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Big Data De-duplication using modified SHA algorithm in cloud servers for optimal capacity utilization and reduced transmission bandwidth; [Big Data Deduplicaci utilizando algoritmo SHA modificado en servidores en la nube para una utilizaci tima de la capacidad y un ancho de banda de transmisi reducido]
Data de-duplication in cloud storage is crucial for optimizing resource utilization and reducing transmission overhead. By eliminating redundant copies of data, it enhances storage efficiency, lowers costs, and minimizes network bandwidth requirements, thereby improving overall performance and scalability of cloud-based systems. The research investigates the critical intersection of data de-duplication (DD) and privacy concerns within cloud storage services. Distributed Data (DD), a widely employed technique in these services and aims to enhance capacity utilization and reduce transmission bandwidth. However, it poses challenges to information privacy, typically addressed through encoding mechanisms. One significant approach to mitigating this conflict is hierarchical approved de-duplication, which empowers cloud users to conduct privilegebased duplicate checks before data upload. This hierarchical structure allows cloud servers to profile users based on their privileges, enabling more nuanced control over data management. In this research, we introduce the SHA method for de-duplication within cloud servers, supplemented by a secure pre-processing assessment. The proposed method accommodates dynamic privilege modifications, providing flexibility and adaptability to evolving user needs and access levels. Extensive theoretical analysis and simulated investigations validate the efficacy and security of the proposed system. By leveraging the SHA algorithm and incorporating robust pre-processing techniques, our approach not only enhances efficiency in data deduplication but also addresses crucial privacy concerns inherent in cloud storage environments. This research contributes to advancing the understanding and implementation of efficient and secure data management practices within cloud infrastructures, with implications for a wide range of applications and industries. 2024; Los autores. -
EGMM: removal of specular reflection with cervical region segmentation using enhanced Gaussian mixture model in cervix images
Colposcopy is a crucial imaging technique for finding cervical abnormalities. Colposcopic image evaluation, particularly the accurate delineation of the cervix region, has considerable medical significance.Before segmenting the cervical region, specular reflection removal is an efficient one. Because, cervical cancer can be found using a visual check with acetic acid, which turns precancerous and cancerous areas whiteand these could be viewed as signs of abnormalities. Similarly, bright white regions known as specular reflections obstruct the identification of aceto-whiteareas and should therefore be removed. So, in this paper, specular reflection removal with segmentingthe cervix region ina colposcopy image is proposed. The proposed approach consists of two main stages, namely, pre-processing and segmentation. In the pre-processing stage, specular reflections are detected and removed using a swin transformer. After that, cervical regions are segmented using an enhanced Gaussian mixture model (EGMM). For better segmentation accuracy, the best parameters of GMM are chosen via the adaptive Mexican Axolotl Optimization (AMAO) algorithm. The performance of the proposed approach is analyzed based on accuracy, sensitivity, specificity, Jaccard index, and dice coefficient, and the efficiency of the suggested strategy is compared with various methods. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Speculative investment decisions in cryptocurrency: a structural equation modelling approach
Cryptocurrency markets are inclined towards speculative usage due to the inherent high risk of financial loss and the potential for substantial gains during transaction completion. In response to this phenomenon, this study represents the inaugural effort to explore the influence of variables such as subjective norms, domain knowledge, impulsive investment tendencies, and self-control on decisions related to speculative investments. Utilising structural equation modelling with a dataset of 367 responses in India, the study is the first of its kind. The research reveals that subjective norms and domain knowledge play a significant role in influencing impulsive investment and self-control. Additionally, impulsive investment exhibits significant associations with decisions involving speculative investments. This insight underscores the complexity wherein individuals, despite exercising self-control, may still engage in speculative decisions that lead to adverse consequences. The findings have practical implications for investors and regulators, offering valuable insights into investment behaviours within the cryptocurrency realm. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
The SDG conundrum in India: navigating economic development and environmental preservation
The paper explores the complex interplay between economic development and environmental sustainability in the context of Indias pursuit of the Sustainable Development Goals (SDGs). It examines the inherent contradictions and trade-offs involved, particularly in agriculture, industrialisation, and infrastructure sectors. The paper highlights how economic growth, essential for improving living standards, often conflicts with environmental objectives. The paper underscores the importance of integrating economic, environmental, and social objectives to achieve a sustainable and inclusive future for India. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Effectiveness of Financial Inclusion through PMJDY Scheme: A Study of the PMJDY Beneficiaries in Tamil Nadu
The study explored whether various banking dimensions, viz. savings and borrowings, literacy and promotions, bank facilities and other bank services, contributed to the PMJDY beneficiaries' satisfaction in the Coimbatore region. Moreover, the study examined whether the satisfaction of the beneficiaries obtained through banking dimensions led to the frequent usage of bank accounts under the PMJDY. The data were collected from 380 beneficiaries of PMJDY from 12 administrative blocks in the Coimbatore district of Tamil Nadu, the Southern part of India. Factor analysis and Structural Equation Modeling (SEM) were used for the analysis. The results showed that the banking dimensions, viz. savings and borrowings and literacy and promotions, had positively influenced the beneficiaries' satisfaction. There was a linkage between the beneficiaries' satisfaction with frequent bank accounts under the PMJDY in rural areas of the Coimbatore region. It was found that an enriched banking service through politeness and benevolence of bank employees would enhance satisfaction, which helped the bank to acquire and retain existing beneficiaries for a thriving business environment. 2024 The Society of Economics and Development, except certain content provided by third parties. -
Death of Vernaculars and Language Hegemony: An ethnography of the higher education sector in 21st century India
The paper examines how new age pedagogies and neoliberal policies consciously work towards naturalizing English languages hegemony in institutions of Higher Education (IHE) in India. An ethnographic study the paper foregrounds the precarious positioning of non-English Indian languages vis-vis the pervading discourses of internationalization and education as job/skill oriented. Hegemony of English in the present is coupled with a restructuring of language departments as well as fleeting market demands for human capital. The paper also brings into question the role of the Internet and related technologies in reorganizing the linguistic dynamics of HE. Instead of democratizing, the Internet produces new monopolies in knowledge production, controls knowledge traffic from global North to South and further legitimizes the language hegemony. The paper argues that, in the last two decades, the neoliberal rupture has been leading HE institutions to a death of vernaculars within their physical, cultural and academic spaces. 2024, Hiroshima University,Research Institute for Higher Education,. All rights reserved. -
A Lightweight Multi-Chaos-Based Image Encryption Scheme for IoT Networks
The swift development of the Internet of Things (IoT) has accelerated digitalization across several industries, offering networked applications in fields such as security, home automation, logistics, and quality control. The growth of connected devices, on the other hand, raises worries about data breaches and security hazards. Because of IoT devices' computational and energy limits, traditional cryptographic methods face issues. In this context, we emphasize the importance of our contribution to image encryption in IoT environments through the proposal of Multiple Map Chaos Based Image Encryption (MMCBIE), a novel method that leverages the power of multiple chaotic maps. MMCBIE uses multiple chaotic maps to construct a strong encryption framework that considers the inherent features of digital images. Our proposed method, MMCBIE, distinguishes itself by integrating multiple chaotic maps like Henon Chaotic Transform and 2D-Logistic Chaotic Transform in a novel combination, a unique approach that sets it apart from existing schemes. Compared to other chaotic-based encryption systems, this feature renders them practically indistinguishable from pure visual noise. Security evaluations and cryptanalysis confirm MMCBIE's high-level security properties, indicating its superiority over existing image encryption techniques. MMCBIE demonstrated superior performance with NPCR (Number of Pixel Changing Rate) score of 99.603, UACI (Unified Average Changing Intensity) score of 32.8828, MSE (Mean Square Error) score of 6625.4198, RMSE (Root Mean Square Error) score of 80.0063, PSNR (Peak Signal to Noise Ratio) score of 10.2114, and other security analyses. 2013 IEEE. -
EASM: An efficient AttnSleep model for sleep Apnea detection from EEG signals
This paper addresses the crucial task of automatic sleep stage classification to assist sleep experts in diagnosing sleep disorders such as sleep apnea and insomnia. The proposed solution presents a novel attention-based deep learning model called, Efficient Attention-sleep Model (EASM), designed specifically for sleep apnea detection using EEG signals. EASM incorporates a streamlined architecture that includes a modified Muti-Resolution Convolutional Neural Network (MRCNN), Adaptive Feature Recalibration (AFR), and a simplified Temporal Context Encoder (TCE) module to reduce complexity. To mitigate overfitting, ridge regression is utilized, which incorporates a penalty term to enhance model generalization. Furthermore, the proposed EASM utilizes a class-balanced focal loss function to address data imbalance issues. The effectiveness of EASM is evaluated on two publicly available datasets, SLEEP EDF-20 and SLEEP EDF-78. Comparative analysis of EASM against state-of-the-art models demonstrates its superior performance in terms of accuracy, training time, and model complexity. Notably, the proposed model achieves a 50% reduction in training time and a 55.7% decrease in complexity compared to the Attnsleep model. The EASM achieves a classification accuracy of 85.8% with minimum loss when compared to the Attnsleep model. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Analytical Estimation and Experimental Validation of the Bending Stiffness of the Transmission Line Conductors
The bending stiffness of transmission line conductors can vary significantly, ranging from maximum stiffness when behaving monolithically to minimum stiffness when wires behave loosely. This large range makes it challenging to estimate stiffness accurately at intermittent bending stages. To address this issue, a mathematical model that accounts for both frictional forces between wires in the same layer and the clenching effects of helical wires from preceding layers is proposed in this paper. The proposed model estimates cable bending stiffness as a function of axial load and curvature for multilayered strands by considering slip caused by wire behavior. To evaluate the bending stiffness, experiments were conducted on Panther and Moose Indian Power Transmission line conductors. The proposed slip model considers Coulomb frictional effects and clenching effects caused by Hertzian contact forces, filling the void in the estimation procedure. Additionally, the model considers the wire stretch effect, a parameter not previously accounted for in cable research. The predicted numerical results of the proposed model were found to vary within a maximum of 7% from the experimental tests. The proposed mathematical model thus offers a more accurate and comprehensive way of estimating the bending stiffness of transmission line conductors, addressing the existing limitations in the estimation procedure. 2024 College of Engineering, Universiti Teknologi MARA (UiTM), Malaysia. -
An analysis of policy prospective of taxi aggregators and consumers in digital eco-system
The term digital trade is becoming more prevalent in the modern era. Newer company structures have evolved to replace traditional methods with online companies as digitalisation has become the standard. Taxi aggregators are one of the most prevalent digital business concepts. With this particular model, which is now known as taxi aggregators, you may quickly book a cab using your smartphone for transportation inside and outside the city limits. They are also inexpensive to use. Nevertheless, as lawmakers created new and revised rules to control these business models, the last two years have been very difficult for application-based taxi providers like Ola and Uber. The regulations are being developed by legislators in several nations, but the pace and the scope are much slower than necessary. This essay will examine past and present taxi market scenarios before suggesting ways to enhance them in the future. Copyright 2024 Inderscience Enterprises Ltd. -
Factors Affecting the Risk Perceptions of Cryptocurrency Investors
This study explores risk perceptions in cryptocurrency investments among Indian investors. It employs a multistage random sampling survey of 228 investors. Four key factors influence this perception: conceptual clarity, investment education, awareness of investment options, and fear-induced psychological factors. The overall risk perception of crypto investors is high. Based on our findings, we suggest that the Indian government should organize an awareness campaign to create awareness and educate investors about cryptocurrency. Policymakers and investment managers should focus on transforming high-risk investors into lower-risk investors through education and support, fostering a more favorable investment environment. 2024 The Institute of Behavioral Finance. -
Buffer zones in Wayanad: A social constructivist exploration into farmers mental health
Buffer zones are regions set aside to border protected areas to preserve biodiversity, control interactions between people and wildlife, and foster sustainable development. The majority of research on buffer zones focuses on ecological issues, and little is known about how they affect local communities mental health. This study explores buffer zones potential consequences on farmers mental health in Wayanad. Through purposive sampling, eleven participants residing in Wayanad were recruited for the study. The socio-demographics of participants were collected through printed translated questionnaires. The qualitative exploration of their lived experiences, perceptions, and coping strategies was conducted using semi-structured, in-depth interviews. Thematic analysis by Braun and Clarke was used to gain a clearer understanding of the data collected. Through in-depth analysis of the data, it was identified that Mental Health Factors, Communication Factors, Financial Impact, Operational Stress, Interference of Judiciary and Legislature, and Seclusion of the Tribal Community were the issues the farmers faced in Wayanad. The results will contribute to the expanding mental health field and give policymakers, conservationists, and mental health professionals information about the potential psychological effects of buffer zones and guide them in creating suitable interventions and support systems to improve mental health. The Author(s) 2024. -
Peristaltic mechanism of Ellis fluid with viscous dissipation and thermal radiation induced by cilia wave
Bioheat transfer analysis in tissue has attracted the attention of numerous researchers due to its widespread potential applications in the medical field, mainly in thermotherapy and the human thermoregulation system. Also, temperature regulation of the human body primarily occurs through bioheat transfer. Due to the widespread biomedical applications of bio-heat transfer, we aim to investigate the movement of biofluid and bioheat in human organs with the influences of thermal radiation and ciliary waves. The mathematical model for Ellis fluid flow through a tube includes the metachronal wave of cilia motion and convective conditions. The governing equations are created based on mass, momentum conservation, and energy. The current problem is displayed and exact solutions are managed under long wavelength (? < 1) and low Reynolds number (Re < 1) approximations. An analytical approach is employed to derive expressions for longitudinal velocity, temperature, pressure gradient, and stream function as a function of the parameters of the problem. The physical behavior of the peristaltic motion of the Ellis fluid is explained in detail and illustrated graphically for various parameter values. The results of the current study provide potential information for advancement in the biomedical industry, particularly in the development of biomedical devices and processes. World Scientific Publishing Europe Ltd. -
Through the Lenses of Sexual Minorities in the Indian LGBTQ + Community: Perception of Social Equality and Community Support
Whether in the form of same-sex attraction or love, the history of same-sex relationships has been well documented in every culture across the globe. In India, evidence of the same can be found on the monolithic sculptures of the Vishvanath Temple in Khajuraho and texts like Mahabharata and Sushrata Samahita. The acceptance and openness enjoyed by the non-hetero-normative and non-cis-gender individuals in ancient India, changed after the nations colonization. In current times, mainstream society holds heterosexual intercourse as the norm while considering same-sex relationships as deviations. Same sex relationships are a highly stigmatized and garner objections from several religious and political sects. This social stigma and erasure becomes harsher when directed toward individuals with polysexual or asexual orientations. The lack of awareness and representations garners bisexuals, pansexuals and asexuals the status of sexual minorities within the LGBTQ + community. This study makes use of three focus group discussions to explore the perception of each sexual minority regarding social equality within the Indian LGBTQ + community and outside it, alongside trying to understand the community support received by the sexual minorities in the Indian LGBTQ + community. The study uses inductive thematic analysis to draw out themes. The results indicate a predominant feeling of being misunderstood, exploited, fetishized and alienated even within the LGBTQ + community while finding solace in their own sub-communities and the online community. The results also reveal feelings expectations held by individuals from each sexual minority in terms of their desired place in society. 2024 Taylor & Francis Group, LLC. -
A characterization of star-perfect graphs
Motivated by Berge perfect graphs, we define star-perfect graphs and characterize them. For a finite simple graph G(V, E), let (Formula presented.) denote the minimum number of induced stars contained in G such that the union of their vertex sets is V(G), and let (Formula presented.) denote the maximum number of vertices in G such that no two of them are contained in the same induced star of G. We call a graph G star-perfect if (Formula presented.), for every induced subgraph H of G. A graph G is star-perfect if and only if G is (Formula presented.) -free, for every (Formula presented.). A bipartite graph G is star-perfect if and only if every induced cycle in G is of length (Formula presented.). The minimum parameter (Formula presented.) and the maximum parameter (Formula presented.) have been extensively studied in various contexts. 2024 The Author(s). Published with license by Taylor & Francis Group, LLC. -
Creating a sustainable future: insights into brand marketing in the luxury fashion industry
This paper aims to develop a conceptual framework that elucidates the factors that impact sustainable luxury brand marketing, specifically focusing on the luxury fashion industry. The framework aims to highlight the role played by the industry in promoting economic, social, and environmental sustainability. By examining these factors, the study seeks to contribute to a better understanding of how luxury fashion brands can effectively incorporate sustainability into their marketing strategies, thereby fostering a more sustainable and responsible approach to luxury consumption. Applying the theoretical framework derived from the literature review and systematic mapping approach, we examine its relevance in the luxury fashion market. This exploration allows us to assess its practical applicability and gather empirical evidence regarding sustainable brand marketing in this context. This research will give an in-depth analysis of the major elements influencing the consumption of sustainable luxury goods. The findings expand our understanding of the sustainable practices adopted by luxury fashion brands, providing valuable insights for academia and the industry. This studys implications are profound: luxury brand managers can enhance brand value through insights on sustainable fashion consumption drivers, while sustainable brands gain strategies for audience engagement and loyalty. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Emotional Inhibition and Personality as Predictors of Anxiety and Depression in Young Adults
Purpose: Anxiety and depression have been major contributors to the global burden of disease, and the impact has been exacerbated following the COVID-19 pandemic. Therefore, the aim of this study was to understand the association between emotional suppression and the introverted-extraverted dimension of personality in young people and anxiety and depression. Method: Participants were 152 Indian females between the age group of 18-25 years who provided basic demographic details and completed three questionnaires via a google form. Findings: Results described a significant negative correlation of anxiety r (152) = .500, p <0.01and depression r(152)=.471, p <0.01 with emotional inhibition. There was also a significant positive correlation of anxiety r (152) = .288,p < 0.01 and depression r(152)= .288, p <0.01 with personality. While Emotional inhibition emerged as a significant negative predictor of anxiety (R2= .250) as well as of depression (R2=.222), personality (R2=.243) emerged as a significant predictor of depression. Conclusion/Value: Contrary to popular belief, the results of this study suggest that anxiety and depression are inversely related to emotional inhibition. It restores the complexity of emotions and the need to investigate their role in various pathologies. These findings provide an initial basis for further investigation into the role of emotional expression and suppression in the Indian population. 2024 RJ4All. -
Lightweight Model for Occlusion Removal from Face Images
In the realm of deep learning, the prevalence of models with large number of parameters poses a significant challenge for low computation device. Critical influence of model size, primarily governed by weight parameters in shaping the computational demands of the occlusion removal process. Recognizing the computational burdens associated with existing occlusion removal algorithms, characterized by their propensity for substantial computational resources and large model sizes, we advocate for a paradigm shift towards solutions conducive to low-computation environments. Existing occlusion riddance techniques typically demand substantial computational resources and storage capacity. To support real-time applications, it's imperative to deploy trained models on resource-constrained devices like handheld devices and internet of things (IoT) devices possess limited memory and computational capabilities. There arises a critical need to compress and accelerate these models for deployment on resource-constrained devices, without compromising significantly on model accuracy. Our study introduces a significant contribution in the form of a compressed model designed specifically for addressing occlusion in face images for low computation devices. We perform dynamic quantization technique by reducing the weights of the Pix2pix generator model. The trained model is then compressed, which significantly reduces its size and execution time. The proposed model, is lightweight, due to storage space requirement reduced drastically with significant improvement in the execution time. The performance of the proposed method has been compared with other state of the art methods in terms of PSNR and SSIM. Hence the proposed lightweight model is more suitable for the real time applications with less computational cost. 2024 by the author(s). -
Relationships between Ultrasonographic Placental Thickness in the Third Trimester and Foetal Outcomes
Poor neonatal outcomes, including low birth weight (LBW), poor APGAR scores, more NICU hospitalizations, and a higher chance to develop Pre-Eclampsia, IUGR, and Oligo Hydramnios, are all linked to thin placental thickness. While both thin and thick placentae are connected to a greater prevalence of C-sections, thick placentae are linked with a greater possibility of developing GDM and an increase in NICU hospitalizations. Objective of this research was to investigate the association between placental thickness as measured by ultrasonography in the third trimester and foetal outcome, including the relationship between placental histopathology and placental thickness. investigate the link among placental thickness, foetal outcome, and placental histology. Most newborns had fibrinoid necrosis and calcifications. Babies with Macrosomia and IUGR, respectively, were more likely to develop Syncytial knots and thickening of the vessel wall. Patients with normal placenta thickness at 36 weeks' gestation experienced fewer difficulties than those with thin or thick placentas at the same time. The study emphasizes the value of evaluating placental thickness using ultrasound in the third trimester to detect high-risk pregnancies. The study also shows that aberrant foetal and neonatal events are linked to certain placental histological characteristics, like artery wall thickening and infarctions. RJPT All right reserved.