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Study on heat transfer and pressure drop in tube-in-tube helical heat exchanger
The present work aims to investigate the effect of different configurations of the tube-in-tube helically coiled heat exchanger. Commercial CFD codes were used to predict the fluid flow and heat transfer in a tube-in-tube helical heat exchanger. The model of different configurations of the inner tube has been simulated by varying the Dean number. The numerical results are verified and found to be in good agreement with reported data in the literature. Nusselt Number and friction factor are evaluated for different angular positions. The use of geometry E increases the Nusselt number and friction factor by 19.05% and 16% respectively at a Dean number of 4000 as compared with a circular tube as compared with the circular tube. 2021 Tamkang University. All rights reserved. -
AN ANALYSIS ON THE PORTRAYAL OF INDIA BY NATIONAL GEOGRAPHIC MAGAZINE
The research is an analysis on how the magazine ??National Geographic has portrayed India over the years and whether or how it has changed. National Geographic being an all American historical magazine might have its own ways of portraying particular nations. India being known for festivals, colors, superstition and snake charmers has always been portrayed countless number of times as only the above mentioned stereotypical explanation. May it be in movies, cartoons, books, etc., National Geographic being a credible magazine has never failed to bring forth to the world all historical aspects of any country. Bollywood, Spicy food, Religion etc. has been a hot topic for both Nat Geo magazine and television. The researcher wishes to find out if the magazine has portrayed India differently over the years. -
An analysis on the portrayal of India by national geographic magazine /
The research is an analysis on how the magazine National Geographic has portrayed India over the years and whether or how it has changed. National Geographic being an all American historical magazine might have its own ways of portraying particular nations. India being known for festivals, colors, superstition and snake charmers has always been portrayed countless number of times as only the above mentioned stereotypical explanation. May it be in movies, cartoons, books, etc., National Geographic being a credible magazine has never failed to bring forth to the world all historical aspects of any country. Bollywood, Spicy food, Religion etc. has been a hot topic for both Nat Geo magazine and television. The researcher wishes to find out if the magazine has portrayed India differently over the years. -
Optimal Allocation of Renewable Sources with Battery and Capacitors in Radial Feeders for Reliable Power Supply Using Pathfinder Algorithm
Allocating renewable energy systems (RESs) in an electrical distribution system (EDS) is crucial to achieving various objectives. However, their intermittency presents several challenges. In this connection, an efficient meta-heuristic pathfinder algorithm (PFA) is employed to determine the optimal location and size of photovoltaic (PV) and wind turbine (WT) systems, along with energy storage systems (ESS) and capacitor banks (CB) for both grid and islanding modes of operations. An objective function was formulated for loss reduction, greenhouse gas (GHG) emissions, and voltage profile improvement. The simulation results for the IEEE 33-bus EDS system are shown for two cases: grid-connected and islanding. The computational effectiveness of the PFA was compared with that reported in the literature. The PFA results showed an outstanding ability to resolve difficult optimisation problems. In addition, the optimal size of the RES when the network operates in the grid-connected mode can significantly improve the performance. The real power losses and GHG emissions were reduced by 48.49 % and 67.75% with PV systems and the other, respectively, whereas WT systems they are reduced to 69.68 % and 67.85 %, respectively. However, a combination of ESS, CB, and PV/WT can render the EDN sustainable for the islanding mode of operations. The Author(s). -
Political Optimizer-Based Optimal Integration of Soft Open Points and Renewable Sources for Improving Resilience in Radial Distribution System
A novel and simple meta-heuristic optimization technique viz., political optimizer (PO) is proposed in this paper to identify the size and optimal location of solar photovoltaic (SPV) system. The main objective is to minimize the distribution loss and is solved using proposed PO. The computational efficiency of PO is compared with the literature, and its superiority is highlighted in terms of global solution at initial stage. The physical requirements of SPV system via soft open points (SOPs) among multiple laterals are solved considering radiality constraints in second stage. The proposed concept of interoperable-photovoltaic (I-PV) system has been applied on standard IEEE 69-bus system and has shown the effectiveness in performance enhancement of the system. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Political Optimizer Algorithm for Optimal Location and Sizing of Photovoltaic Distribution Generation in Electrical Distribution Network
In this paper, the political optimizer (PO), a new and efficient socio-inspired meta-heuristic search algorithm, is proposed for the first time in this research for determining the ideal locations and capacities of photovoltaic (PV) distribution generation (DG) in electrical distribution networks (EDN). A multi-objective function is designed to lower distribution losses and voltage deviation indexes and maximize voltage stability, among other objectives. The computational efficiency of PO when solving the optimal allocation of PV systems in EDN is investigated on an IEEE 33-bus EDN. The results indicate that integrating small DGs at multiple locations has a better EDN performance than integrating a single significant DG in the network. The results also suggest that, as demonstrated by a comparative analysis of PO results and those of other related literature works, PO can deal with complex multi-variable optimization problems. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Markovian risk model with possible by-claims and dividend barrier
A MAP/PH risk model with possible by-claims and a dividend barrier is considered. Along with the main claim, a by-claim also can occur with a certain probability but by-claims are settled only after an inquiry and hence delayed. The model is analysed considering associated Markovian fluid models under the original timeline and an auxiliary timeline. Systems of integro differential equations (IDE) are developed for the Gerber-Shiu function (GSF) and the total dividends paid until ruin. Explicit expressions are obtained for the GSF of the models without and then with the barrier. Expressions are also provided for the moments of the total dividends paid until ruin. A dividends-penalty identity is given. The method is numerically illustrated with a two-phase model and sensitivity analysis of the model is done by varying some of the parameters involved. 2023 Inderscience Enterprises Ltd.. All rights reserved. -
Women influencers in e-commerce: Shaping the future for high-end products
Industry 5.0 represents a transformative shift in industrial practices, merging advanced technologies with human-centered approaches. This evolution emphasizes personalization, ethical considerations, and enhanced consumer experiences in e-commerce. Social media platforms, such as Instagram, TikTok, and Facebook, have revolutionized brand engagement by enabling targeted advertising, community building, and real-time interaction. Women influencers play a crucial role in this new landscape, using their personal brands to drive consumer trust and loyalty. They create authentic content and promote diverse, inclusive narratives. As e-commerce adapts to Industry 5.0, integrating technological advancements with a focus on human values and ethical practices becomes essential for business success and consumer satisfaction. 2025, IGI Global Scientific Publishing. All rights reserved. -
Hierarchically porous RhB-encapsulated ZIF-7 as a dual-emission fluorescence probe for ultrasensitive detection of melamine in infant formulations
Melamine is an unauthorized food additive and a highly concerning adulterant in foods that can occur either accidently or intentionally in dairy products, with potential health risks upon exposure to higher concentrations. An ultrasensitive fluorescent probe based on dual emissive RhBx@ZIF-7 was developed to detect melamine. In this study, a fluorescent dye, Rhodamine B (RhB), was successfully encapsulated into the metal-organic framework (MOF) pores of ZIF-7 to form a fluorescent probe (RhB30@ZIF-7), with dual emission properties to enable the detection of melamine at low concentrations. RhB30@ZIF-7 was optimized by varying experimental parameters, including temperature (25 C), pH (7.0), incubation time (10 min), and probe concentration (1 mg mL?1), to enhance its sensitivity and selectivity. The observed fluorescent quenching towards melamine was primarily attributed to the mechanisms of the internal filtering effect (IFE), due to absorption of the excitation wavelength by melamine, causing a turn-off response in the system. The limit of detection (LOD) and limit of quantification (LOQ) were found to be 0.47 ?M and 1.4 ?M, respectively, with an R2 of 0.99. This study reveals the previously unexplored enhanced fluorescence of RhB30@ZIF-7 and elucidates the contribution of the intermolecular interaction between RhB and ZIF-7 to fluorescence sensing, paving the way for food safety monitoring. 2025 RSC. -
K shell X-ray intensity ratios, K-Li, K-L, and K-M vacancy transfer probabilities of Ba and Tl following internal conversion process
K shell X-rays of barium and thallium following internal conversion decay in Cs137 and Hg203, respectively, were detected using a Si(Li) X-ray detector coupled to PC-based 8k multichannel analyser employing the method suggested earlier by our group. The K shell X-ray intensity ratios and vacancy transfer probabilities for thallium and barium were calculated. The obtained results are compared with theoretical, semiempirical, and others' experimental results obtained via photoionization as well as decay processes. The effects of beta decay and internal conversion on X-ray emission probabilities are discussed. 2014 Published by NRC Research Press. -
Indian Stock Market Prediction Using Neural Networks: A Comparative Analysis
Predicting stock prices remains a challenging problem due to the highly dynamic and nonlinear nature of financial markets. Traditional statistical models like ARIMA and GARCH often fail to capture the complexities inherent in stock market data. This paper investigates the use of deep learning techniques, focusing on Convolutional Neural Networks (CNNs) and a hybrid CNN-LSTM ensemble model for stock price prediction in the Indian stock market. The CNN model efficiently extracts temporal patterns from sequential data, while the CNN-LSTM ensemble leverages temporal dependencies for improved long-term prediction accuracy. Historical data from Tata motors, spanning over two decades, was used to train and evaluate the models. Experimental results highlight the CNN-LSTM ensemble's superior performance in capturing volatile trends and long-term dependencies, with a notable decrease in test loss compared to standalone CNN. This study underscores the effectiveness of hybrid deep learning architectures in enhancing prediction reliability, paving the way for more adaptive and robust financial forecasting systems. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Internet of Things and Cloud Computing Involvement Microsoft Azure Platform
The rapid advancement of cloud technology has resulted in the emergence of many cloud service providers. Microsoft Azure is one among them to provide a flexible cloud computing platform that can scale business to exceptional heights. It offers extensive cloud services and is compatible with a wide range of developer tools, databases, and operating systems. In this paper, a detailed analysis of Microsoft Azure in the cloud computing era is performed. For this reason, the three significant Azure services, namely, the Azure AI (Artificial Intelligence) and Machine Learning (ML) Service, Azure Analytics Service and Internet of Things (Io T) are investigated. The paper briefs on the Azure Cognitive Search and Face Service under AI and ML service and explores this service's architecture and security measures. The proposed study also surveys the Data Lake and Data factory Services under Azure Analytics Service. Subsequently, an overview of Azure Io Tservice, mainly Io THub and Io TCentral, is discussed. Along with Microsoft Azure, other providers in the market are Google Compute Engine and Amazon Web Service. The paper compares and contrasts each cloud service provider based on their computing capability. 2022 IEEE. -
Adoption of digital technologies in the procurement process to improve supplier lead time
Supply chain is a complicated process involving a number of stakeholders. A proper integration of all the stakeholders helps to improve the efficiency of the system in terms of time, money and effort. Adoption of digital technology has been a hindrance in many industries, thereby affecting their business processes. The study aims to throw light on the adoption of digital technologies in procurement process to improve supplier lead time in the automotive industry. An observational study was conducted in a major automotive supply chain company in South India. Researchers tried to identify the possible contributing factors to improve supplier lead time and derive the root cause of the issue. A framework for an advanced shipping notice portal was created which can help both the supplier and recipient. Digital technology adoption can increase supply chain efficiency, decrease manual error rates, and streamline communication. Additionally, the portal can serve as a centralized hub for data sharing, promoting improved teamwork and real-time information sharing. 2024 by IGI Global. -
Life Cycle Assessment of Battery Energy Storage Technologies for Vehicular Applications
The necessity of sustainable energy sources and storage technologies is emerging due to growing energy demands. Thus, it encourages the need to perform sustainability analysis in terms of energy efficiency. For battery technologies, energy production and recycling holds a significance. In this study, the direct and indirect requirements of various battery technologies including production to transportation. The five battery technologies taken into account for the analysis are Lithium ion, Nickel Metal Hydride, Lead acid, Valve Regulated lead Acid, and Nickel Cadmium. The characteristics analyzed here are cycle life, energy density and energy efficiency. The study also covers the life cycle assessment in an structured way from raw to evaluation of materials, energy flow, installation, usage to end of life. The Authors, published by EDP Sciences, 2024. -
NEUROSYMBOLIC AI FOR CONTEXT-AWARE RESOURCE MANAGEMENT IN 5G SMART HEALTHCARE NETWORKS
Context-aware resource management in 5G Utilising neurosymbolic AI has growing impacts in the next-generation healthcare systems as smart healthcare networks to overcome the crucial issues of optimal service delivery and dynamic resource allocation. The 5G technology is adopted in healthcare networks for real-time processing, low latency, and high reliability that supports a vital application as telemedicine and remote patient monitoring. The resource management process of existing model rapidly fails in complicated, context-dependent situation with dynamic demands. To overcome these limitations, we proposed improved framework that combines a deep learning (DL) models for context extraction and symbolic reasoning process for decision-making. To determine the contextual patterns, the DL component analyses the multi-source data, as patient vitals, network conditions, and device status by utilising Transformer and Graph Neural Networks (GNNs). These data fed into symbolic reasoning module employ a knowledge graph and a rule-based system to dynamically allocate and distribute the resources based on the predetermined healthcare policies and requirements. Experimental results of this study showcase the improvements by attaining a reduction in latency, enhances in resource utilisation efficiency, and improved Quality of Service (QoS) for essential healthcare applications. In 5G-enabled smart healthcare systems, the results ensure a proposed model potential to transforms a resource management and ensure context-aware, versatile, and dependable service delivery for enhanced patient outcomes. 2025, Scibulcom Ltd.. All rights reserved. -
Role of psychological well-being, quality of life and distress tolerance in caregivers of geriatric population: an Indian exploratory study
Purpose: This study aims to gain an understanding of how caring for an ageing population affects caregivers psychological well-being, quality of life and ability to tolerate distress. This study provides valuable insights into the challenges faced by family caregivers and underscores the critical need for comprehensive support systems. Design/methodology/approach: A correlational method and cross-sectional research design was used for the study. For this, a sample of 200 caregivers in the age range of 2560 years who were taking care of the geriatric population above the age of 70 years for a minimum of one year were chosen. Four questionnaires ? Burden Scale for Family Caregivers, Psychological Well-Being Scale, World Health Organizations Quality of Life Scale-BRIEF version and Distress Tolerance Scale were chosen. Correlation and multivariate regression were calculated using statistical package for social sciences (SPSS) 21 and Jamovi 3.4.1. Findings: This study found that there is a negative correlation of caregiver burden with psychological well-being, quality of life and distress tolerance. The sub-domains of self-acceptance, psychological health and tolerance levels were most impacted for the caregivers. Through multivariate regression, it was found that the caregiver burden significantly predicted psychological well-being and quality of life. Research limitations/implications: This study focuses on the English-speaking caregivers which may overlook the diverse linguistic and cultural variations within the broader caregiver community in India and the data collection exclusively targeted family caregivers providing support to geriatric population without chronic illnesses. This restriction could potentially limit the generalizability of the findings to the broader caregiving context. Practical implications: The implications of this research are that for caregivers, this study underscores the importance of tailored support programmes that address the negative impact of caregiver burden on psychological well-being and quality of life. Health-care professionals can use the findings to incorporate mental health assessments and interventions within caregiving contexts, recognizing the interconnected nature of these variables. Policymakers can use the findings to inform policies related to caregiver support and health-care resource allocation. Originality/value: In India, the social norm is that children are expected to take care of their parents when they become old. Taking care of elderly parents can be challenging, even emotionally. As a result, this study will focus on how caregivers psychological well-being, quality of life and ability to tolerate distress are affected. Consequently, promoting the creation of community support groups and workplace mental health programmes which could give caregivers a forum to voice their concerns. 2024, Emerald Publishing Limited. -
Improvement in food preservation with nanozymes
To ensure safety, quality, and extended shelf life of perishable food products, food preservation is a critical aspect of food industries. Concerns regarding the potential health risks and loss of nutritional value of food because of traditional methods of preservation such as using chemical additives and high temperatures have set the need for finding alternative methods of preservation, for the betterment of health and the environment. Enzymes have the potential to kill microorganisms. Enzymes such as oxidases, peroxidases, hydrolases, catalases, and others have been extensively studied for their microbicidal activities. However, natural enzymes have shortfalls as they can be easily denatured and cannot be recycled. Nanozymes have gained the limelight in recent years as they can be applied in food industries to overcome the shortfalls of natural enzymes. They embody the highly beneficial properties of both enzymes and nanoparticles at the same time. Due to their enzyme-mimicking properties and versatile applications, nanozymes have become more popular in the last few years. Nanozymes have evolved as a promising alternative for food preservation and the detection of various contaminants in food. However, before the integration of nanozymes into the food industry, several factors such as their stability, biocompatibility, longevity, toxicity, cost-effectiveness, scalability, and regulatory approval need to be addressed. This chapter discusses the concept of nanozymes, its classification, and various applications in food industries specially designed for preservation of food products. 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Greener Assembly of Nano Catalysts and Sustainable Applications of Magnetically Retrievable and Plasmonic Nano Catalysts
Since ages, catalysts have played a pivotal role in accelerating the production and lowering the cost of a plethora of industrially important commodities. The latest in the scenario are nanocatalysts, which offer a wide array of advantages ranging from improved reaction rates to higher rates of recyclability. However, factors such as stability and support systems must be fine-tuned to achieve maximum efficiency. In accordance with the principle of sustainability, green synthesis methods have propelled the development of a range of nanocatalysts that can be applied in various domains, such as the food industry and biofuel production. Simultaneously, heterogeneous catalysis is gaining more attention globally, primarily due to the ease of recoverability of the nanocatalysts and in this context, magnetically retrievable nanocatalysts are indeed a boon for the green synthesis and sustainable production. Nanocomposites combining plasmonic and catalytic components with noble metal nanoparticles (Au and Ag) and doped semiconductor nanostructures have gained interest in recent years owing to their utility in multiple sectors by virtue of their ability to convert sunlight to chemical energy. The current review describes some methods for the synthesis of such nanocatalysts and their applications in diverse domains. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Data science: simulating and development of outcome based teaching method
The educational researcher has a wealth of options to apply analytics to extract meaningful insights to improve teaching and learning due to the growing availability of educational data. Teaching analytics, in contrast to learning analytics, examines the quality of the classroom environment and the efficacy of the instructional methods used to improve student learning. To investigate the potential of analytics in the classroom without jeopardizing students' privacy, we suggest a data science strategy that uses simulated data using pseudocode to build test cases for educational endeavors. Hopefully, this method's findings will contribute to creating a teaching outcome model (TOM) that can be used to motivate and evaluate educator performance. In Splunk, the study's simulated methodology was carried out. Splunk is a real-time Big Data dashboard that can gather and analyze massive amounts of machine-generated data. We provide the findings as a set of visual dashboards depicting recurring themes and developments in classroom effectiveness. Our study's overarching goal is to help bolster a culture of data-informed decision-making at academic institutions by applying a scientific method to educational data. 2023 IEEE. -
State of local governance and urban development problems: A study of Bengaluru
[No abstract available]