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Masked Face Recognition and Liveness Detection Using Deep Learning Technique
Face recognition has been the most successful image processing application in recent times. Most work involving image analysis uses face recognition to automate attendance management systems. Face recognition is an identification process to verify and authenticate the person using their facial features. In this study, an intelligent attendance management system is built to automate the process of attendance. Here, while entering, a persons image will get captured. The model will detect the face; then the liveness model will verify whether there is any spoofing attack, then the masked detection model will check whether the person has worn the mask or not. In the end, face recognition will extract the facial features. If the persons features match the database, their attendance will be marked. In the face of the COVID-19 pandemic, wearing a face mask is mandatory for safety measures. The current face recognition system is not able to extract the features properly. The Multi-task Cascaded Convolutional Networks (MTCNN) model detects the face in the proposed method. Then a classification model based on the architecture of MobileNet V2 is used for liveness and mask detection. Then the FaceNet model is used for extracting the facial features. In this study, two different models for the recognition have been built, one for people with masks another one for people without masks. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Mass layoffs at BYJUS founders dilemma
Learning outcomes: This case study provides students/managers an opportunity to learn about the following: to infer the challenges involved in the downsizing of employees; to asses and evaluate BYJUS organizational culture; and to determine the impact of workplace toxicity. Case overview/synopsis: The focus of this case is the controversy faced by BYJUS due to its mass layoffs and toxic work culture. This case discusses the CEOs dilemma in resolving the controversy. Two rounds of mass layoffs at BYJUS are discussed in detail. The industrial dispute filed by Employees Union against BYJUS accusing it of denying due compensation to laid-off employees is also discussed. This case consists of a section explaining the toxic work culture at BYJUS, which is supported by employee complaints. The CEOs justification and apology have been illustrated in this case. The case ends with a closing dilemma and challenges faced by the CEO. Complexity academic level: The case is best suited for undergraduate students studying Human Resources Management subjects in Commerce and Business Management streams. The authors suggest that the instructor inform students to read the case before attending the 90-min session. It can be executed in the classroom after discussing the theoretical concepts. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2024, Emerald Publishing Limited. -
Masstige consumption in the emerging market: mediating effects of brand happiness and moderating role of age
Purpose This study investigates how Indian consumers evaluate local and foreign cosmetic brands, focusing on brand prestige, loyalty and evangelism. It explores brand happiness as a mediating variable and age as a moderating factor within the masstige consumption context in an emerging market. Design/methodology/approach A two-phase empirical approach was adopted. Phase 1 involved a comparative analysis of marketing strategies across Lakmand international brands (MAC, L'Orl Paris, and Maybelline) using a total sample of 573 female consumers. In Phase 2, only the high masstige brands (MAC and L'Orl Paris) were retained, and responses from 244 participants were analyzed using structural equation modeling to examine the mediating role of brand happiness and the moderating effect of age. Findings Indian consumers perceive foreign brands like MAC and L'Orl Paris as masstige brands. Masstige brand consumption significantly enhances brand happiness and brand loyalty, while its influence on brand evangelism is fully mediated through brand happiness and brand loyalty. Brand happiness partially mediates the relationship between masstige consumption and brand loyalty, and also indirectly affects brand evangelism through brand loyalty. Age weakens the effect of masstige consumption on loyalty but strengthens the effects of brand happiness on loyalty and brand loyalty on evangelism. Originality/value This study extends masstige marketing literature by integrating emotional (brand happiness) and demographic (age) variables into the brand prestigeloyaltyevangelism framework. It offers practical insights for global and local brands aiming to enhance consumer engagement in emerging markets through differentiated brand strategies. 2025 Emerald Publishing Limited -
Masstige scale: An alternative to measure brand equity
Masstige marketing is a strategic word for market penetration for premium but reachable products based on brand equity, trying to develop brand awareness, likability, affection and attachment. Hence, masstige scale may allow firms to measure brand equity to derive insights into the popularity of their brands. However, there is no empirical evidence available to test whether these scales are related measures of brand equity and, at the same time, independent measures, respectively. This study investigates whether the masstige scale and multidimensional consumer-based brand equity scale measure the same constructs. A total of 493 participants evaluated four different athletic shoe brands. The multi-trait, multimethod and confirmatory factor analyses suggested that the masstige scale may be a viable alternative to consumer-based brand equity and masstige value. We discuss the implications and provide directions for future research derived from our findings. 2022 John Wiley & Sons Ltd. -
Maternal circulating sFlt-1/placental growth factor is a biomarker of fetal death associated with placental lesions of maternal vascular malperfusion
Objectives: Fetal death is a major pregnancy complication, with rates of 5.5 per 1,000 births in the United States and substantially higher in India (24.7/1,000) and Pakistan (44.5/1,000). Maternal vascular malperfusion (MVM) is the most frequent placental lesion associated with fetal death, occurring in 58 % of fetal deaths and 31 % of preterm neonatal deaths in South Asia. Angiogenic imbalance, characterized by a low placental growth factor (PlGF) to soluble fms-like tyrosine kinase-1 (sFlt-1) ratio, has been associated with MVM and fetal death in high-income countries. We examined whether maternal serum concentrations of PlGF, sFlt-1, and their ratio differ between mothers with and without MVM among stillbirths and preterm neonatal deaths in India and Pakistan. Methods: This retrospective cohort analysis used data from the PURPOSe study (Project to Understand and Research Preterm Pregnancy Outcomes and Stillbirths in South Asia). Maternal blood was collected at delivery, and placental histopathology was classified according to the Amsterdam criteria. Serum PlGF and sFlt-1 were measured using Elecsys immunoassays, with analyses stratified by gestational age. Results: Placental MVM was present in 44-57 % of stillbirths and 31-38 % of preterm neonatal deaths. Between 28 and 36 weeks, women with MVM had significantly lower PlGF and higher sFlt-1 and sFlt-1/PlGF ratios (p<0.001). A tenfold decrease in PlGF or increase in the ratio was associated with MVM (OR 0.5 and 1.7, respectively). Conclusions: The maternal sFlt-1/PlGF ratio identifies pregnancies with fetal or neonatal death associated with placental MVM, particularly between 28 and 36 weeks' gestation. 2025 the author(s) -
Mathematical analysis of histogram equalization techniques for medical image enhancement: a tutorial from the perspective of data loss
This tutorial demonstrates a novel mathematical analysis of histogram equalization techniques and its application in medical image enhancement. In this paper, conventional Global Histogram Equalization (GHE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Histogram Specification (HS) and Brightness Preserving Dynamic Histogram Equalization (BPDHE) are re-investigated by a novel mathematical analysis. All these HE methods are widely employed by researchers in image processing and medical image diagnosis domain, however, this has been observed that these HE methods have significant limitation of data loss. In this paper, a mathematical proof is given that any kind of Histogram Equalization method is inevitable of data loss, because any HE method is a non-linear method. All these Histogram Equalization methods are implemented on two different datasets, they are, brain tumor MRI image dataset and colorectal cancer H and E-stained histopathology image dataset. Pearson Correlation Coefficient (PCC) and Structural Similarity Index Matrix (SSIM) both are found in the range of 0.6-0.95 for overall all HE methods. Moreover, those results are compared with Reinhard method which is a linear contrast enhancement method. The experimental results suggest that Reinhard method outperformed any HE methods for medical image enhancement. Furthermore, a popular CNN model VGG-16 is implemented, on the MRI dataset in order to prove that there is a direct correlation between less accuracy and data loss. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Mathematical and computational analysis of a fractional-order drug abuse model with nonlinear incidence and logistic growth
This paper presents a novel mathematical model for analyzing the dynamics of drug addiction using a fractional-order system based on the LiouvilleCaputo derivative. The proposed model incorporates a nonlinear saturated incidence rate, logistic growth in the addiction compartments, and seven interconnected subpopulations representing different stages of drug use and recovery, including relapse and awareness. We conduct a rigorous mathematical analysis to establish the existence, uniqueness, positivity, and boundedness of solutions, ensuring the epidemiological and physical validity of the model. The basic reproduction number R0 is derived, and the local and global stability of the equilibrium points is analyzed. A major contribution of this work is the application of a new domain decomposition spectral method based on second-kind Dickson polynomials, combined with the quasilinearization technique, to efficiently solve the complex nonlinear system. The convergence of the numerical method is theoretically validated. Numerical simulations are provided to illustrate the model's dynamics and to explore the impact of various parameters and intervention strategies. Compared to existing models, this study offers an improved framework for understanding memory-dependent behavior in addiction dynamics and introduces a computationally efficient approach to solve fractional-order systems with high accuracy. 2025 International Association for Mathematics and Computers in Simulation (IMACS) -
Mathematical and prosodic analysis of intonation in Malayalam
This study investigates the intonation patterns of Malayalam, a language spoken in Kerala, India, using polynomial regression and Kernel Density Estimation. Malayalam has distinct pitch modulation patterns across genders and question types, with variations in acoustic features, syllables, and stress structures. We examine the mean pitch characteristics of different question types and analyze the correlation between stress patterns and syllable structure counts in the language. Additionally, we perform clustering analysis on Malayalam words to highlight similarities and diversities in acoustic features, which helps us understand the phonetic diversity within the language. Our analysis shows that the overlap of KDE curves in the feature space allows us to analyze the linguistic factors that influence variability in Malayalam speech. This suggests a need for further research on regions where syllable complexity and phonological patterns are notably concentrated. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
Mathematical approach for impact of media awareness on measles disease
During the recent pandemic caused by COVID-19, media awareness played a crucial role in educating people about social distancing, wearing masks, quarantine, vaccination, and medication. Media awareness brought individual behavioral changes among the people, which in turn helped reduce the infection rate. Motivated by this, we have formulated a mathematical model introducing a media compartment to mitigate measles disease transmission. In this paper, the SEIR model is used to study measles disease in three cases: one with a delay in vaccination, the second with regular vaccination, and the third with the impact of media awareness on the spreading of measles disease. Further, the dynamical behavior of the models is studied in terms of positivity, boundedness, equilibrium, and basic reproduction number (BRN). The sensitivity analysis of the models is conducted, which verifies the importance of the BRN ((Formula presented.)) to be less than one for disease eradication. The numerical study confirms the impact of media awareness on exposed and infected populations. 2023 John Wiley & Sons Ltd. -
Mathematical Capabilities of LLMs
Large language models (LLMs) have the potential to solve mathematical problems well, but little has been investigated. In this research, we evaluate five leading LLMs - (Gemini, Claude, Mistral, ChatGPT, and Llama - on a set of 50 mathematical problems that cover calculus, algebra, geometry, number theory, and probability. Finally, the study evaluates the accuracy of their solutions and gives the ability to assess their intermediate steps correctly. I created a primary dataset for comparison of the LLM performances and ranked the models according to how well they were able to solve those problems. It illustrates the shortcomings of present LLMs at reasoning and solving for mathematics and suggests what needs to be rectified in the LLMs. Future research will further refine this dataset and monitor the progression of LLM capabilities in solving more complex mathematical problems. 2025 IEEE. -
Mathematical foundations based statistical modeling of software source code for software system evolution
Source code is the heart of the software systems; it holds a wealth of knowledge that can be tapped for intelligent software systems and leverage the possibilities of reuse of the software. In this work, exploration revolves around making use of the pattern hidden in various software development processes and artifacts. This module is part of the smart requirements management system that is intended to be built. This system will have multiple modules to make the software requirements management phase more secure from vulnerabilities. Some of the critical challenges bothering the software development community are discussed. The background of Machine Learning approaches and their application in software development practices are explored. Some of the work done around modeling the source code and approaches used for vulnerabilities understanding in software systems are reviewed. Program representation is explored to understand some of the principles that would help in understanding the subject well. Further deeper dive into source code modeling possibilities are explored. Machine learning best practices are explored inline with the software source code modeling. 2022 the Author(s), licensee AIMS Press. -
Mathematical model for effective CO2 emission control with forest biomass using fractional operator
The emission of CO2 is the foremost culprit for global warming and is also considered a significant greenhouse gas. Due to the human populations tremendous growth and activities, the rate of CO2 in the atmosphere has increased. To mitigate the emission of CO2 there are artificial ways. But, naturally have a natural resource called "Forest Biomass," one of the significant sinks to absorb CO2 during photosynthesis. Considering all these factors, the main objective of the current investigation is to understand and illustrate the importance of forest biomass in the emission of CO2. The proposed nonlinear model consists of four variables: atmospheric CO2, human population, energy sectors, and forest biomass. We have studied the model both qualitatively and quantitatively, which will help us make future predictions. To study the model in depth, we have formed a fractional-order model to study the systems behavior at different ranges of fractional orders. The model is termed with the Caputo fractional operator. Boundness and Lyapunov stability for non-linear and fractional order models are studied, and equilibrium points, existence and uniqueness, and numerical simulation are examined. The Adams-Bashforth-Moulton method illustrates the essence of the systems numerical method. The numerical approach reveals that the altered models stability is unchanged. Also, we have examined the model by changing the parameter values to different fractional orders to understand the systems behavior, and the changes are captured as figures. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
MATHEMATICAL MODEL OF NICKEL-GRAPHENE COMPOSITE INKS FOR JETTING PROPERTIES IN INKJET PRINTING
The droplet formation process in inkjet printing is studied numerically and verified through a simulation model. The droplet formation process decides the printing quality of the coating, and a mathematical model is developed to understand the complete process from droplet formation to detachment. The Navier-Stokes equation is used to mathematically derive the droplet radius (rnumerical). COMSOL multiphysics is used for simulation and the radius (rsimulation) is calculated from the droplet mass. The rnumerical and rsimulation are compared for inks containing nickel, graphene, and nickel-graphene composite ink it is observed that the composite ink radiuses have the lowest difference (rsimulation - rnumerical = 0.085 m). A droplet is formed at 1.47 mm from the nozzle inlet, for nickel-graphene ink, and after 1.5mm for other pristine inks. The results are verified through Z number, velocity profile, and droplet mass. The droplet formation observed from the velocity profile is earliest at 120 s. It is seen that a stable droplet is generated at 100s for nickel-graphene ink and at 200 s for individual inks. 2024 Faculty of Science, Universiti Malaya. All rights reserved. -
Mathematical Modeling for Evaluating the Mechanical Properties of High Strength Concrete with Natural Zeolite and Additives
The cement manufacturing industry is a major contributor to atmospheric pollution, primarily due to carbon dioxide emissions. Consequently, there is a pressing need to develop eco-friendly concrete capable of mitigating air pollution by sequestering atmospheric carbon dioxide. In this context, the incorporation of Natural Zeolite in concrete has been investigated, as it can absorb environmental carbon dioxide. This study explored the effects of partial cement replacement with Natural Zeolite (5%) and varying percentages of Silica Fume, Metakaolin, and Fly Ash (5%, 10%, and 15%) on the mechanical properties and carbon sequestration potential of High Strength Concrete (HSC). Comprehensive testing was conducted to evaluate the split tensile, compressive, and flexural strengths of the modified HSC. Experimental results indicated that the addition of Natural Zeolite and Metakaolin enhanced the strength of HSC, with Mix 3 displaying a higher 90-day compressive strength compared to the reference mix. The findings suggest that incorporating Natural Zeolite and other supplementary cementitious materials in concrete has the potential to alleviate environmental pollution. The dataset, comprising 900 samples, exhibited no autocorrelation or multicollinearity issues, making it suitable for multiple regression analysis. The statistically significant regression models developed in this study can effectively predict concrete strength. (2023). All Rights Reserved. -
Mathematical Modeling of Concrete Fracture Energy of Notched Specimens Using Experimental Evidence
The tensile stiffness of concrete is an important parameter for crack initiation. The microcrack initiation and propagation regulate the stressstrain behavior and the failure mode of concrete. Therefore, fundamental awareness of the fracture mechanism in terms of fracture energy is a requisite to comprehend concrete behavior. There is research consensus that fracture energy alone does not suffice to characterize the ductility/brittleness and also the size dependency of concrete. Therefore, it is necessary to evaluate the fracture energy and the characteristic length for a realistic assessment of the fracture behavior of concrete. Towards this objective, this study examined the fracture energy of concrete by experimentation, and the fracture energy proposed by various models in the literature. Further, the characteristic length proposed by Hillerborg which depicted both the material influence and the size effect, has been computed. Based on the RILEM50 FM recommendations, 18 specimens with varying grades of concrete and notch depths have been tested and the fracture energy parameters have been evaluated. Also, two regression models with key fracture parameters as variables for two-notch ratios, have been formulated for the concrete fracture energy. The arguments have been supported by experimental evidence. The Author(s), under exclusive licence to Shiraz University 2024. -
Mathematical Modeling of Concrete Fracture Energy of Notched Specimens Using Experimental Evidence
The tensile stiffness of concrete is an important parameter for crack initiation. The microcrack initiation and propagation regulate the stressstrain behavior and the failure mode of concrete. Therefore, fundamental awareness of the fracture mechanism in terms of fracture energy is a requisite to comprehend concrete behavior. There is research consensus that fracture energy alone does not suffice to characterize the ductility/brittleness and also the size dependency of concrete. Therefore, it is necessary to evaluate the fracture energy and the characteristic length for a realistic assessment of the fracture behavior of concrete. Towards this objective, this study examined the fracture energy of concrete by experimentation, and the fracture energy proposed by various models in the literature. Further, the characteristic length proposed by Hillerborg which depicted both the material influence and the size effect, has been computed. Based on the RILEM50 FM recommendations, 18 specimens with varying grades of concrete and notch depths have been tested and the fracture energy parameters have been evaluated. Also, two regression models with key fracture parameters as variables for two-notch ratios, have been formulated for the concrete fracture energy. The arguments have been supported by experimental evidence. The Author(s), under exclusive licence to Shiraz University 2024. -
Mathematical modeling to investigate the influence of vaccination and booster doses on the spread of Omicron
The emergence of new variants, such as Omicron, has raised concerns regarding the transmission dynamics of COVID-19 and the effectiveness of vaccination strategies. This paper proposes a mathematical model to investigate the impact of vaccination and booster doses on Omicron transmission dynamics, considering various infection compartments. The model incorporates multiple compartments representing different stages of infection, including susceptible individuals, vaccinated individuals, boosted individuals, and those infected with Omicron. The infection dynamics are captured by parameters such as vaccine efficacy, vaccination with booster received efficacy, and infection rate. Using mathematical analysis and numerical simulations, we explore how different vaccination and booster strategies affect the spread of Omicron. The normalized sensitivity analysis method of R0 is investigated to understand the importance of parameters in disease transmission. Furthermore, we assess the influence of infection compartments, such as asymptomatic and symptomatic cases, on overall transmission dynamics. 2023 Elsevier B.V. -
Mathematical modelling and mechanics of acoustic waves in piezoelectric layers between n-type semiconductor plates: an irreducible Cardano method coupled with a functional iteration scheme
This study presents a comprehensive analyticalnumerical investigation of acoustic wave dispersion, attenuation, and energy dissipation in piezoelectricsemiconductor heterostructures composed of SiPZTSi and GePZTGe layers. The governing electromechanicaldiffusive equations for the coupled media are formulated with full continuity conditions, leading to a cubic characteristic equation solved using a hybrid irreducible Cardano method and functional iteration scheme. A detailed convergence analysis demonstrates stable, monotonic residual decay for both symmetric and asymmetric modes, confirming the robustness of the adopted solver. Numerical results reveal strong sensitivity of phase velocity, attenuation, and specific loss to wave number, semiconductor mobility, convergence and carrier concentration. GePZTGe consistently exhibits higher phase velocity, reduced attenuation, and lower dissipative losses than SiPZTSi, primarily due to the higher carrier mobility and weaker acoustoelectric drag in Ge. Additional parametric plots highlight the influence of semiconductor quality and PZT layer thickness on acoustic energy confinement. The findings provide actionable design guidelines for optimizing SAW-based filters, delay lines, sensors, and signal-processing devices, where low loss, high velocity, and efficient energy trapping are critical. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2026. -
Mathematical Modelling of Love-Type Wave Transmission in Magnetostrictive Smart Materials with Imperfect Interface
Abstract: The purpose of this study is to investigate the propagation of Love-type surface acoustic waves through two magnetostrictive materials, NiFe2O4 (Nickel Ferrite) and Terfenol-D, embedded in a plate-substrate configuration with an imperfect interface. The study aims to investigate the effect of plate thickness, imperfect parameter, and heterogeneity parameter on both the materials under magnetically open and short scenarios. Methodology: To accomplish this, the study uses a variable-separable approach with the Direct Sturm-Liouville technique along with suitable boundary conditions, to construct frequency relations for both magnetically open and short-circuit conditions. Numerical simulations are carried out to explore the impacts of plate thickness, imperfect parameter, and heterogeneity parameter on Terfenol-D and NiFe2O4 materials under magnetically open and short circumstances. These results have been discussed through graphs that are plotted with the help of Mathematica software. Findings: The results of the study show that the phase velocity increases greater in Terfenol-D than in NiFe2O4, regardless of whether the case is magnetically open or closed. Graphical comparisons clearly demonstrate the impact of width plates, faulty parameters, and heterogeneity parameters on wave propagation characteristics. Research Limitations: The study is limited to linear wave propagation and excludes non-linear effects. Furthermore, the research is based on the attributes of the idealized material and the contact conditions. Practical implications: The findings of this study can help with the design and optimization of sensors, energy harvesters, and wave manipulation devices that use piezomagnetic materials. Understanding the behaviour of surface waves in these structures is critical for their proper use. Originality: This paper provides a complete investigation of surface wave propagation in two types of piezomagnetic composite structures, taking into account heterogeneity and interface circumstances. The comparison of several piezomagnetic models, as well as the addition of heterogeneity and contact circumstances, contribute to the researchs originality. Pleiades Publishing, Ltd. 2025. -
Mathematics as an agent of dialogue in the society
Though Mathematics is mostly considered as a subject of the intelligent, it is used by everybody for daily activities. It acts as an efficient agent of dialogue in the society. Its role in transferring abstract knowledge to concrete experience, in interpreting the unknown and as a tool for problem-solving are discussed in this paper. Mathematics also helps human beings to transcend from concrete experience to abstract knowledge. This paper showcases various elements of Mathematics over a wide spectrum, from those useful in everyday life of human beings to the discussions on potential and actual infinity. Mathematics is an integral part of human life and an essential tool in knowing the universe. We do not deliberately side with any of the schools in Mathematics or that of Philosophy. 2017 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore).