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The Influence of Marketing and Awareness Campaigns on Solar Energy Adoption: A Review of Strategies and Effectiveness
The shift to renewable energy sources is picking up pace globally, with solar energy being one of the most significant sustainable solutions. However, with technological advancements and declining costs, solar adoption has been inconsistent among various consumer segments. This review critically examines marketing strategies, awareness campaigns, financial incentives, and socioeconomic factors as drivers of solar energy adoption. The study classifies findings into four key dimensions, namely: consumer awareness, effectiveness of traditional compared to digital marketing, socioeconomic influences, and psychological and behavioural impacts on decision making. Results show that high consumer awareness leads to highly significant increases in adoption rates, while traditional marketing finds relevance in low-digital penetration, but digital marketing is more effective all along. Policies and incentives for economic support also have an immense impact on adoption rates among the lower classes because high-class education and urbanization affect adoption rates strongly. Behavioural factors including consumer trust in providers, environmental causes, installation ease, and social influence further influence consumer adoption readiness. Recommendations emerging from this study point towards awareness campaigns targeted at specific groups, availability of financial incentives, and customized marketing strategies aimed at actual consumption at a scale. This literature review has informed policymakers and marketers on how to tailor their marketing and promotion approach towards solar energy as a mass adoption solution. 2025, Iquz Galaxy Publisher. All rights reserved. -
Texture-Based DNN for Pneumonia in Thorax X-Rays
This paper introduces an innovative methodology for identifying pneumonia in thoracic X-ray images through the application of neural network classifiers. In our experiment, we employed a comprehensive training regimen involving multiple neural network classifiers, each trained on distinct sets of texture features meticulously extracted from thoracic X-ray images. Four different gray-level matrices and a neighboring gray-tone difference matrix (NGTDM) were used to generate these input features, guaranteeing a reliable depiction of the textural properties found in the X-ray pictures. We carried out an extensive evaluation utilizing a number of performance criteria to gauge the trained classifiers' efficacy. Classifying the thoracic X-ray pictures into two groups pneumonia and healthy state was the assignment assigned to the classifiers. A thorough study of the classifiers' performance was provided by our assessment measures, which comprised accuracy, precision, recall, F1-score, and the area under the receiver operating characteristic curve (AUC-ROC). The experimental findings showed that the suggested method accomplished a remarkable 91% overall test categorization accuracy, which was encouraging. This degree of precision highlights how well our approach works to accurately diagnose pneumonia from thoracic X-ray images. Furthermore, the consistent performance across different metrics highlights the robustness and generalizability of the proposed strategy. 2025, Iquz Galaxy Publisher. All rights reserved. -
A Comparative Study of Gender and Age-Based Differences in Organisational Culture: Evidence from an Empirical Analysis
Organisational culture (OC) plays a significant role in shaping employee attitudes, engagement, and overall effectiveness. However, limited empirical evidence explores how demographic factors, such as age and gender, influence employees perceptions of organisational culture. This study reveals age and gender-based differences in organisational culture among employees from leading Indian-origin IT services companies in Bengaluru. Grounded in the Denison Organizational Culture Model, the study examines four key dimensions: involvement, consistency, adaptability, and mission. Data were collected from employees using a structured questionnaire, and statistical analyses, including ANOVA and Z-tests, were applied to examine differences in cultural perceptions. The results indicated that overall organisational culture scores did not differ significantly among age or gender groups. Specific dimensions, such as capability development, core values, agreement, and vision, exhibited significant age-related differences, with younger employees (2030 years) perceiving a stronger culture than those in the 3140 age group. No significant gender-based differences were observed across any dimension. These findings demonstrate the importance of demographic responsiveness in shaping inclusive organisational practices. The study contributes to organisational behaviour literature and offers practical implications for HR managers and leaders seeking to develop employee engagement and cultural alignment in the IT services sector. Keywords:. 2026, Iquz Galaxy Publisher. All rights reserved. -
Sridevi's Stardom as A Cultural Vehicle for Women Empowerment and Social Commentary: A Textual Analysis of English Vinglish (2012) and Mom (2017)
In the Indian film sector, stardom is more than mere performance; it operates as a cultural text that produces impacts and negotiates with social values, ideals, and contradictions. Female stardom, in this way, is particularly potent in generating discourses of gender and empowerment, both disrupting patriarchal norms while enacting socially accepted moral orders. Sridevi's stardom carries specific cultural resonance, as the films she stars in offer a blend of popular entertainment while carrying deeper social significance. This study seeks to understand Sridevi's stardom and the potential for her representation of women's empowerment, as well as social commentary by analysing the films English Vinglish (2012) and Mom (2017). The study explores the implications related to Sridevi's star persona as a cultural and ideological site for women's empowerment and social critique in contemporary Indian cinema. It applies a purposive sampling method, and utilises textual analysis to investigate performance style, narrative structures, visual framing and symbolic meaning signifying women's power and resilience. The textual analysis of English Vinglish finds empowerment framed through self-assertion and linguistic competence within familial and social spaces whereas in Mom empowerment emerges in the more ambiguous domain of maternal justice and moral authority. Taken collectively, these films showcase how Sridevi's stardom functioned as a cultural vehicle, entertaining audiences while provoking critical consideration of women's roles, autonomy, justice, and empowerment within contemporary Indian society. 2026, Iquz Galaxy Publisher. All rights reserved. -
Discriminated-SDS: A Novel Hybrid Approach for Optimizing EEG Based Brain-Computer Interface Signals Faced by Metaheuristic Algorithms
Brain Computer Interfaces (BCIs) will convert the thoughts of individuals with physical disabilities into commands for devices to enable them autonomous mobility. The Electroencephalogram (EEG) is widely favoured as a control signal due to its ease of acquisition compared to invasive recordings. While the affordability of EEG equipment allows for the use of numerous recording channels, this abundance increases computational complexity, necessitating optimal channel selection strategies to improve efficiency and classification accuracy. Deep Neural Networks (DNNs) often face scalability issues with multidimensional, locally correlated inputs, making them impractical for such applications. Convolutional Neural Networks (CNNs) are efficient for analysing BCI data but require careful hyperparameter tuning to achieve optimal performance. This paper introduces a framework for classifying BCI channel selection using deep learning techniques. The study primarily concentrates on refining the hyper parameters of deep learning algorithms through metaheuristic techniques, specifically employing Discriminated Stochastic Diffusion Search (SDS) to enhance BCI channel selection. The findings indicate that the proposed hyperparameter optimization methods, such as Discriminated-SDS, significantly enhance classification accuracy. The proposed D-SDS balances exploration and exploitation, mitigates the local optima issue, and is especially advantageous for intricate deep learner architectures such as VGGNet, ResNet, and InceptionNet. Hyperparameter optimization in EEG-based BCI systems can substantially improve performance, enhancing their efficiency and reliability. 2026, Iquz Galaxy Publisher. All rights reserved. -
Idiosyncratic Deals and Motherhood Stress: Understanding the Mediating Effect of Work to Family Enrichment with Moderating Effect of Workplace Dignity
Motherhood stress has developed as a substantial yet underexplored outcome of present-day employment practices, particularly in organizational contexts where flexibility is increasingly individualized. While prior research has examined motherhood stress, flexible work arrangements, and idiosyncratic deals largely in isolation, limited attention has been given to how personalized flexibility shapes the psychological experiences of working mothers. This study attempts to bridge this gap by examining how I-deals influence motherhood stress through psychological and relational mechanisms embedded within organizational and socio-cultural contexts. Drawing on interdisciplinary literature, this study positions I-deals as context-dependent resources whose effects on motherhood stress are mediated by work family enrichment and where workplace dignity has a moderating role. The study adopts a quantitative survey approach across 410 female employees in the Indian IT sector to test the proposed hypotheses among working mothers. The study establishes a direct and negative association between Idiosyncratic deals and work to family enrichment which further plays a mediating role with motherhood stress. It also found that workplace dignity plays a significant role in moderating the association between I-deals and work to family enrichment. The study contributes by integrating organizational behaviour and motherhood research, reconceptualizing flexibility as a psychologically contingent practice, and highlighting the importance of work to family enrichment and dignity in shaping stress outcomes. The findings offer an understanding and practical insights for organizations looking to design flexibility policies that genuinely support working mothers without inadvertently intensifying stress. 2026, Iquz Galaxy Publisher. All rights reserved. -
Balancing Beauty and Facts: Examining the Dual Impact of Product Presentation and Information on Consumer Purchase Decisions in the Skincare Products
This paper is a discussion by the authors on effects of the presentation and information of product on consumer purchasing behaviour in skincare industry. In the existing competitive market where there are many products of similar kind and assertions, consumers are usually overwhelmed with excessive information. Product presentation-by designing the packaging, the aesthetics and branding something-develops the first impressions and emotional attraction, whereas product information including ingredients content, safety certification, labelling and others develops confidence and perceived quality. Nevertheless, there are not many studies that contrast their relative impact or investigate their mutual impact. This study bridges that gap by conducting a mixed method study consisting of a focus group visual preference testing (n=170) and an online survey of consumers (n=162). Results also show that information on the product, particularly ingredient disclosure and safety accreditation are a major determinant of purchase among consumers. Design and presentation may evoke immediate interest, but when product information is manipulated they have no statistical power on the ultimate purchase. It is important to note that the synergistic effect of presentation and information is not better than the effects of information alone. The implications of these findings are that although brand recognition increases with the aesthetic appeal, it is factual clarity that eventually leads to purchase intention. The research builds on the consumer decision-making theory because it focuses more on informational factors rather than emotional packaging cues in the ultimate buying of skincare products to provide marketing marketers with an excellent idea on how to increase transparency and authenticity to enhance consumer trust and confidence to buy a product. 2026, Iquz Galaxy Publisher. All rights reserved. -
Bridging Technology and Consumer Experience: The Role of Augmented Reality and Perceived Usefulness in Digital Retailing
The advent of Augmented Reality (AR) has sparked an interest in the capability of redesigning the experiences of consumers. This paper examines the effects of AR on Consumer Experience (CE) and the mediator of Perceived Usefulness (PU). The study utilizes the Technology Acceptance Model (TAM) to identify the conceptual model based on the Structural Equation Modelling (SEM) with the data obtained in the sample of 311 participants. The results indicate that Augmented Reality has great power over Consumer Experience as elements such as engagement in Augmented Reality inspire a realistic effect on users. The results indicate that Perceived Usefulness plays a minor moderating role in the relationship between Augmented Reality and Consumer Experience, which suggests that the idea of perceived usefulness should be understood even in the environment full of technologies. Therefore, the research contributes to the existing body of literature because it combines AR experience with the main TAM concepts and offers a feasible justification of PU as an enabler in models of consumer experiences driven by technologies. Basically, the findings suggest that to maximize the effect of AR, creators and sellers should not only emphasize on engaging design but also relate the practical utility of the AR tools to the users by encouraging user interaction and awareness. 2026, Iquz Galaxy Publisher. All rights reserved. -
Elliptic curve-based cryptography solutions for strengthening network security in IoT environments
Elliptic Curve-Based Cryptography (ECC) may be a solid way to move forward organize security in Web of Things (IoT) settings, where other cryptography strategies regularly come up short. ECC suggests a tall level of security with moderately little key sizes, which is especially important for Internet of Things devices without any assets. This speed cuts down on preparing squander, memory utilize, and control utilize, which makes it culminate for IoT apps that utilize a part of diverse sorts of equipment. By making beyond any doubt there are secure ways to communicate and verify clients, ECC can lower the dangers of data spills and illicit get to. ECC is additionally great at securing private information over gadgets that are connected to each other since it is safe to modern dangers and can be changed to work with distinctive IoT conventions. Utilizing ECC-based arrangements in IoT systems not as it were makes them more secure, but it moreover moves forward speed, making it conceivable to receive secure and adaptable arrangements in settings that are getting more complicated and spread out. 2025, Taru Publications. All rights reserved. -
Invariant intersection graph of a graph
Studies in algebraic graph theory showcase the interplay between group theory and graph theory by defining graphs on groups, investigating their properties, and also by analysing the automorphism groups that emerge from the graphs. In this article, we introduce the idea of constructing an algebraic derived graph; that is, constructing a graph based on the algebraic properties of a graph, by introducing the invariant intersection graph of a graph, constructed based on the automorphism group of a graph. Here, we introduce the graph construction and initiate an investigation on the structure of the invariant intersection graph with respect to the graph and its automorphism group. 2025, Taru Publications. All rights reserved. -
Entropy diagnostics for cryptographic key material from random circuit sampling
Random Circuit Sampling (RCS) has emerged as a leading paradigm for demonstrating quantum advantage. Beyond computational complexity, RCS provides a high-dimensional, chaotic probability distribution whose structure is characteristic of random unitary dynamics; here, we study its entropy properties in an ideal statevector baseline intended for later hardware validation. In this work, we present a reproducible validation framework for certifying cryptographic keys using a 12-qubit RCS ensemble (N = 4096 states ) within an ideal quantum simulation framework. Unlike standard Quantum Random Number Generators (QRNGs), which often rely on single-qubit optics, our protocol utilises multi-qubit entanglement to ensure nonlocality. We quantify the security of the system using a dual-metric approach: basis-dependent Min-Entropy (H? ? 9.05 bits ) for cryptographic extractability, and basis-independent Subsystem Von Neumann Entropy (S ? 3.96 bits) for quantum certification. We further demonstrate a privacy-amplification pipeline that uses a frequency-preserving, endian-corrected SHA-3 extraction to produce a 256-bit secure key (candidate key material). This study provides a transparent methodological bridge between the theoretical Quantum Supremacy regime and practical cryptographic key generation. 2026, Taru Publications. All rights reserved. -
Transforming network security through zero trust architecture: Principles, challenges, and future directions
Given the continued expansion of cyber threats; such perimeter-based resistance traditional security strategies have proven to be inadequate. No one is trusted by default, either inside or outside the network, in a Zero Trust architecture. Zero Trust Architecture (ZTA) is a modern security model that demands consistent authentication of users and devices and denies any presupposition of implicit trust. It should also be of strong authorization, network division, and authentication. This article covers the principles, components, pros, and cons along with zero trust implementation strategies and the impact on network security. 2026, Taru Publications. All rights reserved. -
Decoding math : A review of datasets shaping AI-driven mathematical reasoning
Math problem solving is a fundamental part of the modern era, and artificial intelligence (AI) driven mathematical reasoning has become an essential part of data work. In this literature review, we explore the diverse array of datasets intended to improve AI models capacity to solve mathematical word problems. These datasets not only provided diverse problem sets but also served as benchmarks for evaluating the performance of various deep learning models, including recurrent neural networks (RNNs) and graph-based models. The datasets, particularly GSM8K, posed challenges that even the most sophisticated transformer models struggled to overcome, setting a new standard for the study of AI systems in math problem solving. This literature review aims to provide a comprehensive overview of the evolving landscape of mathematical problem solving, paving the way for future advances in AI-driven mathematical reasoning. 2025, Taru Publications. All rights reserved. -
Developing mathematical models to analyze economic growth patterns in emerging market dynamics
A key factor in determining national development and directing successful market strategies is economic growth. Making better judgements in developing countries is facilitated for investors and policymakers by having a better understanding of the main drivers of growth. The purpose of this paper is to use mathematical models to explain how economic growth patterns vary among the major growing nations. It examines the effects of inflation, foreign investment, trade, and current account balances on the GDP growth of five major economies India, China, Russia, Brazil, and South Africa between the year 2005 to 2025. The study presents how these variables connect to growth and vary among nations using techniques like logistic regression, linear regression, and ANOVA. TARU PUBLICATIONS. -
Fuzzy Logic Approach to Cold-Start Challenges in Deaf and Hard of Hearing Recommender Systems
An adaptive e-learning environment faces significant challenges in offering personalized learning resources for Deaf and Hard-Hearing (DHH) learners. These learners exhibit diverse preferences in learning and communication, influenced by their characteristics related to deafness, highlighting the need for personalized educational content. A well-defined learning model is essential to map the characteristics of learners to suitable learning resources, enabling effective recommendations within an e-learning system. This study explores the development of a comprehensive DHH learner model, focusing on the presence of multiple learning preferences based on the VARK (Visual, Aural, Read/Write, and Kinesthetic) learning style model and the effectiveness of fuzzy clustering in capturing the diverse but overlapping preferences. Fuzzy-C-Means (FCM) successfully identified six different but overlapping clusters, indicating that most learners exhibit multimodal learning preferences rather than relying solely on a visual learning style. Cluster centroid analysis reveals that the visual learning style is the most preferred, while aural learning is the least favored among DHH learners. By calculating the overall learning style score based on the fuzzy membership value across all clusters on all four dimensions of VARK, learners' learning style preferences were validated against self-reported data. The evaluation involved a survey of 130 higher secondary DHH students from Kerala, India, yielding promising results (precision: 0.90, recall: 0.84, F1-score: 0.84) on the model's efficiency in identifying the dominant learning style. These findings emphasize the need for adaptive content delivery strategies that integrate text, visual, and interactive elements to enhance the engagement of DHH learners. However, the limited sample size, due to the unavailability of publicly accessible datasets, and the limited number of students in higher secondary education, further highlights the need for accessible and standardized DHH data to advance this research domain. by the authors. -
Demographic Determinants of Fire-Safety Behavior in High-Rise Residential Buildings: A Survey-Based Behavioral Analysis from Bengaluru, India
This study explores the role of demographic and experience-based parameters for fire safety behavior among residents of high-rise residential apartment buildings in the city of Bengaluru, a metropolitan capital in India. Data were gathered through a questionnaire-based survey among 262 residents. Multiple regression analysis was used to assess the correlation among demographic parameters and behavioral responses during evacuation. The results show that age (R2 = 0.154, p = 0.004), presence of vulnerable household members (R2 = 0.137, p = 0.022), and prior fire experience (R2 = 0.157, p = 0.004) are statistically significant predictors of fire-safety behavior. In contrast, gender (R2 = 0.117, p = 0.073), educational qualifications (R2 = 0.109, p = 0.136), and chronic health conditions (R2 = 0.121, p = 0.500) do not exhibit significant associations. Cross-tabulation analysis further indicates that residents who have received fire-safety training prioritize immediate evacuation, whereas untrained residents display delay behaviors. By providing empirical behavioral evidence from an Indian metropolitan context, this study highlights the demographic heterogeneity in evacuation behavior and supports the integration of behavioral realism into performance-based fire safety design for high-rise residential buildings. (2026), (Dr D. Pylarinos). All rights reserved. -
Comparative analysis of carrier material efficiency in the encapsulation of flavor bioactives from Decalepis hamiltonii extract by using spray-drying and freeze-drying
An aqueous extract from the tuberous roots of Decalepis hamiltonii was encapsulated by spray-drying and freeze-drying for food applications. The study aimed to identify suitable carrier materials among sodium caseinate, maltodextrin, and gum acacia, used alone and in blends, to understand their collective effect during encapsulation. The physicochemical characteristics of freeze-dried and spray-dried samples revealed differences of 14%20% in 2-hydroxy-4-methoxy benzaldehyde, 12%40% in phenolic content, and 7%40% in flavonoid content in the dried powders. Similarly, the methanol extracts of freeze-dried encapsulated samples demonstrated good antioxidant potential compared with those of spray-dried encapsulated powder. Among the carrier materials used, sodium caseinate showed good retention of bioactives and a flavor metabolite (2-hydroxy-4-methoxybenzaldehyde), which was quantified by high-performance liquid chromatography (encapsulation efficiency 82%; yield 40 w/w) and confirmed by1H nuclear magnetic resonance (NMR). However, in this study considering flavor retention and powder yield (encapsulation efficiency 74% and 59 w/w), maltodextrin in combination with sodium caseinate (MS) was observed to be the best carrier material for spray-drying. These "maltodextrinsodium caseinate" microcapsules are stable and show 70% retention of flavor metabolite after 3 months of storage at room temperature, with the microbial load remaining within acceptable limits. The particle size of the carrier materials ranges from 11.1 to 17.6 m. Thus, the current study suggests that a carrier material mixture (sodium caseinate and maltodextrin) can be used as a prospective material for encapsulating Decalepis hamiltonii bioactives with flavor metabolites and may be useful in food formulations. 2025 by the author(s). -
Analysis of Mothers Willingness for Age 1 First Dental Visit of Their Child using Andersens Behavioral Model of Health Service Utilization
Background: Early childhood caries (ECC) is a preventable disease among children under 6 years of age.The first dental visit (FDV) is a preventive model endorsed by the American Academy of Pediatric Dentistry and the American Academy of Pediatrics. It is designed to improve oral health outcomes, yet the FDV attendance rate before the age of 1 is low globally, especially in India. Aims: To investigate maternal willingness to attend the FDV within 1 year of age and explore associations with predisposing, enabling, and need factors using Andersens behavioral model for health services utilization. Materials and methods: A cross-sectional survey was conducted among mothers of children aged 915 months. A validated questionnaire was administered to 640 mothers visiting vaccination centers in two hospitals. Statistical analysis involved descriptive statistics and logistic regression to evaluate factors influencing FDV willingness. Results: Willingness to attend FDV within 1 year of age was significantly influenced by predisposing factors, such as oral health knowledge, perceived barriers, and susceptibility to caries. Enabling factors, such as socioeconomic status and family support, showed minimal influence, while need factors, including the perceived oral health of the child, strongly correlated with FDV willingness. Findings revealed low awareness and attendance rates for FDV in the study population. Conclusion: First dental visit attendance among infants in the study population is critically low, highlighting the need for targeted awareness campaigns. Pediatric healthcare professionals should actively promote oral health and FDV as preventive measures during well-baby visits to enhance acceptance and utilization. Clinical significance: This studys focus on analyzing mothers willingness to pursue the FDV at age 1, using Andersens behavioral model of health service utilization, which provides actionable insights into the multifactorial drivers behind health-seeking behavior. Understanding how predisposing, enabling, and need-based factors influence maternal decision-making not only aids in identifying barriers to early dental care but also hi hli hts o ortunities to tailor ublic health interventions The Author(s). -
AN ADAPTIVE HYBRID SCHEDULING APPROACH FOR SUSTAINABLE AND RELIABLE CLOUD SERVICES
The modern cloud computing systems have to plan the heterogeneous workloads and balance performance effectiveness, service availability, and sustainability. In this study, an adaptive hybrid scheduling framework is developed Adaptive Ant-guided Min-Max (AAMM) combining ant-guided optimization with dynamic Min-Min and Max-Min in deciding how to allocate cloud tasks as a multi-objective. The scheduler jointly evaluates task completion time, the likelihood of Service Level Agreement violations, energy consumption, and monetary cost within a unified scoring framework, enabling informed trade-offs among competing objectives. AAMM is assessed based on a real disaggregated Deep Learning Recommendation Model workload of 1,544 heterogeneous tasks, running on heterogeneous virtual machines. Comparative experiments are done with Min-Min, Max-Min and ACO-guided Min-Min scheduling strategies. According to experimental findings, the suggested approach has been very effective in reducing energy per task, cost per task, SLA violations are significantly lowered, and flow time stability is enhanced. Though moderate growth in the makespan is witnessed, the accompanying trade-off has created equal distribution of resources and service reliability. 2026 Academy and Industry Research Collaboration Center (AIRCC). All rights reserved. -
Australian bushfire emissions result in enhanced polar stratospheric clouds
Extreme bushfire events amplify climate change by emitting greenhouse gases and destroying carbon sinks. They also cause economic damage, through property destruction, and even fatalities. One such bushfire occurred in Australia in 20192020, and this event injected large amounts of aerosols and gases into the stratosphere and depleted the ozone layer. While previous studies have focused on the drivers behind ozone depletion, the bushfire impact on polar stratospheric clouds (PSCs), a paramount factor in ozone depletion, has not been extensively investigated so far. Therefore, this study focuses on the effects of bushfire aerosols on the dynamics and stratospheric chemistry related to PSC formation and its pathways. An analysis from Auras Microwave Limb Sounder revealed that the enhanced hydrolysis of dinitrogen pentoxide significantly increased nitric acid (HNO3) in the high-latitude lower stratosphere in early 2020. This resulted in an anomalously high areal coverage of PSCs with ice, exceeding 3 standard deviations with respect to background period. Based on Lagrangian backward-trajectory analysis, we find that a predominant fraction (79 %) of the liquidnitric acid trihydrate (NAT) mixture formed via the ice-free nucleation pathway. These NAT particles subsequently acted as nuclei for ice formation, accounting for 95 % of the observed ice PSCs. This rapid conversion from NAT to ice likely contributed to the strong positive anomaly in ice PSC. This highlights the primary formation pathways of ice and liquidNAT mixtures and possibly helps us to simulate PSC formation and denitrification process better in climate models. These findings will contribute significantly to a deeper understanding of the impacts of extreme wildfire events on stratospheric chemistry and PSC dynamics. Author(s) 2025.