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BRICS VS. G7: A COMPARATIVE ANALYSIS OF ECONOMIC AND POLITICAL EFFICIENCY IN SHAPING GLOBAL ORDER
The global distribution of power is increasingly shaped by the competing influences of two major blocs: BRICS (Brazil, Russia, India, China, and South Africa) and the G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States). This paper investigates how BRICS and the G7 shape the emerging multipolar global order. Using comparative analysis of key indicators: GDP, trade flows, investment patterns, diplomatic engagement, and strategic alliances. The paper examines each blocs structure and internal cohesion. The analysis underscores the G7's historical supremacy, which stems from its economic strength and political unity, in contrast to BRICS rising role as a representative for the Global South and a platform for alternative governance models. Important metrics include trade flows, investment trends, diplomatic efforts, and strategic alliances. The research also assesses the internal dynamics within each bloc, including challenges to cohesion and the effectiveness of decision-making. By comparing the advantages and drawbacks of BRICS and G7, this paper provides insights into their respective functions in a multipolar world order, evaluating their ability to promote transformative global agendas. Lastly, the paper concludes that both alliances embody divergent approaches to global governance, reflecting deeper shifts in international collaboration, competition, and the balance of power. 2025, Observare. All rights reserved. -
Social-Ecological System Framework Network
The Social-Ecological Systems Framework Network (SESFN) provides a holistic approach to understanding the complicated relationships between ecological and social systems. By integrating network analysis, SESFN unveils the dynamic interconnections and interdependencies that shape these systems, offering critical insights into governance, resilience, and adaptive capacity. This framework is a powerful tool for addressing contemporary challenges such as biodiversity conservation, resource management, and climate change. Through interdisciplinary collaboration, SESFN facilitates stakeholder engagement, combining traditional knowledge with scientific research to foster sustainable practices. The application of SESFN has established its effectiveness in promoting adaptive management and improving both ecosystem health and human well-being. As global environmental challenges deepen, SESFN emerges as a pivotal and essential framework for crafting innovative solutions to achieve sustainability and resilience across diverse social-ecological contexts. 2026 John Wiley & Sons Ltd. All rights reserved. -
Government Support and Policies
Government interventions play a crucial role in nurturing technopreneurship and advancing sustainability. The proposed chapter explains the significance of governmental support in bridging the financial, infrastructural, and knowledge gaps that technopreneurs face. It categorizes the types of support into financial aid, regulatory frameworks, infrastructure development, and educational programs, providing a structured overview of each. A detailed analysis of policy frameworks that foster innovation and sustainability is presented, supported with global examples such as the United States Small Business Innovation Research (SBIR) program, Israels Innovation Authority, Indias Digital India Initiative and Germanys High-Tech Strategy 2025. These examples illustrate how strategic policies can catalyse technological advancements and economic growth. The chapter further includes case studies from diverse regions, showcasing successful policy implementations and their tangible impacts. These case studies offer practical insights and best practices, demonstrating how tailored policies can create robust technopreneurial ecosystems. Finally, the chapter addresses the challenges in policy implementation and offers recommendations for future directions, emphasizing the need for adaptive, inclusive, and collaborative policy approaches. This comprehensive exploration aims to provide policymakers, academicians, and technopreneurs with valuable knowledge on leveraging government support for sustainable technopreneurial success. 2025 selection and editorial matter, Rajender Kumar, Rahul Sindhwani, Raman Kumar, Punj Lata Singh, and J. Paulo Davim. -
Analyzing online food delivery industries using pythagorean fuzzy relation and composition
Food and beverages constitute a significant portion of the family expenditure, which motivates the food delivery companies in striving hard to meet the customer needs through their dynamic food delivery apps. The online food ordering system is one of the most profitable marketing strategies for restaurant businesses. The face of the restaurant industry has shifted from the traditional dine-in culture to takeaways, online ordering, and home deliveries. Digital technology and social media have a significant role in ensuring the efficiency and popularity of a food delivery app. The four essential factors for a food delivery company to satisfy the needs of the consumers in day to day life are choice of restaurants, speed of delivery, payment option and quality of service. The objective of this study is to discern and analyse these four essential factors adopted by the leading four food delivery companies and evaluate the perceptions of the consumers. The best online food delivering company is identified using Pythagorean Fuzzy Relation (PFR)and composition. The analysis concludes that Zomato food application is the best in consumers perception.The outcome of the survey is made more efficient by adopting a mathematical approach. Copyright IJHTS. -
Impact of COVID-19 on Delivery of Quality Hospitality Education in India
The Covid-19 pandemic caused many industries globally to undergo radical changes in their operational systems, disrupting the service delivery processes. The education industry is no exception to this phenomenon. India's higher educational institutions witnessed the immense challenge of taking the teaching process online with limited means and infrastructural support. This study aimed to assess the impact of the pandemic on the delivery of education online in India with particular reference to hospitality courses. A survey of 250 students and interview of 10 faculty members from 5 universities offering hospitality course across India showed that the online learning system is far from satisfactory and effective. Moreover, teachers need to undergo training sessions in order to improve their online teaching skills and create newer methods of imparting skills and evaluating students' performance. IJHTS -
A study of entrepreneurial choices and challenges encountered by young graduates
India, one of the most populous countries is growing phenomenally, though the challenges of unemployment is compounding. An unique method of overcoming this issue is through motivation of college students in becoming entrepreneurs, which will not only create employment but will also reduce the pressure of gaining employment on the students. However, flexible government policies in favor of entrepreneurs will facilitate the economic development of the country. In this study, a quantitative method is used to collect the data on entrepreneurship and the changing preferences of college students. A survey (N= 209) among college students of Bengaluru, India is conducted to identify the impact of entrepreneurship on work life choices of young graduates, evaluate the emergence of entrepreneurs in influencing decisions and analyzing the differing choices of males and females in terms of entrepreneurial selections. Analysis of the collected data indicates that Indian Government policy, unskilled labor, entrepreneurial education, family background and caste are factors affecting the entrepreneurial growth rate in Bangalore. Entrepreneurship education in Bangalore is still in the early stages, thus, depriving the college students from acquiring gainful practical knowledge. The structure of a conventional learning system and lack of social experiences also affects the learning process. 2019, International Journal of Scientific and Technology Research. All rights reserved. -
Women chefs in Indian hospitality industry: Challenges and strategies /
International Multidisciplinary Research Journal, Vol.4, Issue 7, pp.117-132, ISSN No: 2231-5063. -
Reflections on the issues and determinants associated with women's career progression in hospitality industry at Bengaluru /
Social Sciences International Research Journal, Vol.2, Special Issue, ISSN: 2935-0544. -
Statistical Forecasting of Fat in Body Proportion Utilizing Nonlinear Anthropological Parameters and Density Evaluation
Body Fat Percentage (BFP) is an accurate body fat assessment, plays vital role in order to evaluate an individual's health status and disease risk. Traditional BFP assessments, such as dual-energy X-ray absorptiometry (DXA) and hydrostatic weighing are high in accuracy which is compromised by their cost and complexity. This research work focuses on creating a predictive BFP model using anthropometric techniques. For formulating and validating the proposed model, a benchmark dataset is used consisting of 252 samples having measures of weight, height, waist circumference (WC), hip circumference (HC), skinfold thicknesses along with air displacement plethysmography (ADP) based density estimates. For feature engineering, the most important values are selected such as body mass index, hip ratio etc., as well as logarithmic values and then the best artificial neural network model is trained. The proposed model is developed using quadratic polynomial terms with a literature-based space-cost function (r > 0.98), provided the best model with a Mean Absolute Error (MAE) of 1.5% and coefficient of determination R = 0.92 outperforming conventional works. 2025 IEEE. -
Volatility-Based Stock Categorization and Risk-Informed Investment Support System
This paper presents an application that will benefit novice investors by categorizing stocks by levels of volatility so users can better understand risk by average parameters and increase factors assessed for long-term wealth generation. The offering model supports portfolio creation by enabling novice investors to choose appropriate options based on their risk tolerance, something that would be more challenging for investors with limited financial savvy under different circumstances. To develop an investment companion application that reduces emotional investing and increases strategic long-term financial decision making through effective data visualization, especially for novices. An application that uses statistics on volatility to compartmentalize stocks by low, medium and high-risk options for selection, with the ability to create and assess a portfolio based on this criteria through a virtual interface. Increased investment construction accessibility, the ability to create diverse portfolios, and a foundation for subsequent advanced investment features like notifications and trend predictive analysis. 2026 IEEE. -
Enhancement of Accuracy Level in Parking Space Identification by using Machine Learning Algorithms
Parking space identification is a crucial component in the development of intelligent transportation systems and smart cities. Accurate detection of parking spaces in urban areas can significantly improve traffic management, reduce congestion, and enhance overall parking efficiency. This proposed model is focuses on enhancing the accuracy of parking space identification through the utilization of Support Vector Machine (SVM) algorithms. The proposed methodology involves the following steps. First, a dataset comprising labelled parking space images is collected and pre-processed to ensure optimal quality and consistency. Next, feature extraction techniques are applied to capture certain relevant spatial and textural information from the images in the dataset, enabling the creation of informative feature vectors. These feature vectors are then utilized to train a SVM model, which is well-known for its capability to handle complex classification tasks. To measure the effectiveness of the SVM-based approach, a comprehensive set of experiments is carried out using real-world parking data. The performance metrics is to analysis accuracy level of the parking space identification. Comparative analysis has been done by comparing the proposed SVM approach with other popular machine learning algorithmsto demonstrate the superiority. The results indicate that the SVM-based model achieves a significantly higher accuracy level in parking space identification compared to other existing algorithms. 2023 IEEE. -
Comparative Study on Gasoline and Methanol in a Twin Spark IC Engine
In search of a viable alternative to petrol and diesel, methanol, ethanol and biodiesel play an important role. Methanol and ethanol are traditional alternatives to petrol(gasoline) because of better engine performance and reduced emission of carbon monoxide, oxides of nitrogen (NOx), unburnt hydrocarbon (UBHC) and other harmful gases. This work represents the result of four sets of spark timings on engine performance and engine emissions when run on methanol and petrol. Exhaustive investigations are carried out on a variable compression ratio DTSi engine for both methanol and gasoline. Engine was run at full throttle and at a constant speed of 1600RPM. Theefficiency of the engine found to be enhanced with methanol fuel which has higher octane number and high laminar flame speed. Maximum efficiency was found to be ~25.45% and ~28.7% at compression ratio 10 for gasoline and methanol fuel, respectively. This is observed at 2624 BTDC (before top dead center) spark advance combination. Optimum compression ratio for gasoline and methanol is found to be 6.8 and 7.4, respectively, at this spark advance angle combination. Moreover, methanol fuel eventually emits lesser amount of CO, UBHC and NOx than gasoline under all experimental combinations. 2021, Springer Nature Singapore Pte Ltd. -
Strategic Integration of AI in Modern Data Management
The exponential growth of data from sources such as social media, IoT, and enterprise systems has catalyzed a transformative shift in data management practices. This paper explores the integration of artificial intelligence (AI), edge computing, cloud-native frameworks, and graph-based techniques to support intelligent, low-latency, and scalable data processing across complex ecosystems. It presents a comparative analysis of classical versus modern data architectures, highlighting how technologies like Graph Neural Networks (GNN4TS), reinforcement learning, and large language models (LLMs) enable more adaptive, interpretable, and automated pipelines. The study also addresses challenges in legacy system modernization, time-series modeling, and cyber threat detection while underscoring the role of AI in autonomous database management and metadata enrichment. Further, it examines critical risks - including explainability, adversarial vulnerabilities, concept drift, and privacy preservation - associated with AI-integrated data workflows. A structured overview of emerging paradigms such as neuro-symbolic AI, adaptive governance in multi-agent systems, and the potential of quantum computing provides a future-focused lens on intelligent data ecosystems. The insights presented aim to assist researchers, data engineers, and decision-makers in navigating the evolving landscape of AI-driven data management. 2025 IEEE. -
Small signal stability in a Microgrid using PSO based Battery storage system
This papers covers, modelling and analysis of a small microgrid with Battery Storage System (BSS). A sample microgrid is considered, it is analyzed for small signal stability, with and without BSS. Voltage, frequency and current THD which are considered to be the major attributes of stability in a microgrid, the behavior of these attributes is observed with and without BSS. The Battery storage system is connected to the considered microgrid through PV array, using PSO algorithm, which improves the stability of the system. Simulation is carried out using MATAB/ Simulink and the results are presented. Microgrid considered consists of PV array, Diesel Generator and Battery storage system. These sources are modelled according to the loads connected to the microgrid. BSS acts as emergency backup to the considered system and also provides small signal stability to the microgrid. Simulation is carried out with BSS and without Battery Storage in the Islanded mode. The obtained results show that microgrid with BSS is more stable during small disturbances and also acts as backup power supply. A Properly modelled microgrid can act as power backup for industries. 2022 IEEE. -
An Adaptive Cluster based Vehicular Routing Protocol for Secure Communication
In todays scenario, Vehicular Ad-hoc Network (VANET) is one of the modern fields in vehicle communication; it includes a large number of nodes that can be changed arbitrarily with the ability to link or exit the system anytime. Moreover, it has various complexities because of the attacks model in the transmission and communication channel. Besides, most of the attacks are known as black hole attack and wormhole attack. The presence of these attacks causes large damage in the data broadcasting region that ends in data drops or collapses. To defeat these problems, a novel Clustered Vehicle Location protocol for Hybrid Krill Herd and Bat Optimization (CVL-HKH-BO) technique is proposed. Thus, the proposed mechanism of hybrid krill herd and bat optimization is to detect and prevent attacks based on the fitness function. Moreover, secure communication can be enhanced by the proposed technique. Consequently, the solution to energy consumption and packet delay issues are solved using the CVL protocol. The projected strategy is implemented in the Network simulator (Ns-2) platform, and the outcomes show the node energy, overload and delay are minimized by increasing the quantity of packets transmitted in the network. Sequentially, the proposed technique is compared with existing techniques in terms of throughput, packet loss, delay time and data broadcasting ratio. Therefore, the duration of the node can be enhanced and can attain high energy capable data transmission. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Gender Differences in Social Capital and Job Search Methods in the Information Technology Industry in Bangalore
The Indian Journal of Economics Vol. 55, No. 3, pp 501-917, ISSN No. 0971-7927 -
Job search methods in the software industry in Bangalore: Does social capital matter? /
The Indian Journal of Labour Economics, Vol.61, Issue 4, pp.681-699, ISSN No: 0971-7927. -
Patriarchy and Wifehood: A Feminist Reading of One Part Woman and Singarevva and the Palace
Marriage is a socially approved relationship between a man and a woman that binds each other into a permanent, official relation of husband and wife. In a patriarchal culture, the husbands personify dominance and liberty, whereas the wives are expected to be the epitome of fidelity, fecundity and chastity. In the Indian context, the intense devotion of wives towards their husbands defines married women as pativratas. The present study intends to analyze the various aspects that contribute to and shape the formation of the identity of a wife in a marital space through Ponna and Singarevva, the female protagonists of the novels One Part Woman and Singarevva and the Palace, respectively. The paper demonstrates how these female protagonists identity as wives gets suppressed over a period of time and how they succeed in reconstructing their identities, sailing against all odds stacked against them. The paper views these issues through the feminist theoretical lens. 2024 IUP. All Rights Reserved. -
Influence of hydrothermal synthesis conditions on lattice defects in cerium oxide
Cerium oxide makes one of the most promising materials for chemical transformations in environmental and energy applications. Herein, the influence of hydrothermal conditions on the physico-chemical characteristics of cerium oxide prepared from salt solution via ammonia precipitation is analyzed. The systems are well characterized using SEM, TEM, XRD analysis, photoluminescence spectra, Raman spectra, TPR study. and XPS analysis. Normal aqueous conditions lead to particles of size ~8 ?nm, with truncated octahedral geometry, closer to spheroid shape (RT-Ce) bound by {111} and {100} planes. Elevated temperature facilitated preferential exposed {100} plane bounded cubic ceria structures of size ~15 ?nm (HT-Ce), which are stabilized by more number of anion vacancies. Low temperature synthesis yielded smaller sized particles with less crystallinity and higher surface area, when compared to hydrothermal route. Lattice defects, represented in terms of Ce3+ ions and associated lattice oxygen vacancies are seen in higher amounts in ceria synthesised via hydrothermal path, as supported by various characterization results. CeO2 achieved via hydrothermal path exhibited higher catalytic oxidation activity, which is examined using a model oxidation reaction, vis., CO oxidation. The enhanced activity of HT-Ce is explained through the defect structure induced facile redox shift in the system. 2021 Elsevier Inc. -
Bridging Financial and Operational Gaps in Supply Chain Finance: An Information Processing Theory Perspective
This paper explores the integration of financial and operational flows in Supply Chain Finance (SCF) through the lens of Information Processing Theory (IPT). Despite increasing adoption of SCF solutions like reverse factoring and trade credit, existing literature lacks a unified theoretical framework that captures both financial and organizational complexities. Drawing from 47 peer-reviewed articles in leading supply chain journals, this study identifies key SCF dimensionstask characteristics, environment, and interdependenceas primary sources of uncertainty and information processing needs. It then examines how IT systems, coordination mechanisms, and organizational design enhance processing capacity, enabling firms to build SCF capabilities such as risk assessment, supplier onboarding, and financial process standardization. These capabilities facilitate financial supply chain integration through data connectivity, embedded flows, and collaborative planning. The study contributes a comprehensive conceptual model that connects SCF uncertainties, processing strategies, and performance outcomes, addressing theoretical and managerial gaps. It further provides a foundation for future empirical research and strategic design of SCF systems to enhance supply chain resilience and financial efficiency. 2025 by the authors.