Christ University Bengaluru: Open Journal Systems
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Optimization of Single-Seller Multi-item in Multiple Outlets Distribution Network Fuzzy Inventory System with Lead Time and Carbon Emission Cost
No full textManaging multiple products across various locations reduces total costs through consolidated replenishment. This strategy reduces ordering costs because fewer transactions result in better pricing. It also reduces shipping costs by using combined shipments to minimize transportation expenses. The objective is currently inaccurate due to several variables that are not well-defined. Hexagonal fuzzy numbers are utilized in this model to account for the uncertain nature of buyer and supplier parameters. Optimizing the fuzzy objective function is challenging because its output value remains uncertain. The model is solved using the alpha cut technique combined with the Lagrangian method, while the fuzzy counterparts of the remaining constraints are available. An algorithm is developed to determine the optimum order size for each item at every outlet. This approach simultaneously minimizes the joined entire price for the entire inventory system. Evaluation of fuzzy multi-item in multi-outlet distribution network inventory system against crisp multi-item in multi-outlet distribution network inventory system is concluded with numerical illustrations. Finally, graphical representations of the proposed system's performance are provided. This fuzzy inventory framework is effective in optimizing results for multi-item across various outlets
Examine the Impact of Curriculum Components on Students' Employability Potential: A Study on Undergraduate Tourism Students
No full textThe major goals of education are to educate students, equip them with the necessary skills to support themselves, and prepare them for success in their selected areas of work. The purpose of this study is to examine the impact of curriculum components on students’ employability potential. The target population of the study consists of institutions and universities in the North Indian region. A total of 360 students enrolled in bachelor's programs and taking tourism courses in the regular mode were approached for the study. To analyze the collected data, SPSS version 24 and AMOS version 21 were used. Himachal Pradesh, Punjab, Haryana, and Uttar Pradesh were taken into consideration. Exploratory factor analysis and confirmatory factor analysis, along with structural equation modeling (measurement model and structural model), were employed, revealing that the generic skills and functional area skills of curriculum structure design have a significant positive influence on students’ employability potential
QRMHF-DNK: Hybrid Optimization and Deep Kernel Approach for Fake News Detection
No full textIn this study, QRMHF-DNK (Quasi Reflection Metropolis Hasting Firefly- Deep Neural Kernel), a hybrid framework is designed to improve fake news detection on benchmark datasets. The framework integrates three main stages: data preprocessing to reduce sampling errors, feature selection using a swarm-based optimization strategy, and classification using a deep neural kernel model. This combination enables effective handling of high-dimensional textual data while accurately identifying informative features for classification. The proposed framework was evaluated on a publicly available Kaggle fake news dataset and compared with existing cooperative and multilingual deep learning methods. Experimental results show that QRMHF-DNK achieves a precision of 0.98 and recall of 0.95, with a sampling error of 0.0671%, indicating that the sampled data closely represents the true class distribution. These results demonstrate the effectiveness of the proposed approach on the evaluated dataset and suggest its potential applicability to fake news detection tasks, while further validation on additional datasets is left for future work
White Paper: Artificial Intelligence In The Automotive Industry 2.0
Full text linkArtificial Intelligence (AI) is changing the automotive industry across the world. It is helping the industry to work in new and improved ways. This change is considered one of the most important technological developments after the invention of the internal combustion engine. Today, AI is used in many stages of the automotive value chain. It supports vehicle design, improves manufacturing processes, and helps in quality control. AI also plays a major role in autonomous driving, smart vehicle connectivity, and customer support systems such as predictive maintenance and service recommendations. Technologies such as machine learning, deep learning, computer vision, IoT sensors, 5G networks, and edge computing are widely used in modern vehicles. These technologies help automotive companies increase accuracy, reduce human effort, and improve overall efficiency. AI systems also help vehicles understand their surroundings, make decisions, and react to road conditions in real time. This white paper explains the basic concepts of Artificial Intelligence used in the automotive sector. It discusses practical use cases, current challenges, and future opportunities. The paper is intended to support students, researchers, industry professionals, and policymakers who want to understand how AI can improve the future of mobility
Derivation of the Ginzburg-Landau Equation and Estimation of the Heat Transfer in a Rayleigh-Bénard Convection of a Micropolar fluid with Time Periodic Body Force
Full text linkThis study examines the behavior of a micropolar fluid in a Rayleigh–Bénard configuration under a time-varying gravitational force. A scaled fourth-order Lorenz model is employed to describe weakly nonlinear convection. The model conserves energy and retains all the essential characteristics of the classical Lorenz system. The scaled Rayleighnumber and the Ginzburg-Landau equation are derived using the Venezian method. The graphs showing the variation of the correction Rayleigh number with the modulation frequency for different parameter combinations are plotted, and it is found that the system supports supercritical motion. Furthermore, an analytical expression for the time-average Nusselt number is obtained and plotted for various values of the parameters, and it is found that the presence of micropolar fluid generally promotes the heat transfer.
Study of Pre-Chaotic and Post-Chaotic Motions in Internal Heat Generation Driven Convection of Palm Oil-Based Nanoliquids: Rigid-Rigid Boundaries
Full text linkThe paper investigates both linear and non-linear regimes of convection in nanoliquids having palm-oil as the base with internal-heat-generation (IH G ) dominating buoyancy. Palm oil is used with well-dispersed nanoparticles of either copper or titanium dioxide. We adopt a formulation that gives an IH G - based Rayleigh number as an eigenvalue. The effective thermophysical properties are evaluated using mixture theory and phenomenological models, leading to a modified Rayleigh number that involves a dimensionless factor, F, representing the influence of nanoparticles loading. The Maclaurin series expansion method is used in the linear stability analysis to represent the eigen function as a power series. For the nonlinear regime, the Galerkin-Fourier method helped in deriving the generalized-Lorenz-model and thereby the Stuart–Landau equation is arrived at to describe the amplitude evolution near the convection threshold. The approach enhances understanding of how internal heat generation affects convective and chaotic flows in nanoliquids and offers valuable guidance for optimizing thermal management and energy system performance. Palm oil-based nanoliquids containing either copper or titanium dioxide nanoparticles have contrasting thermal and chemical properties and lead to distinct enhancements in heat transfer performance, stability, and response to IH G . Chaotic motion is shown to be impossible in the considered palm-oil-based nanoliquids due to them being high Prandtl number liquids. The results of the problem have immense applications in thermal energy problems involving coolants and also in thermal-storage devices.
Granular Estimation of the Female Workforce in the Tourism Industry of India
No full textTravel and Tourism contributes more than 5% of India’s GDP and generates direct employment for at least 1.7 crore people. Combining direct and indirect employment (such as transport logistics, handicrafts production, local artisans, etc.), the tourism industry influences 4 to 7 crore jobs in India. The industry is women workforce-friendly and has the potential to generate tens of lakhs of additional job opportunities for women. The government of India is therefore driving numerous initiatives and drafting policies for the tourism industry to grow faster and thereby generate more employment opportunities for women. A key challenge in drafting these policies and monitoring their impact is the lack of women workforce data at a granular level. In this paper, we leverage quantitative techniques from Linear Algebra to estimate the women workforce in tourism-related industries at a granular level using the macro-level data published by government agencies. Our quantitative techniques are general and may in future be used to estimate the women workforce at an even more granular level, such as the women workforce in specific tourism-related industries in specific districts
India-Russia Dynamic Relations in the Context of Indian Foreign Policy
Full text linkHistory has witnessed a time-tested relationship between India and Russia that has evolved into a legacy. However, the current ongoing systemic geopolitical changes in the world are creating such uncertainty that both nations are facing some difficulties in maintaining their relations. Hence, despite Western efforts to isolate Russia at the global level, both India and Russia have maintained cordial relations with each other, prioritising defence and economic cooperation amid a complex geopolitical landscape, which highlights their autonomous strategy. In this context, this research paper presents India’s foreign policy from the perspective of how conscious both India and Russia are about their relations and what both countries are taking essential steps to fulfil their national interests. Under the realist framework, the research paper emphasises the national interests, power balance, and security of both countries, especially in the aftermath of the Russia-Ukraine war. This research analyses the relationship from a state-centric perspective, where both countries are motivated to protect their existential interests, whether through balancing efforts or strategic autonomy. Pointing to India’s neutrality and autonomous policy, the paper also evaluates and outlines the prospects of relations between the two countries, highlighting major obstacles. It examines the key factors strengthening the privileged India-Russia relationship. Lastly, an effort has been made to find a smooth path to enhance their trusting and cordial relations by removing obstacles
