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Methodologies and Applications of Computational Statistics for Machine Intelligence
With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past. Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians. 2021, IGI Global. All rights reserved. -
Methods and model for worklife balance of women entrpreneurs /
Patent Number: 202011039249, Applicant: Dr. Purvi Pareek.
The increase in the rate of capital formation is an integral part of the economic development of a country. An women entrepreneur stimulates the economic forces in capital formation through his undertakings. When there is industrial development by means of establishing new industries at different locations, employment is generated, regional disparity is reduced and the better standard of living is achieved. -
METROLOGICAL IMPACT ON ORANGE FRUIT: A COMPARATIVE ANALYSIS OF DEEP LEARNING MODELS FOR PREDICTING FRUIT DISEASES
This research offers a comprehensive comparative analysis of efficient deep learning models for predicting diseases in orange fruits, with a particular emphasis on the impact of meteorological factors on disease prevalence. Citrus diseases such as Blackspot, Canker, and Greening are significantly influenced by environmental conditions. Recognizing the crucial role of weather conditions in the development and spread of these diseases, we concentrate on enhancing prediction accuracy by integrating Convolutional Neural Networks (CNNs) with various classification algorithms to develop hybrid models that account for meteorological impacts. Specifically, we assess the performance of a CNN combined with Gradient Boosting (CNN-GB) and compare it against other hybrid models such as CNN integrated with Long Short-Term Memory networks (CNN-LSTM), Support Vector Machines (CNN-SVM), and Random Forest classifiers (CNN-Random Forest). These models are evaluated using different optimization algorithms to determine the most effective approach for disease prediction under varying meteorological conditions. A meticulously curated dataset comprising 1,600 training images and 300 testing images of orange fruits exhibiting a variety of disease symptoms was utilized for evaluation. The dataset reflects diverse environmental conditions to capture the meteorological impact on disease manifestation. All the models tested, the CNNGB hybrid model with NDAM optimizer exhibited superior performance (Accuracy 98.03) in comparison of other models like CNN (Accuracy 96.03), CNN+LSTM (Accuracy 96.16), CNN + SVM (Accuracy 97.13) and CNN + Random Forest (Accuracy 97.79). The exceptional performance of the CNN-GB model suggests that integrating CNNs with powerful classification algorithms like Gradient Boosting, along with considerations of meteorological data, can significantly enhance disease detection in crops. This advancement contributes to more proactive and effective disease management strategies, ultimately reducing economic losses and increasing productivity in the agricultural sector. 2025 Published by Faculty of Engineering. -
METROLOGICAL IMPACT ON ORANGE FRUIT: A COMPARATIVE ANALYSIS OF DEEP LEARNING MODELS FOR PREDICTING FRUIT DISEASES
This research offers a comprehensive comparative analysis of efficient deep learning models for predicting diseases in orange fruits, with a particular emphasis on the impact of meteorological factors on disease prevalence. Citrus diseases such as Blackspot, Canker, and Greening are significantly influenced by environmental conditions. Recognizing the crucial role of weather conditions in the development and spread of these diseases, we concentrate on enhancing prediction accuracy by integrating Convolutional Neural Networks (CNNs) with various classification algorithms to develop hybrid models that account for meteorological impacts. Specifically, we assess the performance of a CNN combined with Gradient Boosting (CNN-GB) and compare it against other hybrid models such as CNN integrated with Long Short-Term Memory networks (CNN-LSTM), Support Vector Machines (CNN-SVM), and Random Forest classifiers (CNN-Random Forest). These models are evaluated using different optimization algorithms to determine the most effective approach for disease prediction under varying meteorological conditions. A meticulously curated dataset comprising 1,600 training images and 300 testing images of orange fruits exhibiting a variety of disease symptoms was utilized for evaluation. The dataset reflects diverse environmental conditions to capture the meteorological impact on disease manifestation. All the models tested, the CNNGB hybrid model with NDAM optimizer exhibited superior performance (Accuracy 98.03) in comparison of other models like CNN (Accuracy 96.03), CNN+LSTM (Accuracy 96.16), CNN + SVM (Accuracy 97.13) and CNN + Random Forest (Accuracy 97.79). The exceptional performance of the CNN-GB model suggests that integrating CNNs with powerful classification algorithms like Gradient Boosting, along with considerations of meteorological data, can significantly enhance disease detection in crops. This advancement contributes to more proactive and effective disease management strategies, ultimately reducing economic losses and increasing productivity in the agricultural sector. 2025 Published by Faculty of Engineering. -
MHD flow and nonlinear thermal radiative heat transfer of dusty prandtl fluid over a stretching sheet
Boundary layer flows and melting heat transfer of a Prandtl fluid over a stretching surface in the presence of fluid particle suspensions has been investigated. The converted set of boundary layer equations are solved numerically by RKF-45 method. Obtained numerical results for flow and heat transfer characteristics are deliberated for various physical parameters. Furthermore, the skin friction coefficient and Nusselt number are also presented in Tabs. 2 and 3. It is found that the heat transfer rates are advanced in occurrence of nonlinear radiation compered to linear radiation. Also, it is noticed that velocity and temperature profile increases by increasing Prandtl parameter. 2020 Tech Science Press. -
MHD flow of SWCNT and MWCNT nanoliquids past a rotating stretchable disk with thermal and exponential space dependent heat source
The main purpose of this investigation is to analyze the impacts of a novel exponential space dependent heat source on MHD slip flow of carbon nanoliquids past a stretchable rotating disk. The flow is created due to rotation and stretching of the disk. Aspects of the convective condition and cross-diffusion (Soret and Dufour effects) are also accounted. A comparative study of nanofluids made up of SWCNTs (single-walled carbon nanotube) and MWCNTs (multi-walled carbon nanotube) is presented. The governing partial differential equations system is reduced to nonlinear ordinary boundary value problem. The RungeKuttaFehlberg is utilized for numerical simulations. Embedded dimensionless parameters on the flow fields are examined via graphical illustrations. The rate of heat mass transfer can be controlled by cross-diffusion, exponential space-based heat source and thermal-based heat source effects. It is also proved that q( ) (? ) x q x SWCNT nanoliquid MWCNT nanoliquid -. A novel idea of the exponential space dependent heat source is implemented in the investigation of the slip flow over a rotating deformable disk under the effects of cross-diffusion, temperature based heat source and magnetic field for the first time. A comparison between two different fluids namely SWCNT-H2O nanoliquid and MWCNT-H2O nanoliquid are studied. 2019 IOP Publishing Ltd Printed in the UK. -
MHD Maxwell nanofluid flow over a porous conical surface: A fractional approach
The current novel study focuses on the two-dimensional magnetohydrodynamic flow of fractional Maxwell nanofluid through porous conical geometry under convective boundary conditions. The nanofluids considered for the study are suspensions of single and multi-walled carbon nanotubes with blood as the base fluid. Fractional-ordered governing equations are transfigured into non-dimensional forms using appropriate transformations. The finite difference approximations are obtained by discretizing the momentum and energy profiles. The results of both profile are plotted against various physical flow-pertaining parameters. It is evident, that multi-walled carbon nanotubes consistently show higher velocity profiles and lower temperature phases than single-walled carbon nanotubes nanofluid across all embedded parameters. Further, the study revealed that the absence of magnetic parameter improves by 11.36% of velocity distribution and the presence of heat source parameter improves by 18.37% of temperature distribution. This framing highlights the convergence criterion of the findings with previous work, emphasizing both reliability and accuracy within the range of 10?4 to 10?6. Graphical representation concludes that the model involving the fractional technique is superior to the integer one. Thus, achievement demonstrates practical application potential in optimizing the efficiency of fluid heating and cooling processes, underscoring its importance in thermal management. 2025 -
MHD nanofluid flow past a rotating disk with thermal radiation in the presence of aluminum and titanium alloy nanoparticles
The effects of thermal and exponential space dependent heat sources (THS and ESHS) on magneto-nanoliquid flow across a rotating disk with uniform stretching rate along radial direction are scrutinized in this communication. H2O based nanoliquids containing aluminium (AA 7075) and titanium (Ti6Al4V) alloy nanoparticles are considered. The AA7075 is made up of 90% Al, 5-6% Zn, 2-3% Mg, 1-2% Cu with additives such as Fe, Mn and Si etc. The flow is driven due to rotating disk with uniform stretching of the disk. Impacts of Joule and viscous heating are also deployed. The multidegree ordinary differential equations are formed via Von Karman transformations. The obtained non-linear BVP is solved by Runge-Kutta-Fehlberg based shooting approach (RKFS). Graphical illustrations depict the impacts of influential parameters on flow fields. The skin friction and Nusselt number are also calculated. Results pointed out that the thermal boundary layer growth stabilizes due to the influence of ESHS aspect. Velocities of AA7075 H2O nanofluid are superior than that of Ti6 Al4V H2O nanoliquid. Furthermore, the thermal performance of base liquid is outstanding when we added titanium alloy nanoparticles in comparison with aluminium alloy nanoparticles. 2018 Trans Tech Publications, Switzerland. -
MHD nanofluid flow through Darcy medium with thermal radiation and heat source
In this analysis, we have considered heat transmission in two-dimensional steady laminar nanouid ow past a wedge. Magnetohydrodynamic (MHD), Brownian motion, viscous dissipation and thermophoresis eects are considered over the porous surface. Similarity transformations have been used to change the governing partial dierential equations (PDEs) into nonlinear higher-order ordinary dierential equations (ODEs). Governing ODEs with boundary conditions are then converted to the system of first-order initial value problem. After that the modeled system is solved numerically by RK4 technique. Impact of the magnetic number, Eckert number, Prandtl number, Lewis number, Brownian motion, thermophoresis and permeability parameters on the ow domain is analyzed graphically as well as in tabular form. It is noted that magnitude of Nusselt number for the ow regime increases with the increase of nondimensional parameter Pr; Nb; Nt while opposite behavior is observed in case of R. World Scientific Publishing Company. -
Micro and nano Bi2O3 filled epoxy composites: Thermal, mechanical and ?-ray attenuation properties
Polymer composites have attracted considerable attention as potential light-weight and cost-effective materials for radiation shielding and protection. In view of this, the present work focusses on development of lead-free composites of diglycidyl ether of bisphenol A (DGEBA) epoxy resin with micro (~ 10 ?m) and nano (~ 20 nm) bismuth (III) oxide (Bi2O3) fillers, using solution casting technique. Thermal, mechanical and ?-ray attenuation properties of the composites were studied by varying the filler loading. Inclusion of the fillers into epoxy matrix was confirmed both structurally and morphologically by XRD and SEM, respectively. Thermogravimetric analysis (TGA) showed the thermal stability of composites to be as high as 400 C. The nanocomposites exhibited relatively higher thermal stability than their micro counterparts. Among the composites, 14 wt% nano-Bi2O3/epoxy composites showed highest tensile strength of 326 MPa, which is about 38% higher than 30 wt% micro Bi2O3/epoxy composites. Mass attenuation coefficients (?/?) of the composites were evaluated at ?-ray energies ranging from 0.356 to 1.332 MeV. Nanocomposites showed better ?-ray shielding at all energies (0.356, 0.511, 0.662, 1.173, 1.280 and 1.332 MeV) than micro composites with same filler loading. These studies revealed the significance of nano-sized fillers in enhancing overall performance of the composites. 2021 Elsevier Ltd -
Micro Borrowing an Amalgam of Structure and Strategy: Evidence from India
Micro borrowing was either an outcome of structure in the credit environment (termed the outreach stream), or a strategic response of the borrowers (termed the sustainability stream). Furthermore, borrower personal effects drove borrowing behaviour. This study draws variables from both the streams of literature and tests them against the amount borrowed and purposes loans are borrowed for. Results show how borrowing behaviour is neither an outcome of pure structure nor pure strategy, but rather, is an interplay of both, and further influenced by personal effects. The survey data (consisting of 839 rural borrower responses, from four districts of erstwhile Andhra Pradesh in South India) was subjected to a rigorous statistical analysis. Results show how a larger number of banks in the villages (a structural constraint), enabled the borrowers to receive larger loans, who defaulted more (a strategic response). Men borrowed larger sums (a personal effect). A similar amalgam of structure, strategy and personal effects drive borrowing behaviour even after controlling for loan purpose and district fixed effects. Yet, when district effects are introduced, amount borrowed is agnostic to personal effects, and is driven purely by structure and strategy. JEL Classifications: C25, C83, G51, Z13 2022 SAGE Publications India Pvt. Ltd. -
Micro Borrowing an Amalgam of Structure and Strategy: Evidence from India
Micro borrowing was either an outcome of structure in the credit environment (termed the outreach stream), or a strategic response of the borrowers (termed the sustainability stream). Furthermore, borrower personal effects drove borrowing behaviour. This study draws variables from both the streams of literature and tests them against the amount borrowed and purposes loans are borrowed for. Results show how borrowing behaviour is neither an outcome of pure structure nor pure strategy, but rather, is an interplay of both, and further influenced by personal effects. The survey data (consisting of 839 rural borrower responses, from four districts of erstwhile Andhra Pradesh in South India) was subjected to a rigorous statistical analysis. Results show how a larger number of banks in the villages (a structural constraint), enabled the borrowers to receive larger loans, who defaulted more (a strategic response). Men borrowed larger sums (a personal effect). A similar amalgam of structure, strategy and personal effects drive borrowing behaviour even after controlling for loan purpose and district fixed effects. Yet, when district effects are introduced, amount borrowed is agnostic to personal effects, and is driven purely by structure and strategy. JEL Classifications: C25, C83, G51, Z13 The Author(s) 2022 -
Micro grid Communication Technologies: An Overview
Micro grid is a small-scale power supply network designed to provide electricity to small community with integrated renewable energy sources. A micro grid can be integrated to the utility grid. Due to lack of computerized analysis, mechanical switches causing slow response time, poor visibility and situational awareness blackouts are caused due to cascading of faults. This paper presents a brief survey on communication technologies used in smart grid and its extension to micro grid. By integration of communication network, device control, information collection and remote management an intelligent power management system can be achieved 2022 IEEE. -
Micro-credentials in todays education
In addition, for todays students and professionals constrained by job commitments or those seeking to acquire niche or specialised skills, micro-credentials (MCs) have emerged as a crucial innovation in online education. -
Micro-finance institutions and women's entrepreneurship in India
Microfinance institutions are considered a miracle to reduce poverty, promote empowerment, reducing gender inequality by providing microcredit and other financial services to strata of people outside the ambit of the formal financial system. Such micro-credit and other services lead to promoting entrepreneurship ventures among women leading to financial freedom and economic development of the country. This chapter studied the status of microfinance institutions across all continents and their pace of evolution with respective objectives. India-specific mission objectives and business models of microfinance institutions were dealt with in detail. 200 literatures based on the keywords related to the theme of chapter titles were fetched from the Scopus database and were subjected to cooccurrence analysis using network visualization on VOS viewer software. Microfinance has been identified as one of the important tools for poverty reduction and women's empowerment by promoting women entrepreneurship. 2025 by IGI Global Scientific Publishing. -
Microaggression and Its Impact on Lower Caste Women with Psychiatric Disorders in India
This article presents a collection of personal stories of Dalit women highlighting their daily experiences of microaggressions, which they did not even realize or endured in silence, but how it left deep psychological, emotional, and relational scars. These experiences are examined from a postmodern theory perspective. In addition, the article will describe Anderson Franklin and Nancy Boyd-Franklins theoretical concepts of invisibility and Kenneth Hardys concepts of voicelessness and psychological homelessness. These stories indicated that having mental illness defined these women, leading to a lack of opportunities and resources and further chipping away at their sense of self, capabilities, and value. As a therapist, the primary author felt drawn to connect with these womens humanity, suffering, and pain, but also felt vulnerable to seeing them as different and ignoring the fact that she exercised power by categorizing them as low-income, Dalit, and traumatized. By seeing these women differently, the primary author felt less vulnerable and safer in a therapeutic relationship but also realized how language in therapy reinforces the internal psychological and emotional experience of being invisible and thus unimportant. Mental health professionals should use caste-sensitive language and adopt caste-affirmative therapy to prevent the drop-out of these women from therapy. Copyright 2025, Mary Ann Liebert, Inc., publishers. -
Microalgae as Biorefineries for Biofuel and Bioenergy Production: Recent Developments and Future Prospects
Microalgae boasts unique advantages regarding biofuel production, where researchers have made significant strides in increasing biofuel yields while reducing costs by improving lipid profiles in various microalgal strains, incorporating nano-additives, and improving extraction techniques. They have achieved this through genetic engineering, nanotechnology, and innovative cultivation techniques, optimizing the entire process. Moreover, microalgae are rich in bioactive compounds, and this chapter emphasizes advanced methods for extracting and purifying compounds like carotenoids, phycobiliproteins, polysaccharides, and omega-3 fatty acids, which have broad applications in food, medicine, and various industries. In energy production, microalgae generate renewable and eco-friendly energy through microbial fuel cells, employing techniques such as thermochemical liquefaction and producing energy from fermentation processes. Advancements in microalgae-based photobioreactors and strategies to improve photosynthetic efficiency further contribute to the efficiency and scalability of energy production. The book chapter highlights the importance and sustainability of microalgae in addressing energy and environmental challenges. By harnessing the latest advancements in biofuel production, valuable product synthesis, and renewable energy generation, microalgae have the potential to steer in a greener and brighter future. Their rapid growth, carbon dioxide absorption, and valuable compound synthesis make them a powerful tool in our pursuit of sustainable solutions. Embracing the potential of microalgae can lead us to an environmentally friendly and economically prosperous future. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Microalgae: a promising tool for plastic degradation
The use of plastics in the present-day routine is an unavoidable part of human life. It is posing a global environmental threat due to its never-ending accumulation. Complete disposal of plastics is a major problem, and for their complete degradation an effective solution or method has not been discovered yet. However, in order to turn to a biological approach for coping with the ever-increasing fear of plastic aggregation and decay, the development of a methodology would be useful for posterity. To eliminate plastic wastes, two scenarios exist: produce biodegradable plastics from renewable materials or fossil fuels as building blocks, such as hydrobiodegradable/oxo-biodegradable; or find appropriate microalgae and their toxins for the development of a protocol to effectively biodegrade the plastics. Just as biodegradation of plastics is a constructive option, as they are eco-friendly with not much harm done to the environment, the development of biodegradable plastic is also equally effective. Some of the algae that are isolated from the plastic wastes are green-algae, blue-green algae, diatoms, etc. Polyethylene is basically carbon and hydrogen polymer, which is exceptionally resistant to biodegradation (less than 0.5% over 100 years), whose degradation is dependent mainly on moisture, light, and temperature. The most used types of plastics like polyethylene terephthalate and polypropylene are a major threat as they are used in the manufacture of bottles, fibers, packing materials, etc. The degradation or disposal of these plastics is leading to their conversion into microsized particles which is further leading to harm to the environment, mainly when these microplastics interact with microalgae like Spirulina. However, landfill, incineration, and chemical methods are some of the conventional methods for polyethylene disposal that are fatal to the environment as they cause hazardous effects on flora and fauna. 2022 Elsevier Inc. All rights reserved. -
Microbial biofertilizers: A sustainable agricultural approach to augment crop resilience against biotic and abiotic stresses
Increasing plant growth and yield with the aid of plant growth-promoting bacteria is a widely accepted, eco-friendly and economic approach in modern agriculture. Their use as an alternative to widely used harmful chemical fertilizers and pesticides can improve overall soil health and fertility, thereby enhancing crop yield. The positive modulation of genes related to growth and development, fruit formation, stress tolerance and phytohormone production helps plants significantly during maturation. Furthermore, the enhanced production and expression of defence-related hormones aid in survival under various stress conditions, such as drought, pH fluctuations, salinity and water stress. In addition, the application of growth-promoting bacteria, mainly from species such as Azospirillum, Bacillus, Klebsiella, Enterobacter, Pseudomonas, Azotobacter, Burkholderia, Rhizobium, Alcaligenes, Arthrobacter and Serratia supports plant growth and development by improving soil porosity, pH and salinity conditions. This review briefly outlines the role of the plant growth-promoting bacteria as microbial biofertilizers that enhance crop resilience under both biotic and abiotic stress conditions. By highlighting recent advances in understanding the mechanisms of microbe-plant interactions under these stresses, it also provides unique insights into how microbial biofertilizers can be employed for sustainable agriculture. This has direct relevance for policymakers and farmers by reducing dependence on chemical fertilizers, which have various negative impacts, thereby promoting long-term environmental sustainability and improved agricultural practices. (2025), (Science Press). All rights reserved. -
Microbial Decomposition of Feather Waste
Keratin is generally found as an ?-keratin helix form in hair, nails, horns and ?-keratin sheet form found in feathers, scales, beaks and claws. ?-keratin contains a domain rich in residues favoring to form ?-sheet structures associated with the filament framework. 'N' and 'C' terminal domains are associated with the matrix and forms cross-linking via disulfide bonds. Several million tons of feather waste are generated by poultry industries each year. Since this waste is rich in protein, it contains excellent potential as a protein source for animal feed and other applications.Bacterial and fungal strains used in microbial degradation of feathers are summarized. Various species from the bacterium genus are involved in keratin degradation including Bacillus, Stenotrophomonas, Pseudomonas, Brevibacillus, Fusarium, Geobacillus, Chryseobacterium, Xanthomonas and Serratia which are some keratin degrading bacteria. Actinomycetes and fungi also contribute to feather degradation by the enzyme activity of keratinases. 2022 World Research Association. All rights reserved.