Browse Items (11808 total)
Sort by:
-
Antecedents of organic food consumption in Delhi NCR
The consumption of organic food in increasing rapidly in the country. It has a significant impact on the environment, individuals and public health. This is an attempt to understand the antecedents of organic food and try to re-establish the relationship between the attributes of organic food, the utilitarian and hedonic attitudes and consumer purchase intentions. The SOR model has been used to support the theoretical framework for conducting the research on organic food products. The nutritional values, sensory appeal, environmental concern price and natural content of organic food products have significant and positive relationship on utilitarian and hedonic attitudes of the consumer. Even utilitarian and hedonic attitudes have a positively strong relationship on consumer purchase intentions for organic food products. 2021 Ecological Society of India. All rights reserved. -
Spray dried nano oxide ceramics for free flowing plasma spray coating powders and battery material processing
Advanced materials are widely used in electronics, aerospace and automobile industry devices and also in substances synthesized for food, medical and pharmaceutical industries. The quality of the base material powder has high influence on the resulting material body (the product) which goes into the manufacture of the device. To name a few (a) flowable ceramic powders from agglomerated nano ceramic powders for plasma spray coatings with the right sprayable powder characteristics (b) advanced graphene encapsulated nano ceramic oxide powders with uniform conductive coating layers as promising electrodes in Li-Ion batteries, (c) advanced bio-ceramic oxides such as hydroxy-apatite ceramic materials with right amounts of moisture, density and composition consistency as bone and dental implants in bio-ceramics research are examples. Among the many processing methods to achieve the base powders from nano ceramic raw materials the most capable and efficient is 'Spray Drying' which results in powders with high purity with well-defined properties. Complex composite by spray drying is achieved where the 'matrix host' material is encapsulated by the 'guest layer' with special properties. This paper illustrates results pertaining to experimentation via spray drying and microscopic investigation by using SEM associated with EDS on (a) Yttria stabilized zirconia plasma sprayable powders for Thermal Barrier Coatings application and (b) nano yttria stabilized zirconia incorporated into microns sized alumina powders for enhanced densification, to understand the significant role of process parameters on uniformity and consistency of the spray dried products. Information based on review on spray dried Li-ion battery materials is also included. Published under licence by IOP Publishing Ltd. -
A comparative study of Ravi Chopra's Mahabharata(1988) on Doordarshan and Siddharth Anand Kumar's Mahabharat (2014) on Star Plus /
Portrayal of characters on both Ravi Chopra’s Mahabharata and Siddharth Anand Kumar’s Mahabharata on Star Plus. Identifying the costumes of characters of old Mahabharata and new Mahabharata. Identifying the visualization and special effects in both old and new Mahabharata. -
Perception of paid news among media students in Bangalore /
Gone are the days when advertising were among the major source of revenue for media organizations. The recent past has witnessed the rise of paid news in media organizations where they get paid to publish favourable news about a person or organization. This practice is s serious blow to the journalistic ethics of the country. -
Predictive Analysis of the Recovery Rate from Coronavirus (COVID-19)
Estimation of recovery rate of COVID-19 positive persons is significant to measure the severity of the disease for mankind. In this work, prediction of the recovery rate is estimated based on machine learning technology. Standard data set of Kaggle has been used for experimental purpose, and the data sets of COVID cases in Italy, China and India for these countries are considered. Based on that data set and the present scenario, the proposed technique predicts the recovery rate. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Circular supply chains in manufacturingQuo vadis? Accomplishments, challenges and future opportunities
Circular approach in manufacturing supply chain (SC) operations yields multiple benefits through optimal utilisation and consumption of resources. This study maps the scope and structure of circularity in the manufacturing SC discipline and explores the evolution of the domain over time. We review 946 journal articles published between 2013 and September 2023. Our study identifies key drivers and barriers to circular economy (CE) deployment in manufacturing SC operations, bibliometric parameters, emerging research themes, decision support tools, theories and applications. Using the theory extension approach, we propose a strategic framework to fortify the deployment of circularity in SCs. This comprehensive study renders a methodological contribution through combined descriptive content analysis and bibliometric and network analyses to evaluate the circular manufacturing SC operations concepts, theories and applications. We posit that manufacturing firms require to deploy innovation-led approaches to embed the CE strategies in their SC operations. We find that the studies investigating green skill development and circularity-culture adoption can facilitate manufacturers to understand the efficacy of circularity in their SC operations. The findings of this study can facilitate the practitioners to identify the links between the CE approaches and their strategic implications and examine CE implementation at the strategic level. 2024 The Authors. Business Strategy and The Environment published by ERP Environment and John Wiley & Sons Ltd. -
A Novel Ensemble based Model for Intrusion Detection System
In the present interconnected world, the increasing reliance on computer networks has made them susceptible to multiple security threats and intrusions. Intrusion Detection Systems (IDS) is essential for shielding these networks by detecting and mitigating potential threats in real-time. This research paper presents an in-depth study of employing the Random Forest algorithm for building an effective intrusion detection System. The proposed IDS uses the power of the Random Forest algorithm, a popular ensemble learning technique, to detect various types of intrusions in network traffic effectively. The algorithm integrates more than one decision trees to produce a robust and accurate classifier, capable of handling large-scale and complex datasets typical of network traffic. The proposed system can be used in various industries and sectors to protect critical assets, ensuring the uninterrupted operation of computer networks. Evolving cyber threats have encouraged further research into ensemble analytics methods to increase the resilience of Intrusion Detection Systems in an ever-changing threat landscape. 2024 IEEE. -
Parkinsons Disease Progression Prediction using Advanced Machine Learning Techniques
Parkinson's disease (PD) is a neurodegenerative condition that affects people over time and significantly lowers their quality of life. Patients with PD experience both motor and non-motor symptoms. Through clinical evaluation, the Unified Parkinson's Disease Rating Scale (UPDRS) is used to quantify the severity of Parkinson's disease. No definitive diagnostic tests for PD currently exist. Emerging machine learning techniques show potential to forecast future UPDRS scores for making informed medical decisions and enable better disease management. This paper studies research leveraging proteomic data to forecast PD prognosis, focusing on advanced machine learning techniques like CatBoost Regressor, ElasticNet, XGBoost Regressor, RandomForest Regressor, ExtraTrees Regressor and DecisionTree Regressor. 2024 IEEE. -
Exploring Socio-Political Factors and Quality of Life Among LGBT Individuals in India
The quality of life of queer individuals in India is a result of a complex sociopolitical climate which is what this study aims to explore through qualitative methodology. Previous research has explored the social factors that impact the wellbeing of LGBT individuals in western countries, while the impact of politics on the wellbeing of marginalized groups is still largely unexplored. Through thematic analysis, this study found that family support and peer networks are the two most important social structures that determine the quality of life of LGBT emerging adults in India, whereas the impact of politics on wellbeing depends on the level of political awareness of the participants and their socio-political privilege in terms of caste, class and gender. However, there were significant differences in the relevant factors that affect the quality of life for cisgender and transgender participants which leaves room for further research. The findings indicate intra-community conflicts and changing dynamics within the community, and there needs to be extensive research on understanding the intersectionality of different identities within the community and their impact on the lives of queer individuals. 2024 Taylor & Francis Group, LLC. -
Smart Sensory Approach for Soil Health Tracking based Precision Farming
Internet of Things (IoT) technology will have an impact on every area in the future as it will make everything intelligent, which will affect everyone's daily lives. It is a network composed of many devices that can configure themselves. The use of IoT in smart farming is transforming traditional agricultural practices by reducing crop loss, improving them, and making them more cost-effective for farmers. The study's goal is to propose a technological model for soil health monitoring that uses smart sensors and intelligent methods to communicate with farmers through a variety of channels. Farmers will benefit from the real-time farm data (temperature, humidity, soil moisture, UV index, and IR) that allows them to practice smart farming while increasing crop yields and conserving resources. 2023 IEEE. -
Series Preface
[No abstract available] -
Message from General Chair
[No abstract available] -
Conclusion
[No abstract available] -
Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications
The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. 2021 Elsevier Inc. All rights reserved. -
Multilevel Quantum Inspired Fractional Order Ant Colony Optimization for Automatic Clustering of Hyperspectral Images
Hyperspectral images contain a wide variety of information, varying from relatively large regions to smaller manmade buildings, roads and others. Automatic clustering of various regions in such images is a tedious task. A multilevel quantum inspired fractional order ant colony optimization algorithm is proposed in this paper for automatic clustering of hyperspectral images. Application of fractional order pheromone updation technique in the proposed algorithm produces more accurate results. Moreover, the quantum inspired version of the algorithm produces results faster than its classical counterpart. A new band fusion technique, applying principal component analysis and adaptive subspace decomposition, is successfully proposed for the pre-processing of hyperspectral images. Score Function is used as the fitness function and K-Harmonic Means is used to determine the clusters. The proposed algorithm is implemented on the Xuzhou HYSPEX dataset and compared with classical Ant Colony Optimization and fractional order Ant Colony Optimization algorithms. Furthermore, the performance of each method is validated by peak signal-to-noise ratio which clearly indicates better segmentation in the proposed algorithm. The Kruskal-Wallis test is also conducted along with box plot, which establishes that the proposed algorithm performs better when compared with other algorithms. 2020 IEEE. -
Message from the General Chairs
[No abstract available] -
Identification of emission-line stars in transition phase from pre-main sequence to main sequence
Pre-main-sequence (PMS) stars evolve into main-sequence (MS) phase over a period of time. Interestingly, we found a scarcity of studies in existing literature that examine and attempt to better understand the stars in PMS to MS transition phase. The purpose of this study is to detect such rare stars, which we named as 'transition phase' (TP) candidates-stars evolving from the PMS to the MS phase. We identified 98 TP candidates using photometric analysis of a sample of 2167 classical Be (CBe) and 225 Herbig Ae/Be (HAeBe) stars. This identification is done by analysing the near-and mid-infrared excess and their location in the optical colour-magnitude diagram. The age and mass of 58 of these TP candidates are determined to be between 0.1-5 Myr and 2-10.5 M?, respectively. The TP candidates are found to possess rotational velocity and colour excess values in between CBe and HAeBe stars, which is reconfirmed by generating a set of synthetic samples using the machine learning approach. 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.