http://localhost:8080/xmlui/handle/123456789/387 2026-04-26T08:06:15Z http://localhost:8080/xmlui/handle/123456789/3506 Title: Boundary Layer flow of a Casson Fluid Past a Thin Needle Authors: GORANTALA, SARITHA Description: NITW 2024-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3505 Title: DESIGNING SECURE ATTRIBUTE-BASED VERIFIABLE DATA STORAGE AND RETRIEVAL SCHEMES IN CLOUD COMPUTING ENVIRONMENT Authors: Bera, Sourav Abstract: Cloud computing technology is a novel storage and computing paradigm that en ables individuals and organizations to store data, share data with the intended group of users, and retrieve data when required. It greatly improves peoples’ data storage and sharing, and data retrieval capabilities by providing flexible, less expen sive, and quality services. For data security and privacy concerns, fine-grained data access control, authenticated and secure data storage, authorized data searching, and self-verifiability of the corrrectness of search results are of critical importance. Attribute-based cryptographic framework is a promising solution for applications requiring fine-grained access control. However, a significant computation cost that rises in complexity with access policy complexity affects the majority of attribute based cryptosystems. Because of this, their usefulness in resource-constrained en vironments may be compromised. Hence, this thesis aims at designing secure and efficient attribute-based cryptographic schemes with data storage, data sharing, and data retrieval in cloud computing environments. The contributions of the thesis are threefold. We, first, propose a lightweight online-offline attribute-based data storage and retrieval scheme with Boolean key word search mechanism. The computationally intensive tasks are either offloaded to the cloud or offline phase and the lightweight operations are carried out by the data user, which makes the scheme lightweight. Next, we design a verifiable and Boolean keyword searchable attribute-based signcryption scheme in a cloud-based Electronic Medical Record (EMR) manage ment system. The scheme allows EMR owners to store and share their personal EMRs with specific healthcare professionals. It uses disjunctive normal form en cryption policy to make the scheme communicationally efficient. Both the afore mentioned schemes achieve data owner (DO) privacy, data and DO authenticity, non-interactive verifiability, fine-grained access control over encrypted data, Boolean keyword search, keyword privacy, outsourced decryption, and provable security. Further, to achieve efficient data sharing functionality along with data searching, we propose an attribute-based proxy re-encryption scheme with Boolean keyword search mechanism. We prove that the scheme is adaptive chosen ciphertext attack secure at both the original and re-encrypted ciphertext, and chosen keyword attack secure on both ciphertext and token. Keywords: Attribute-based encryption, attribute-based signature and signcryp tion, bilinear pairing, constant decryption cost, linear-secret sharing scheme, data viii storage and retrieval, data sharing, attribute-based searchable encryption, attribute based proxy re-encryption, Boolean keyword search, search results verification Description: NITW 2024-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3504 Title: INNOVATIVE HYBRID METAHEURISTIC ALGORITHMS AND THEIR APPLICATIONS UNDER FUZZY OR DETERMINISTIC ENVIRONMENT Authors: Rath, Subhabrata Abstract: The thesis focuses on developing Innovative metaheuristic algorithms (HPSO, PSOHHO, PSOHHO-V, PSOMHHO, and Fuzzy BTO) inspired by nature. Despite the proliferation of metaheuristic algorithms, a significant void exists in conducting thorough theoretical and mathematical analyses. More studies are needed, particularly in the critical domain of convergence of metaheuristic algorithms. The proposed algorithm's theoretical analysis and mathematical foundation are established to tackle this challenge by introducing the concept of signature and convergence. The stability analysis of HPSO is also discussed to strengthen it mathematically even further. The thesis also emphasizes the applications of developed metaheuristic algorithms on different real-world problems in fuzzy and deterministic atmospheres. Job scheduling problems on computational grids commonly fall into NP-completeness or NP-hardness, making the quest for optimal solutions notably time-intensive. To address this challenge expediently and effectively, scholars have predominantly turned to the exploration of metaheuristic algorithms. Hence, the developed algorithm HPSO is applied to both single-objective and multi-objective Job Scheduling problems on the computational grid. Classification problems frequently involve a surplus of features, but not all contribute to the problem's essence. Redundant or irrelevant features may impede classification accuracy. Metaheuristic algorithms are favoured for feature selection due to their simplicity and practical applicability, offering advantages over deterministic optimization algorithms. For this purpose, the real-world application of developed algorithms PSOHHO, PSOHHO-V, PSOMHHO, and Fuzzy BTO are verified on feature selection problems. They are applied to the hybrid Feature Selection problem and compared with other metaheuristic algorithms on seven UCI machine learning repository datasets. Existing literature highlights the effectiveness of forecasting methods with more diverse set types. The idea of enhancing outcomes by incorporating additional inputs is closely observed. This theoretical basis advocates the efficiency of Picture Fuzzy Sets (PFYSs) in forecasting models. Notably, there needs to be more literature regarding the joint application vii of PFYS and swarm intelligence for Fuzzy Time Series (FTS) forecasting. This chapter introduces the innovative EDSPSO-PFTS approach to address this gap. This thesis is structured into five sections, encompassing ten chapters. Part I consists of Chapter 1, an introduction, and motivation for the research work carried out. It features a comprehensive literature review emphasizing the importance of the thesis's focal issue. In Part II, the emphasis shifts to the real-world deployment of the newly created hybrid metaheuristic algorithms, specifically in the context of Job Scheduling on a computational grid. There are two chapters in this part, which are 2 and 3. Chapter 2 applies a proposed fuzzy particle swarm optimization to address single-objective job scheduling on computational grids. Focused on minimizing the makespan value, indicative of maximum task completion time across the grid, this chapter explores the impact of trapezoidal and pentagonal fuzzy numbers, presenting a detailed comparative analysis. Chapter 3 explores the application of fuzzy particle swarm optimization for multi-objective job scheduling on computational grids. The foundation established in the previous chapter is expanded upon in this chapter, which moves from single-objective to multi-objective optimization. This chapter aims to maintain a delicate balance between makespan and flowtime objectives, which are conflicting. The practical application of the proposed hybrid metaheuristic algorithms in the hybrid feature selection problem domain is the main emphasis of Part III of the thesis. There are five chapters in this section: Chapters 4, 5, 6, 7, and 8. In Chapter 4, a Hybrid Particle Swarm Optimization (HPSO) algorithm is introduced and applied to address a Hybrid Feature Selection problem. This chapter discusses the stability of the proposed HPSO algorithm through the Von Neumann stability criterion and Fourier series concepts. The convergence of HPSO is explained using the Markov chain concept. The chapter thoroughly compares results against other metaheuristic algorithms, employing statistical tests like the Friedman and Mann-Whitney U test to estimate the algorithm's statistical significance. viii In Chapter 5, an improved version of the Particle Swarm Optimization algorithm, HPSO, is thoroughly explored for its application in multi-objective feature selection. This section represents a notable progression from single-objective to multi-objective optimization, leveraging the foundation in the previous chapter. The effectiveness of HPSO is meticulously evaluated across seven UCI datasets, with robust statistical analysis facilitated by the Wilcoxon rank sum test. In Chapter 6, two innovative hybrid optimization algorithms, PSOHHO and its variant PSOHHO-V, are introduced. These algorithms enhance their exploration capabilities by integrating a dual-swarm strategy and an exponential mutation operator. The evaluation of PSOHHO and PSOHHO-V involves rigorous analysis of statistical metrics and convergence rates, with extensive testing on benchmark functions. Furthermore, the algorithms are applied to feature selection problems, and their performance is benchmarked against alternative approaches using seven UCI datasets. In Chapter 7, a ground-breaking Hybrid Swarm Optimization algorithm, PSOMHHO, is introduced, seamlessly integrating Pentagonal and Trapezoidal Fuzzy Numbers. The chapter explores the mathematical foundations by proving the algorithm's convergence using the Markov Chain property and introducing the algorithm's signature. The effectiveness of PSOMHHO is meticulously evaluated through extensive benchmark function testing, establishing its superiority over established metaheuristic algorithms. Rigorous statistical tests, including the Mann-Whitney U test and the Friedman test, affirm the exceptional performance of PSOMHHO across various metaheuristic algorithms. Chapter 8 introduces innovative hybrid swarm optimization algorithms (Fuzzy BTO and its variants). Emphasizing the critical role of parameters in optimization, this chapter introduces fuzzy concepts for dynamic parameter adaptation. The efficiency of Fuzzy BTO and its variants are rigorously evaluated through extensive benchmark functions, followed by a comprehensive comparison with established metaheuristic algorithms. The robust statistical analysis, employing the Kruskal-Wallis Test (KWT), validates the superior performance of Fuzzy BTO across various metaheuristic algorithms. ix In Part – IV of this thesis, the emphasis shifts to applying the proposed hybrid metaheuristic algorithms and Picture Fuzzy Set on Forecasting. This critical part is summarized in a singular chapter, namely Chapter 9. A novel picture fuzzy time series (PFTS) forecasting model built on the foundations of picture fuzzy sets (PFYSs) is presented in Chapter 9. This chapter develops a unique hybrid EDSPSO PFTS forecasting approach by integrating PFYS and EDSPSO. To illustrate the applicability and utility of the proposed forecasting method, it is applied to data sets from the Alabama University and the State Bank of India share price at the Bombay Stock Exchange, India. Average forecasting error (AFE) and mean square error (MSE) are used to evaluate the efficiency of the suggested approach. Thorough statistical validation and performance analysis are carried out to guarantee the validity and dependability of the proposed approach. The thesis summary for Part V is included in a single Chapter 10. It outlines the key findings from the study and points out the issues that still need to be addressed to further this field of study. Description: NITW 2024-01-01T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3503 Title: Linear Stability of Convection in an Inclined Porous Channel Filled with Nanofluid, Casson Fluid, and Dusty Fluid Authors: HUMNEKAR, NIDHI Abstract: In recent years, the study of convective transport through porous media has emerged as an intriguing and significant subject, owing to its relevance in various industrial and engineering applications. Additionally, the exploration of convective instability in fluid-saturated porous layers, heated from below, has long captivated the attention of researchers across different physical conditions. This field finds extensive utility in geophysics, food processing, oil reservoir modeling, thermal insulation construction, and nuclear reactors. Understanding the mechanism of instability in incompressible nanofluid, Casson fluid, and dusty fluid flows through porous media is of utmost importance due to its practical implications in engineering. Nanofluids, which are created by uniformly dispersing and suspending metallic particles on a nanometer scale in conventional heat transfer fluids like water, oil, or ethylene glycol, are particularly relevant and Casson fluid refers to a type of non-Newtonian fluid that exhibits a non-linear relationship between shear stress and shear rate. The primary objective of this thesis is to conduct a linear stability analysis of incompressible nanofluid, Casson fluid and dusty fluid flows in an inclined channel filled with a porous medium. This thesis is organized into four parts and fourteen chapters. Part- I is composed of a single chapter, Chapter 1. This chapter serves as an introduction and covers several concepts, including nanofluid, Casson fluid, dusty Casson fluid, and porous medium. Additionally, it includes a review of relevant literature related to these topics. Part-II contains six chapters, namely Chapters 2, 3, 4, 5, 6 and 7. Chapter- 2 investi gates convective stability of nanofluid flow in inclined porous channel, considering Brownian motion, thermophoresis, and Brinkman’s equation. In Chapter- 3, deals the impact of local thermal non-equilibrium (LTNE) on nanofluid flow stability in an inclined channel filled with a porous medium. Chapter- 4 considers the effects of double diffusion and a magnetic field on the stability of nanofluid flow in an inclined porous channel. Chapter 5 investigates the effect of variable viscosity on the stability of nanofluid flow in an inclined porous channel. Chapter- 6 investigates numerically the local thermal non-equilibrium state of the fluid, par ticle, and solid-matrix phases for the stability of nanofluid flow in an inclined channel with variable viscosity filled with a porous medium. In Chapter- 7, the effects of double diffu sion and variable viscosity on the stability of a nanofluid-saturated Darcy-Brinkman porous medium in an inclined channel are investigated. Part III comprises three chapters, namely Chapters 8, 9, and 10. Chapter 8 delves into the examination of the stability of Casson fluid flow in an inclined channel with a highly permeable porous medium. The analysis takes into account the presence of a heat source or vi sink. In Chapter 9, the investigation shifts towards exploring the stability of Casson fluid f low in an inclined porous channel, considering the effects of chemical reaction and radiation. Chapter 10 is dedicated to investigating the impact of variable viscosity on the stability of Casson fluid flow in an inclined porous channel. Part-IV contains three chapters, namely Chapters 11, 12, and 13. In Chapter 11, the focus shifts to the investigation of the impact on the stability of two-phase dusty Casson f luid flow in an inclined porous channel. In Chapter 12, the emphasis is placed on studying the impact of variable viscosity on the stability of two-phase dusty Casson fluid flow in an inclined porous channel. Chapter 13 discusses the impact of heat source/sink and radiation on the stability of two-phase dusty Casson fluid flow in an inclined porous channel. In each of the preceding chapters, the non-linear governing equations and their associated boundary conditions are initially cast into dimensionless form through a suitable set of non-dimensional transformations and then converted into a system of linear ordinary differential equations by linear stability analysis and the normal mode technique. Chebyshev’s spectral collocation method is used to solve the resultant system of ordinary differential equations. The impact of relevant parameters on the onset of convection is depicted in graphs and tables. In addi tion, for some problems, the pattern of streamlines, isotherms, and isonanoconcentrations is plotted at a critical level over a single period. Part V is comprised of a solitary chapter, namely Chapter 14, which serves the purpose of summarizing the research findings, presenting overall conclusions, and future work scope Description: NITW 2024-01-01T00:00:00Z