. The effect of the uniform thermal environment and linear temperature rise from metal-rich to ceramic-rich regions on critical buckling temperature and free vibration characteristics of re-entry vehicle nose structures made of various FGM have also been examined. Finally, microstructural evaluation and various mechanical tests have been conducted on FGM plate fabricated using spark plasma sintering.
The SiC matrix grows progressively from the Al-rich layer to the SiC-rich layer, as demonstrated by the SEM investigation. No obvious gaps or delamination at the interface between any two layers are observed. The ultimate stresses for the tensile and compression tests are 139 MPa and 242 MPa, respectively. The natural frequencies were also determined experimentally as 820.3 Hz for first mode and 3203.1 Hz for second mode. The SiC-rich layer and the Al-rich layer had average hardness values of 122.42 and 58.81 HV, respectively. Thus, the current research contributes to detailed insight on the metal-ceramic FGM structures which help the designers in aerospace domain
ITIHAS Vol. 24 Issue No. 2
No full textNEWSLETTER FROM SASTRA DEEMED UNIVERSITYhttps://knowledgeconnect.sastra.edu/itihas/1003/thumbnail.jp
The Planning Strategy for Electric Vehicle Charging Stations in the Road Transportation Network Synchronized with the Distribution Network
No full textElectric vehicles (EVs) are recognized as a potentially effective solution to the environmental crisis and fuel deficit that modern metropolises are currently experiencing. Meanwhile, the expansion of EVs and their haphazard charging would negatively affect the road transportation network (RTN) as well as the electric distribution network (EDN). The proper infrastructure for the electric vehicle charging station (EVCS) will enhance the effective utilization of energy of both the networks.
This research work proposes a two-phase planning strategy for deploying Electric Vehicle Charging Stations (EVCS), considering both static and dynamic factors. The strategy uses a hybrid PSO-DS algorithm which is a combination of particle swarm optimisation algorithm and direct search method to optimize multiple objectives. The effectiveness of the proposed algorithm is validated using benchmark functions facilitates in solving of proposed planning strategy. This approach can help decision-makers in efficiently deploying EVCS infrastructure.
In the first phase, a static framework model is developed considering the nodes and distance of the traffic network and distribution network. The EV charging station placement problem concerns the total coverage in the traffic network, the system losses, and node voltage deviations in the electric distribution system. The distribution systems are typically equipped with shunt capacitors for reactive power compensation to address the loss reduction and voltage profile improvement.
In this work, a mathematical model comprising three objective functions, maximisation of coverage and minimisation of loss and node voltage deviations subjected to constraints, is proposed for the simultaneous placement of EV charging stations and shunt capacitors. The control variables for optimisation are the rating and location of charging stations and shunt capacitors. The placement of EVCS on the distribution network would increase the power loss and total voltage deviation. These issues are addressed by the placement of the shunt capacitor in the optimal location. To verify the model, simulations are carried out on an IEEE33-bus distribution system and a 25-node traffic network system to determine the different planning strategies for the placement of charging stations.
In the second phase, a dynamic framework model is proposed which considers the dynamic behavior of traffic network and distribution network. A combined model of road transport and electric distribution network (CoRTED) is proposed in this work to place the charging station on the urban road traffic network with the minimal travel expense of the EV user’s and minimal power loss, voltage deviation in the distribution network. The suggested model calculates the dynamic user equilibrium (DUE) on the traffic network based on the placement of charging stations and simultaneously takes the grid network’s economic operation into account.
The appropriate injection of active and reactive power by PV panels and shunt capacitors resolves the grid difficulties caused by the EVCS. The proposed model is resolved by a bi-level optimization algorithm, where the user equilibrium of the traffic network is resolved by the Combined convex optimisation (CCO) method and the economic operation of the grid is formulated as alternating current optimal power flow, which is solved by a primal-dual interior point method. Finally, an integrated system comprising modified Nguyen-Dupius RTN and IEEE 33 bus EDN is used to validate the effectiveness of the proposed CoRTED model.
Finally, a hybrid short-term solar energy prediction model is suggested to enhance grid safety and reliability, particularly with the rising demand for energy due to the increasing number of electric vehicles (EVs). This necessitates the utilization of renewable energy sources (RES), which emit zero carbon. The intermittency nature of RES makes the grid unstable. Due to the stochastic nature of the sources, it is essential to predict solar power for effective integration. The evolution of deep learning makes the prediction simple with complex and non-linear temporal data.
In this work, a hybrid Vector Auto Regressive (VAR) model, Convolutional neural network (CNN) and Longshort term memory (LSTM) are proposed to predict solar power using real-time data from the Adirampattinam station, Tamilnadu, India for the period of 2014 to 2020. The VAR-CNN-LSTM model employs the VAR model and deep learning network to capture linear and non-linear data features. In this proposed hybrid method, the VAR model capture linear feature of the data, the CNN layer will extract the hierarchical structure from the various weather parameters, and LSTM will extract the long-term temporal characteristics of the data. The results obtained in this work for the proposed model is then compared with distinct VAR, CNN, LSTM, and hybrid CNN-LSTM models to verify the performance of the model
Investigation of Various MIMO Antenna for 5G Mobile Phone Applications
Get PDFThe rapid progress of wireless communication systems has been driven by the persistent demand for higher data rates, improved connectivity, and seamless user experiences. The introduction of fifth-generation (5G) wireless technology introduces fresh challenges and possibilities within the domain of antenna design, particularly concerning Multiple-Input Multiple-Output (MIMO) systems operating in the sub-6 GHz frequency range. This thesis conducts a comprehensive exploration and conceptualization of MIMO antennas expressly crafted for smooth integration into mobile phones, with a particular emphasis on addressing the distinctive requisites of sub-6 GHz 5G communication.
The proposed antenna designs effectively harnesses the advantages inherent in multiple-input multiple-output (MIMO) technology to amplify data speeds and reliability through the utilization of spatial diversity. In response to the constraints imposed by the physical dimensions of mobile phone devices and the frequency spectrum below 6 GHz, the antennas are meticulously crafted to uphold compact forms while ensuring efficacious radiation capabilities. The design process entails thorough analysis of modelling, optimization, and assessment methodologies to attain desirable features encompassing impedance matching, radiation patterns, and reduction of the envelope correlation coefficient (ECC).
Furthermore, this research inspects the influence employed by diverse multiple-input multiple-output (MIMO) configurations specifically, 6x6 and 10x10 on the complete system performance. A thorough investigation is undertaken to measure antenna properties such as isolation, diversity gain, and channel capacity, thereby evaluating the benefits of deploying MIMO antennas in mobile devices tailored for sub-6 GHz 5G applications.
The proposed designs are validated through simulations and measurements, duly spotlighting its feasibility and appropriateness for seamless integration into commercially intended mobile devices. The findings underscore the considerable potential of the suggested MIMO antenna configuration in strengthening the capacity and reliability of sub-6 GHz 5G networks, all while navigating the limitations imposed by the physical dimensions of mobile phones. This study presents a noteworthy contribution to the ongoing efforts aimed at refining wireless communication systems, offering valuable insights into the workings of MIMO antenna design for forthcoming mobile devices operating within the sub-6 GHz frequency realm
Measurements In Kautilya’s Arthasastra, In the Domains of Public Finance and Governance
Get PDFAncient Sanskrit literature has rich discussion of measurements by different authorities. Examples from the Vedic Age and the period of Itihāsas can be found in Ṛgveda (c. 1500 BCE), Rāmāyaṇa, and Mahābhārata. A subsequent, and more elaborate, exercise of codification of measurements, relevant to finance and administration, is observed in Arthaśāstra, written by Kauṭilya, also known as Cāṇakya and Viṣṇugupta (c. 350-275 BCE).
The author, a scholar from Takṣaśilā, was the advisor during Cāndragupta Maurya’s reign (c. 321-297 BCE). After millennia of hibernation, Kauṭilya’s Arthaśāstra resurfaced, in the beginning of the twentieth century. Ever since, Arthaśāstra has been a subject of study, especially of professionals, given its focus on statecraft, economic policy, and military strategy. These subjects have been widely researched into, with a broad mention about measurements in the sense of ‘weights and measures’ in Kauṭilya’s Arthaśāstra. Offences and penalties specified in Arthaśāstra have also been generally studied, from a legal angle.
When viewed from a measurement perspective, the definition of units of measure is only the beginning of measurements in Arthaśāstra. Another dimension is the assessment of damage caused by transgressions and the prescription of fines or other frightful punishments. Going beyond these two aspects – weights and frights – Kauṭilya has presented measurement in different other forms, such as the extensive categorisation of attributes, and grading or ranking by characteristics; these serve as qualitative measurements as to the suitability or otherwise of the objects – be they commodities, persons, or information – for the purpose.
This thesis attempts an exploration of the qualitative and quantitative measurements in Arthaśāstra, employed in the areas of public finance and governance, drawing references to comparative historical literature relevant to topic. Enablers of measurement in Arthaśāstra, as for instance, the elaborate classification and gradation explained by Kauṭilya, are also looked into, to discover relevance and applicability of Kauṭilya’s thoughts in the present-day context
Metal Organic Frameworks Modified Textiles for the Detoxification of Chemical Warfare Agent / Simulant
No full textChemical Warfare Agents (CWAs) have been listed as lethal weapons of mass destruction due to their extreme toxicity and devastating effects. Malfeasant usage of CWAs involved in the current world praxis poses threat to humankind. Owing to their acute lethal toxicity, the pursuit of favorable approaches for the detoxification/degradation are in continuous progress. In current trends, an imminent development of self-detoxification filters is highly desirable against the CWAs exposure. Exploiting protective materials that can be applicable in day – today life for an instantaneous detoxification will be of prodigious importance.
With this background, a series of Zirconium based UiO-66 and UiO-66-NH2 metal-organic frameworks (MOFs) featured with structural defects were synthesized using solvothermal technique by varying the modulator pKa, HCl modulator concentration, water molecules, synthesis temperature and ligands ratio. The structural, morphological, elemental, functional, and thermal properties of synthesized MOFs were analyzed using X-ray Diffractometer, Scanning Electron Microscope, X-ray Photoelectron Spectrometer, Fourier Transform Infrared Spectrometer, and Thermogravimetric Analyzer.
The present study contributes additional evidence that the considered synthesis parameters outset the creation of open framework in its own metrics. By fine tuning the synthesis practices, the formation of structural defects has been greatly induced. Further, the impact of structural defects possessed by the synthesized samples was systematically investigated against Methyl-paraoxon (DMNP), a CWA simulant. The role of catalytic features of UiO-66 and UiO-66-NH2 obtained by tailoring their defects in enhancing the degradation efficiency has been systematically investigated using UV-vis spectrophotometer.
The detoxification efficiency of 98.5% with a half-life time of 0.23 min has confirmed the effectiveness of engineered defects in enhancing the catalytic activity of UiO-66 in detoxifying the identified simulant. The coexistence of amine group (-NH2) representing Bronsted basic sites, and Lewis’s acid sites of metal clusters in UiO-66-NH2 unveils the maximum conversion efficiency up to 93.6% with an ultrafast transient degradation rate (k) and shorter half-life time of 1.567 min-1 and 0.44 min, respectively.
The self-standing UiO-66 and UiO-66-NH2 functionalized fabrics (MOFabrics) exhibited an expeditious detoxification performance against DMNP with a maximum removal percent conversion of 88.9% and 90.68% respectively. Also, UiO- 66 and UiO-66-NH2 impregnated fabrics have showed a reduced half-life of about 10.16 and 11.23 min for DMNP degradation, in comparison with an unmodified/carboxymethylated fabric of 462 min. This substantial catalytic performance conferred the ability of self-detoxifying MOFabrics, to be well suited for a protective garments’ application in a real time scenario
Existence and Uniqueness Results for Deformable Fractional Differential Equations
No full textFractional calculus and fractional differential equations are considered to be the valuable tools in modeling many phenomena in various fields of science and engineering. In the literature, many definitions for fractional order derivatives, such as Riemann-Liouville, Caputo, Jumarie, Hadamard, Weyl, and more, were developed to study the fractional differential equations that govern various phenomena in science and engineering. But these definitions have their own limitations, such as derivatives of constants, product of two functions, quotient of two functions, assertion laws, and limiting values of the derivatives at zero and negative numbers.
To overcome the deficiencies, researchers have recently introduced some new derivatives, namely conformable and deformable fractional derivatives. In particular, a deformable derivative has a special property called the intrinsic property, where the derivative is linearly related to the integer-order derivative. Fractional calculus stands out in modeling the problems involving the concepts of non-locality and memory effect that are not well explained by integer-order calculus. Indeed, fractional calculus tackles the concept of the derivative operator, where in integer-order calculus, the operator has a local nature, whereas in fractional calculus, it has a non-local nature.
Another important aspect is the concept of mild solutions, which are strongly associated with fractional calculus and fractional integral operators. Mild solutions involve integral operators that account for the past behaviour of the system, making them well-suited for modelling phenomena with long- term memory effects. Controllability is one of the basic problems in control theory for the fractional dynamical system represented by linear or non-linear fractional differential equations. Most importantly, obtaining the solution of linear or nonlinear fractional differential equations in analytical or numerical form is very tedious, as the integration of nonlinear fractional order terms is very difficult. The researchers keep studying to develop new methods to tackle these difficulties.
The utilisation of the special property of deformable derivatives, the interesting behaviours of fractional differential equations, and the different kinds of solutions to some fractional differential equations are studied in this thesis as a main objective, and it can be divided into four specific aims. In the first three specific aims, the research reported in this thesis deals with the problem of existence and approximate controllability results for the various types of perturbed fractional differential and integro-differential systems with deformable derivatives in Banach spaces.
First, we study the existence of solutions for perturbed fractional neutral differential and integro-differential equations using the deformable derivative in Banach spaces. Next, the existence of mild solutions for perturbed fractional neutral differential and integro-differential equations using the deformable derivative in Banach spaces is examined. Finally, the existence, uniqueness, and approximate controllability of mild solutions for fractional neutral differential equations using the deformable derivative in Hilbert spaces are discussed.
The stability analysis is also discussed. The approach that is considered here is based on fixed-point techniques such as Banach’s, Krasnoselskii’s, Leray Schauder’s alternative, Schauder’s fixed-point theorem and Ulam-Hyer stability. Several abstract fractional differential equations are provided to illustrate the obtained results. The fourth specific aim is concerned with the methods for solving linear and nonlinear fractional-order differential equations with deformable derivatives. First, the new fractional differential equations governing some models, namely the relaxation equation, the population growth equation, and the one-dimensional diffusion equation, are obtained by replacing the existing fractional order derivative of Caputo type with the deformable derivatives.
Next, the analytical, semi-analytical, and numerical methods such as the Laplace transform, the Homotopy perturbation method, and the finite difference method are developed and applied to the modified models to study the solution quality at different deformable fractional orders. The solutions are also compared with the exact solution as well as the numerical solutions. The methods that are developed are simple, easy, and convenient to handle fractional- order differential equations with deformable derivatives
Design & Development of FR1 Band Antenna for V2X Communication
Get PDFThe developing trends in the automotive industry are evolving towards connected and autonomous vehicles that provide various advantages namely enhanced safety & security, congestion less traffic, smart mobility, and environmental sustainability at a lower cost with greater cause to the society. Vehicle to Everything (shortly V2X) Communication plays a significant role in autonomous driving. Salient features of V2X provide improved better driving experience and traffic efficiency even during fast moving scenarios.
V2X technologies are being carried out in sub 6 GHz range mainly at the 5.9 GHz band called the Dedicated Short-Range Communication (DSRC) based on IEEE 802.11p providing support for basic applications in the field of Vehicular Communication. With advent improvements in the mobile broadband technology and country aiming towards the 5G rollout newer bands in the LTE band-42 (3.4-3.6 GHz range) by 3GPP are a key focus for network-based vehicular communication. Cellular-V2X, defined as the umbrella term having the existing and newer technologies to be deployed. The C-V2X works in two modes, one using the legacy DSRC spectrum for short range communication and the defined mobile broadband range for network based LoS communication.
This research aims to develop an ad-hoc antenna to co-exist both the frequency bands committed for V2X environment. The research proposed a wideband Defected Ground Structured (DGS) Multiple-Input Multiple Output (MIMO) antenna working in the mid-band of the 5G spectrum range for multiple wireless applications including the Wi-Fi and V2X scenarios.
The challenges in the antenna design technique are further enhanced by developing a dedicated multiband MIMO antenna to co-exist the DSRC band and the C-V2X band in the 5G spectrum by bringing forth the Co-Planar Waveguide (CPW) technology which provides excellent features in the aspect of antenna system for Vehicular Communication. Inorder to provide proper placement methodology for the V2X antenna, a compact multiband conformal MIMO antenna is developed for V2X frequency bands which can be easily mounted on the vehicle surface.
The designed antennas are fabricated and compared with simulated antenna parameters such as reflection co-efficient, Gain, Efficiency and the diversity performances of the MIMO system namely Envelope Correlation Co-efficient, Diversity Gain, Mean Effective Gain, Total Active Reflection Co-Efficient and Channel Capacity Loss. The antenna prototype is also tested in real time environment by performing On-Vehicle Analysis (OVA) for the study of reflection and mutual coupling are measured by transmitting and receiving signals in the V2X Environment.
The obtained results for the antenna parameters and MIMO diversity performance for the fabricated antenna prototype are well in association with the simulated results and the real time measurements of the prototype further strengthen the functioning of the antenna as a robust communication system. This research provides a novel antenna system for the next generation Vehicular Communication succeeding the existing antennas used for V2X Communication