Drivers of Customer Retention: An Introspection Into Indian Retail Customers
Customer Loyalty; Customer Retention; Customer Satisfaction; India; Retailing; Switching Cost
There is a wide variety of choices for the modern retail customer including multiple retail formats. The success of the retail establishments has a great reliance of customer retention, which is an essential attribute to achieve profitability. This study takes in to consideration to extract the factors responsible for customer retention which in turn assists in increasing the customer base. The prime objective of the study is to ascertain the influence of customer satisfaction, switching costs and customer loyalty on customer retention. Whereas, the second one is to explore the effect of demographic factors on customer retention. The sample size of this study was 600 respondents who were chosen for the full-fledged study. The statistical techniques used for final analysis were structural equation modelling and regression. The findings subsequent to the statistical analysis and interpretation concluded that customer loyalty, customer satisfaction and switching cost have the strongest effect on customer retention in retails. Customer satisfaction alone is not every time an indicator of customer loyalty. A loyal customer will spread positive word of mouth to other prospective customers about the retail. Occupation of respondent has a major influence on customer retention dimensions. 2021 Management Development Institute.
https://doi.org/10.1177/09722629211043592 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116573823&doi=10.1177%2f09722629211043592&partnerID=40&md5=db3a7f5b2cfacb811ffcce66b2bffa4e
Mathew J., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Influence of Planting Methods on Growth, Yield and Storage of Onion (Allium cepa L.) var. Bhima Shakti
Non pelleted; Pelleted; Seed drill; Transplanted
Background: Successful crop production in any crop depends on the good agronomic practices. Being a commercial crop, onion needs good attention during the crop growth stages, most of the times, in onion cultivation farmers follow broadcasting method which leads to the wastage of seeds, seedling mortality and poor germination and it will affect the total yield and productivity. Methods: To identify the best planting method an investigation on performance of seed drill versus transplanted onion was conducted at University of Agricultural Sciences, Main Agriculture Research Station, Dharwad. Result: Results indicated that, T3- (Transplanting) performed superior for all the vegetative and yield parameters studied. Plant height 55.57 cm, leaf number (7.86, 8.29 and 8.08 in pooled), Leaf width (1.03 cm, 0.99 cm pooled 1.01 cm). Total yield: (21.97 t/ha, 22.05 t/ha and 22.01 t/ha), marketable yield (20.74 t/ha 20.95 t/ha and 20.85 t/ha), bulb weight (64.00 g, 53.00 g and 53.90 g in pooled, analysis). From this, it can be concluded that transplanting of onion was better compared to other methods. (2024), (Agricultural Research Communication Centre). All rights reserved.
Jeevitha D.; Chimmalagi U.; Adishesha K.; Hosamani G.B.; Vinay T.V.; Dharmatti P.R.
Indian Journal of Agricultural Research, Vol-58, No. 5, pp. 885-888.
Agricultural Research Communication Centre
https://doi.org/10.18805/IJARe.A-6217 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208395661&doi=10.18805%2fIJARe.A-6217&partnerID=40&md5=540df867588ccb753ba371e92b157c54
Jeevitha D., Department of Agriculture, Karunya Institute of Technology and Sciences, Tamil Nadu, Coimbatore, 641 114, India; Chimmalagi U., Department of Agriculture, Karunya Institute of Technology and Sciences, Tamil Nadu, Coimbatore, 641 114, India; Adishesha K., Department of Plant Physiology, School of Agriculture, Mohan Babu University, Andhra Pradesh, Tirupati, 517 102, India; Hosamani G.B., Department of Entomology, M.S. Swaminathan School of Agriculture, Centurion University of Technology and Management, Odisha, Gajapati, 761 211, India; Vinay T.V., Statistics in Business Analytics, School of Business and Management, Christ University, Karnataka, Bengaluru, 560 001, India; Dharmatti P.R., University of Agricultural Sciences, Karnataka, Dharwad, 580 005, India
OTT Enchantment: Decoding the Secret of Millennials Subscription Intentions
Continuance Intention; Millennials; OTT; Purchase Intention; Subscription Intention; U&G Theory
This study explores the factors that affect intention and choices of millennials for subscription of Over-The-Top (OTT) platforms. The study involved a mixed-methods approach, involving exploratory and descriptive design. The outcome of the study showed that there is a profound impact of demographic variables on the subscription intention. Results also indicated that factors like convenient navigation, information seeking, and bingewatching impacted respondents attitudes towards purchasing OTT subscriptions. Moreover, factors like relaxation and voyeurism impacted respondents attitudes towards continuing OTT subscriptions. The research findings will be helpful for OTT companies to implement new distribution strategies with mobile operators to launch novel services like mobile-only packs and sachet pricing and thereby increase their user base. The study contributes significantly in understanding the viewership and subscription patterns of millennials. The study is exclusively an original contribution of the authors. 2024, Econjournals. All rights reserved.
Sinha D.; Sinha S.; Phutela N.; Grover P.
International Review of Management and Marketing , Vol-14, No. 6, pp. 119-130.
https://doi.org/10.32479/irmm.17110 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209155163&doi=10.32479%2firmm.17110&partnerID=40&md5=e7e02d1b1cd589a4dc192ff0804e91e3
Sinha D., Christ University, Bengaluru, India; Sinha S., Christ University, Bengaluru, India; Phutela N., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Noida, Pune, India; Grover P., Symbiosis Centre for Management Studies, Symbiosis International (Deemed University), Noida, Pune, India
Interacting Dark Energy and Its Implications for Unified Dark Sector
CMB; GCG; Interacting dark energy; K-essence; Scalar fields; ?-CDM
Alternative dark energy models were proposed to address the limitation of the standard concordance model. Though different phenomenological considerations of such models are widely studied, scenarios where they interact with each other remain unexplored. In this context, we study interacting dark energy scenarios (IDEs), incorporating alternative dark energy models. The three models that are considered in this study are time-varying ?, Generalized Chaplygin Gas (GCG), and K-essence. Each model includes an interaction rate ? to quantify energy density transfer between dark energy and matter. Among them, GCG coupled with an interaction term shows promising agreement with the observed TT power spectrum, particularly for ?<70, when ? falls within a specific range. The K-essence model (??0.1) is more sensitive to ? due to its non-canonical kinetic term, while GCG (??1.02) and the time-varying ? (??0.01) models are less sensitive, as they involve different parameterizations. We then derive a general condition when the non-canonical scalar field ? (with a kinetic term Xn) interacts with GCG. This has not been investigated in general form before. We find that current observational constraints on IDEs suggest a unified scalar field with a balanced regime, where it mimics quintessence behavior at n<1 and phantom behavior at n>1. We outline a strong need to consider alternative explanations and fewer parameter dependencies while addressing potential interactions in the dark sector. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
International Journal of Theoretical Physics, Vol-63, No. 10
Keshav MV P., Department of Physics and Electronics, CHRIST(Deemed to be University), Karnataka, Bangalore, 560029, India; Arun K., Department of Physics and Electronics, CHRIST(Deemed to be University), Karnataka, Bangalore, 560029, India
HMOSHSSA: a novel framework for solving simultaneous clustering and feature selection problems
Dimensionality reduction; Feature selection; Partitional clustering; Pattern recognition; Salp swarm algorithm; Spotted hyena optimizer
In real-life scenarios, information about the number of clusters is unknown. Due to this, clustering algorithms are unable to generate the valuable partitions. Beside this, the appropriate and optimal number of features is also required to produce the good quality clusters. The selection of optimal number of clusters and feature is a challenging task in the clustering. To resolve these problems, an automatic multi-objective-based clustering approach called HMOSHSSA is proposed in this paper. In HMOSHSSA, the spotted hyena and salp swarm algorithms are hybridized to obtain a better trade-off between these algorithms intensification and diversification capabilities. Two novel concepts for encoding and threshold setting are incorporated in the HMOSHSSA. The encoding scheme is used to choose the optimal number of clusters and features during the optimization process. The variance of dataset is used for setting the threshold values for both clusters and features. A novel fitness function is proposed to improve the optimization process. The suggested algorithms performance is evaluated using eight well-known real-world datasets. The statistical significance of HMOSHSSA is measured through t-tests. Results reveal that the proposed approach is able to detect the optimal number of clusters and features from a given dataset without user intervention. This approach is also deployed for solving microarray data analysis and image segmentation problems. HMOSHSSA outperformed the other considered algorithms in terms of performance measures. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Multimedia Tools and Applications, Vol-83, No. 35, pp. 82149-82175.
Kumar V., Department of Information Technology, Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Punjab, 147008, India; Kumari R., ICFAI Business School (IBS) Bangalore, Off-Campus Center of ICFAI Foundation for Higher Education (IFHE) University, Bangalore, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India
Effect of Coupled Microstructural Characteristics of Catalyst Layer on High Temperature: Proton Exchange Membrane Fuel Cell Performance
The widespread adoption of High Temperature-Proton Exchange Membrane Fuel Cells (HT-PEMFC) in commercial applications is limited by their performance and durability compared to conventional energy sources. A key factor affecting these cells is the sluggish oxygen reduction reaction (ORR) at the cathode catalyst layer (CL). Optimizing the structural parameters of the cathode CL can enhance cell performance and longevity. Current research on these parameters is mostly descriptive, lacking numerical evidence to quantify their impact. This study develops a three-dimensional, non-isothermal HT-PEMFC numerical model to investigate the sensitivities of coupled structural parameters of the cathode CL, including Pt loading, CL thickness, and Pt particle diameter, at three levels. The orthogonal/Taguchi approach quantitatively assesses the impact of these parameters. The study reveals that Pt loading significantly affects cell voltage and cathode overpotential, while Pt diameter influences the homogeneity of overpotential distribution. The dominant impact of a single parameter decreases at higher current densities, necessitating careful analysis of trade-offs between different structural characteristics to maximize performance. These findings offer valuable insights for future experimental studies to enhance cell performance through adjustments to cathode catalyst characteristics. 2024 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Varghese G.; Venkatesh Babu K.P.; Joseph T.V.; Chippar P.
Journal of the Electrochemical Society, Vol-171, No. 10
https://doi.org/10.1149/1945-7111/ad86ee https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208280205&doi=10.1149%2f1945-7111%2fad86ee&partnerID=40&md5=e67c80d11b36cbbcc6a5937d5b377e6d
Varghese G., CHRIST (Deemed to be University), Bengaluru, 560 029, India; Venkatesh Babu K.P., Applied Engineering and Computational Analysis Laboratory, St Joseph Engineering College (Affiliated to Visvesvaraya Technological University, Belagavi), Vamanjoor, Mangaluru, 575 028, India; Joseph T.V., CHRIST (Deemed to be University), Bengaluru, 560 029, India; Chippar P., Applied Engineering and Computational Analysis Laboratory, St Joseph Engineering College (Affiliated to Visvesvaraya Technological University, Belagavi), Vamanjoor, Mangaluru, 575 028, India
A ratiometric luminescence thermometer based on lanthanide encapsulated complexes
Lanthanide-containing complexes have been widely developed as ratiometric luminescence thermometers, which are non-invasive, contactless and accurate. The synthesis of these Ln complexes generally requires high temperatures, multiple steps and other harsh conditions. Moreover, bimetallic lanthanide complexes, which have been reported to be better thermometers, are even more challenging to synthesize. This complexity can be simplified by preparing a host-guest complex of lanthanides. In this work, Tb or both Tb and Eu are encapsulated in an MOF host, making them emissive. The ratio of Tb/Eu was also easily tuned by simply changing their ratio in the solution, resulting in a tunable emission. Accordingly, we were able to synthesise both the emissive Tb complex and Tb/Eu complexes at different ratios using a single host. The complexes were found to be suitable as ratiometric luminescent thermometers in the temperature range of 160-380 K, with reasonably good sensitivity and uncertainty. The thermometer's sensitivity and uncertainty were significantly improved using bimetallic Tb and Eu host-guest complexes. Calculations using the host and Eu emission ratio were found to provide better thermometer parameters than the commonly reported Tb and Eu emission ratio. Thus, using a single host, we were able to synthesise different lanthanide complexes that can sense temperature, and we improved the thermometer parameters by incorporating multiple lanthanides in a single host. This research will enable the scientific community to reexamine the applicability of unexplored host-guest lanthanide complexes. 2025 The Royal Society of Chemistry.
Sharma A.R.; Singh A.R.; Kongasseri A.A.; Garain S.; Mariella Babu A.; Lonibala R.; Laishram R.
Dalton Transactions, Vol-54, No. 4, pp. 1377-1383.
ISSN: 14779226; PubMed ID: 39523808; CODEN: DTARA
https://doi.org/10.1039/d4dt02639j https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209395173&doi=10.1039%2fd4dt02639j&partnerID=40&md5=df571d8c5c122ab8962d40221a761a6b
Sharma A.R., Department of Chemistry, Manipur University, Manipur, 795003, India; Singh A.R., Department of Chemistry, Manipur University, Manipur, 795003, India; Kongasseri A.A., New Chemistry Unit and School of Advanced Materials, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR) Jakkur, Bangalore, 560064, India; Garain S., University of Wzburg, Wzburg, Germany; Mariella Babu A., Christ University, Bengaluru, 560029, India; Lonibala R., Department of Chemistry, Manipur University, Manipur, 795003, India; Laishram R., Department of Chemistry, Manipur University, Manipur, 795003, India
Detection of a new sample of Galactic white dwarfs in the direction of the Small Magellanic Cloud
Binaries: general; Hertzsprung; Russell and C M diagrams; Techniques: photometric; Ultraviolet: stars; White dwarfs
Aims. In this study, we demonstrate the efficacy of the Ultraviolet Imaging Telescope (UVIT) in identifying and characterizing white dwarfs (WDs) within the Milky Way Galaxy. Methods. Leveraging the UVIT point-source catalogue towards the Small Magellanic Cloud and cross-matching it with Gaia DR3 data, we identified 43 single WDs (37 new detections), 13 new WD+main-sequence candidates, and 161 UV bright main-sequence stars by analysing their spectral energy distributions. Using the WD evolutionary models, we determined the masses, effective temperatures, and cooling ages of these identified WDs. Results. The masses of these WDs range from 0.2 to 1.3 M? and the effective temperatures (Teff) lie between 10 000 K to 15 000 K, with cooling ages spanning 0.1-2 Gyr. Notably, we detect WDs that are hotter than reported in the literature, which we attribute to the sensitivity of UVIT. Furthermore, we report the detection of 20 new extremely low-mass candidates from our analysis. Future spectroscopic studies of the extremely low-mass candidates will help us understand the formation scenarios of these exotic objects. Despite limitations in Gaia DR3 distance measurements for optically faint WDs, we provide a crude estimate of the WD space density within 1kpc of 1.3 10-3 pc-3, which is higher than previous estimates in the literature. Conclusions. Our results underscore the instrumental capabilities of UVIT and anticipate forthcoming UV missions such as INSIST for systematic WD discovery. Our method sets a precedent for future analyses in other UVIT fields to find more WDs and perform spectroscopic studies to verify their candidacy. The Authors 2024.
Sidharth A.V.; Shridharan B.; Mathew B.; Devaraj A.; Cysil T.B.; Stalin C.S.; Arun R.; Bhattacharyya S.; Kartha S.S.; Robin T.
Sidharth A.V., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Shridharan B., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai, 400005, India; Mathew B., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Devaraj A., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Cysil T.B., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Stalin C.S., Indian Institute of Astrophysics, Sarjapur Road, Koramangala, Bangalore, 560034, India; Arun R., Indian Institute of Astrophysics, Sarjapur Road, Koramangala, Bangalore, 560034, India; Bhattacharyya S., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Kartha S.S., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India; Robin T., Department of Physics and Electronics, CHRIST (Deemed to be University), Bangalore, 560029, India
Aspect Based Feature Extraction in Sentiment Analysis using Bi-GRU-LSTM Model
aspect sentiment extraction; dl based sentiment classification; NLP; Sentiment analysis; text processing
In Natural Language Processing (NLP), Sentiment Analysis (SA) is a fundamental process which predicts the sentiment expressed in sentences. In contrast to conventional sentiment analysis, Aspect-Based Sentiment Analysis (ABSA) employs a more nuanced approach to assess the sentiment of individual aspects or components within a document or sentence. Its objective is to identify the sentiment polarity, such as positive, neutral, or negative, associated with particular elements disclosed within a sentence. This research introduces a novel sentiment analysis technique that proves to be more efficient in sentiment analysis compared to current methods. The suggested sentiment analysis method undergoes three key phases: 1. Pre-processing 2. Extraction of aspect sentiment and 3. Sentiment analysis classification. The input text data undergoes pre-processing through the implementation of four typical text normalization techniques, which include stemming, stop word elimination, lemmatization, and tokenization. By employing these methods, the provided text data is prepared and fed into the aspect sentiment extraction phase. During the aspect sentiment extraction phase, features are obtained through a series of steps, including enhanced ATE (Aspect Term Extraction), assessment of word length, and determination of cosine similarity. By following these steps, the relevant features are extracted on the basis of aspects and sentiments involved in the text data. Further, a hybrid classification model is proposed to classify sentiments. In this work, two of the Deep Learning (DL) classifiers, Bi-directional Gated Recurrent Unit (Bi-GRU) and Long Short-Term memory (LSTM) are used in proposing a hybrid classification model which classifies the sentiments effectively and provides accurate final predicted results. Moreover, the performance of proposed sentiment analysis technique is analyzed experimentally to show its efficacy over other models. 2024 River Publishers.
Gupta S.; Singhal N.; Hundekari S.; Upreti K.; Gautam A.; Kumar P.; Verma R.
Journal of Mobile Multimedia, Vol-20, No. 4, pp. 935-960.
https://doi.org/10.13052/jmm1550-4646.2048 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206458908&doi=10.13052%2fjmm1550-4646.2048&partnerID=40&md5=3f3a6567420f45e0ab13abfc3d46cf17
Gupta S., Shobhit Institute of Engineering & Technology, Deemed to-be University, Meerut, 250110, India; Singhal N., Sir Chhotu Ram Institute of Engineering & Technology, Chaudhary Charan Singh University, Meerut, India; Hundekari S., School of Engineering and Technology, Pimpri Chinchwad University, Maval Talegaon, Pune, India; Upreti K., CHRIST University, Delhi NCR Campus, Ghaziabad, India; Gautam A., Manav Rachna International Institute of Research & Studies, Haryana, Faridabad, India; Kumar P., JSS Academy of Technical Education, Noida, India; Verma R., CHRIST University, Delhi NCR Campus, Ghaziabad, India
Progressive loss-aware fine-tuning stepwise learning with GAN augmentation for rice plant disease detection
Augmentation; Deep Learning; Plant Disease; Rice Disease; Transfer Learning
Modern technology like Artificial Intelligence (AI) must be used in the agricultural sectorif sustainable agricultural output is to be achieved. One of the most convenient strategies for resolving current and future issues is data-driven agriculture. For this, disease prediction is a major task for precise farming. For predictive analysis and precise agriculture monitoring systems, with the application of AI, Machine Learning (ML) and Deep Learning (DL) play vital roles in building a more robust system. In this work, we will design a DL-integrated rice disease prediction system to be implemented for precise farming. Improvisation of the developed model to detect rice plant diseases & pest attacks with a high level of precision. In this work, the Progressive Loss-Aware Fine-Tuning Stepwise Learning (PLAFTSL) model is proposed for disease detection. For step-wise learning fine-tuned ResNet50 model is used with the introduction of freezing and unfreezing layers. This reduces the training parameters and thus computational complexity. The introduction of the step-wise and progressive loss-aware layer will result in fast convergence and improved training efficiency during information exchange among layers respectively. Our proposed work uses a dataset from two sources. The result analysis is presented with an ablation study. Additionally, the baseline model, ResNet50, is used to display the outcomes of the ablation. The results demonstrate that the fine-tuned model results in better performance as compared to the transfer learning model. The Conditional Generative Adversarial Network (cGAN) augmentation is also added to the designed model which will improve detection effectiveness and can also manage the imbalance in input data. The model has achieved approx. 98% accuracy and outperforms better with comparative state-of-art models. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Upreti K.; Singh P.; Jain D.; Pandey A.K.; Gupta A.; Singh H.R.; Srivastava S.K.; Prasad J.S.
Multimedia Tools and Applications, Vol-83, No. 37, pp. 84565-84588.
Upreti K., CHRIST(Deemed to be University), Delhi NCR Campus, Delhi, India; Singh P., JSS Academy of Technical Education, Noida, India; Jain D., ABES Engineering College, Ghaziabad, India; Pandey A.K., ABES Engineering College, Ghaziabad, India; Gupta A., Department of CSE (AI & amp; ML), PIET Engineering College Samalkha, Haryana, India; Singh H.R., Greater Noida Institute of Technology, Greater Noida, India; Srivastava S.K., Department of Applied Computational Science & amp; Engineering, GL BAJAJ Institute of Technology & amp; Management, Greater Noida, India; Prasad J.S., Greater Noida Institute of Technology, Greater Noida, India
Impact of Learnability Quotient on Employability of Students: Mediating Role of Spiritual Intelligence
Employability; India; Learnability Quotient; Spiritual Intelligence
This study investigates the impact of Learnability Quotient (LQ) on Employability, with a particular focus on the mediating role of Spiritual Intelligence (SI). Conducted in southern India with a cross-sectional design, the research utilizes primary data collected from educated adults through surveys. The study aims to elucidate cause-and-effect relationships between LQ and Employability and to test hypotheses regarding these variables. The findings reveal that Learnability Quotient and Employability significantly influence each other, with both being affected by age. Education also plays a crucial role in determining employability, while Spiritual Intelligence and Learnability Quotient are less influenced by educational level. The type of institution does not significantly affect these factors, although the location of the institution does impact Spiritual Intelligence and Employability. Correlation analysis shows that higher Spiritual Intelligence correlates moderately with both Learnability Quotient and Employability, while Learnability Quotient has a strong positive association with Employability. Mediation analysis uncovers a complex dynamic where, despite the positive direct effect of Learnability Quotient on Employability, its impact is diminished when mediated through Spiritual Intelligence, as indicated by a negative Variance Accounted For (VAF). Learnability Quotient is crucial for enhancing employability, while Spiritual Intelligence has a nuanced, potentially counterproductive mediation role. Further research is necessary to refine strategies for improving employability through these variables. 2024, Iquz Galaxy Publisher. All rights reserved.
Varghese S.; Ravikumar T.; Mathew J.; Sathiyaseelan B.
International Research Journal of Multidisciplinary Scope, Vol-5, No. 4, pp. 1292-1302.
Varghese S., School of Business and Management, CHRIST (Deemed University), Bangalore, India; Ravikumar T., School of Business and Management, CHRIST (Deemed University), Bangalore, India; Mathew J., School of Business and Management, CHRIST (Deemed University), Bangalore, India; Sathiyaseelan B., School of Business and Management, CHRIST (Deemed University), Bangalore, India
NSS-ML: a Novel spectrum sensing framework using machine learning for cognitive radio IoT networks
5G communications; BAT algorithm; Cognitive radio; Spectrum sensing
A key component of cognitive radio systems is spectrum sensing, which reduces coexistence problems and maximises spectrum efficiency. However, the introduction of multiple situations with distinct characteristics brought about by 5G communication presents problems for spectrum sensing to support a wide range of applications with high performance and flexible implementation. Inspired by these difficulties, a new method with a multi-layer extreme learning machine optimised for bats is presented in this study. This technique makes use of a variety of input vectors, such as channel ID, energy, distance, and received signal intensity, to enhance user categorization and sensing capabilities. Moreover, we compare the proposed method with the state-of-the-art spectrum sensing approaches in order to evaluate its effectiveness in 5G situations, especially in healthcare applications. Evaluation metrics including channel detection probability, sensitivity, and selectivity are carefully examined. The findings unequivocally prove the suggested spectrum sensing approachs superiority over current methods and highlight its potential for smooth incorporation into a variety of 5G applications. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.
Marriwala N.K.; Shukla V.K.; Shanbhog M.; Panda S.; Kaushik R.; Rathore D.
International Journal of Information Technology (Singapore), Vol-16, No. 7, pp. 4599-4604.
Springer Science and Business Media B.V.
Marriwala N.K., Dept. of Electronics and Communication Engineering, University Institute of Engineering and Technology, Kurukshetra University, Haryana, Kurukshetra, India; Shukla V.K., Information Technology Head of Academics-School of Engineering Architecture Interior Design, Amity University, Dubai, United Arab Emirates; Shanbhog M., School of Sciences, Christ (deemed to be university), Delhi NCR Campus, Uttar Pradesh, Ghaziabad, India; Panda S., Dept. of Electrical, Electronics and Communication Engineering, GITAM School of Technology, Bengaluru Campus, Karnataka, Doddaballapura, India; Kaushik R., Dept. of Electronics and Communication Engineering, University Institute of Engineering and Technology, Kurukshetra University, Haryana, Kurukshetra, India; Rathore D., Dept. of Electronics and Communication Engineering, Guru Ghasidas Vishwavidyalaya, Bilaspur, India
Emotional intelligence, job satisfaction and psychological well-being among nurses in a tertiary care hospital
Emotional Intelligence; Job Satisfaction; Nurse; Psychological well-being
Background: Emotional intelligence helps in preservation of mental health because of their effective emotional regulation skills. Objectives: We aimed to evaluate the impact of emotional intelligence on nurses job satisfaction and psychological well-being. Methods: This cross-sectional study was conducted in a tertiary hospital and included 120 nurses. Wong and Law Emotional Intelligence Scale, Psychological General Well-being scale and Job Satisfaction Survey questionnaires were used. Results: The study showed a low positive correlation between emotional intelligence and psychological wellbeing (r=0.313) and a low correlation between emotional intelligence and job satisfaction (r= 0.122). The emotional intelligence was significantly correlated to their psychological well-being (9.8%). Conclusion: Nurses with higher emotional intelligence experience greater psychological well-being. We did not find a link between emotional intelligence and job satisfaction. Implementing interventions to enhance emotional intelligence in nurses is crucial for improving psychological well-being and reducing burnout risk. The Author(s). 2024.
Malayil C.; Krishnan G.; Sharma T.; Shetty S.B.; Pai K.; Gangadhara V.K.
Indian Journal of Community Health, Vol-36, No. 5, pp. 737-740.
Indian Association of Preventive and Social Medicine
https://doi.org/10.47203/IJCH.2024.v36i05.017 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211216593&doi=10.47203%2fIJCH.2024.v36i05.017&partnerID=40&md5=fe79328ca4a700220dcc37d85465319f
Malayil C., Malabar Cancer Center, Thalassery, Kannur, Kerala, Kodiyeri, India; Krishnan G., Department of Psychology, Christ (Deemed to be University), Karnataka, Bangalore, India; Sharma T., Department of Psychiatry, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India; Shetty S.B., Department of Psychiatry, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India; Pai K., Department of Psychiatry, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India; Gangadhara V.K., Department of Psychiatry, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India
Engineering the functionality of porous organic polymers (POPs) for metal/cocatalyst-free CO2 fixation at atmospheric conditions
Atmospheric pressure; CO2 utilization; Cyclic carbonates; Metal/Co-catalyst-free fixation; Porous Organic Polymer (POP)
Carbon dioxide (CO2) utilization as C1 feedstock under metal/co-catalyst-free conditions facilitates the development of eco-friendly routes for mitigating atmospheric CO2 concentration and producing value-added compounds. In this regard, herein, we designed a bifunctional porous organic polymer (POP-1) by incorporating acidic (-CONH) and CO2-philic (-NH/N) sites by judicious choice of organic precursors. Indeed, POP-1 exhibits high heat of interaction for CO2 (40.2 kJ/mol) and excellent catalytic performance for transforming carbon dioxide to cyclic carbonates, a high-value commodity chemical with high selectivity and yield under metal/cocatalyst/solvent-free atmospheric pressure conditions. Interestingly, an analogous polymer (POP-2) that lacks basic (-NH/N) sites showed lower CO2 interaction energy (31.6 kJ/mol) and catalytic activity than that of POP-1. The theoretical studies further supported the superior catalytic activity of POP-1 in the absence of Lewis acidic metal and cocatalyst. Notably, POP-1 showed excellent reusability with retention of catalytic performance for multiple cycles of usage. Overall, this work presents a novel approach to metal/cocatalyst/solvent-free utilization of CO2 under eco-friendly atmospheric pressure conditions. 2024 Elsevier Ltd
Das R.; Kishan R.; Muthukumar D.; Pillai R.S.; Nagaraja C.M.
Journal of Environmental Chemical Engineering, Vol-12, No. 5
https://doi.org/10.1016/j.jece.2024.113777 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201624684&doi=10.1016%2fj.jece.2024.113777&partnerID=40&md5=51263e616c7d6c0e364261a2f6a335dd
Das R., Department of Chemistry, Indian Institute of Technology Ropar, Punjab, Rupnagar, 140001, India; Kishan R., Department of Chemistry, Indian Institute of Technology Ropar, Punjab, Rupnagar, 140001, India; Muthukumar D., Department of Chemistry, Christ University, Bengaluru, 560 022, India; Pillai R.S., Department of Chemistry, Christ University, Bengaluru, 560 022, India; Nagaraja C.M., Department of Chemistry, Indian Institute of Technology Ropar, Punjab, Rupnagar, 140001, India
Synthesis of ZnO and NiO nano ceramics composite high-performance supercapacitor and its catalytic capabilities
Energy storage; Methane combustion; Nio/ZnO composites; Super capacitor
NiO and ZnO mixed nanocomposites were manufactured using the solution combustion process. As-prepared samples were analyzed using XRD. The XRD shows an average crystallite size of 3540 nm. The elemental composition determined by EDS indicates a nearly equal proportion of Ni and Zn, with an atomic ratio of Ni/Zn = 0.96. The specific capacitances of NiO is 295.5 Fg-1, ZnO is 117.3 Fg-1 and ZnO/NiO nanocomposites is 561.75 Fg-1 which are more than NiO and ZnO alone. This study shows that constructing binary oxide nanocomposites is an approach for developing high-performance supercapacitor electrode materials. Experimental observations on catalytic activity revealed that NiO/ZnO increased catalytic activity. Furthermore, adding NiO to ZnO in the composite increased the overall amount of oxygen vacancies in the samples. Our research lays the door for a simple, inexpensive, nontoxic, and quick technique to synthesize binary transition metal oxide-based electrode materials for high-performance supercapacitors. 2024 Elsevier Ltd and Techna Group S.r.l.
Angadi V J.; Molahalli V.; Soman G.; Hegde G.; Wang S.; Roy N.; Joo S.W.; Pattar V.; Shaikh S.F.; Prakash C.; Kumar A.; Ubaidullah M.; Zhang M.
Ceramics International, Vol-50, No. 20, pp. 39732-39738.
https://doi.org/10.1016/j.ceramint.2024.07.352 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199959723&doi=10.1016%2fj.ceramint.2024.07.352&partnerID=40&md5=e0dfb2198c4df8a762356d49c1ff2f8b
Angadi V J., Department of Physics K.L.E's P.C.Jabin Science College, Hubli-31, Karnataka, India; Molahalli V., Department of Chemistry, Christ University, Hosur Road, Bengaluru, 560029, India; Soman G., Department of Chemistry, Christ University, Hosur Road, Bengaluru, 560029, India; Hegde G., Department of Chemistry, Christ University, Hosur Road, Bengaluru, 560029, India; Wang S., School of Electronic and Information Engineering, Chongqing Three Gorges University, Wanzhou, Chongqing, 404000, China; Roy N., Department of Physics, Yeungnam University, Gyeongsan, 38541, South Korea; Joo S.W., School of Mechanical and IT Engineering, Yeungnam University, Gyeongsan, 38541, South Korea; Pattar V., Education Technology Unit, JNCASR, Bengaluru, India; Shaikh S.F., Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Prakash C., University Centre for Research & Development, Chandigarh University, Punjab, Mohali, 140413, India; Kumar A., Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, 174103, India; Ubaidullah M., Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Zhang M., School of Electronic Engineering, Yangzhou Polytechnic College, Hanjiang, YangZhou, 225009, China
Metaheuristic Machine Learning Algorithms for Liver Disease Prediction
Artificial Bee Colony (ABC) Algorithm; Decision Tree; Machine Learning; Random Forest
In machine learning, optimizing solutions is critical for improving performance. This study explores the use of metaheuristic algorithms to enhance key processes such as hyperparameter tuning, feature selection, and model optimization. Specifically, we integrate the Artificial Bee Colony (ABC) algorithm with Random Forest and Decision Tree models to improve the accuracy and efficiency of disease prediction. Machine learning has the potential to uncover complex patterns in medical data, offering transformative capabilities in disease diagnosis. However, selecting the optimal algorithm for model optimization presents a significant challenge. In this work, we employ Random Forest, Decision Tree models, and the ABC algorithmbased on the foraging behaviours of honeybeesto predict liver disease using a dataset from Indian medical records. Our experiments demonstrate that the Random Forest model achieves an accuracy of 85.12%, the Decision Tree model 76.89%, and the ABC algorithm 80.45%. These findings underscore the promise of metaheuristic approaches in machine learning, with the ABC algorithm proving to be a valuable tool in improving predictive accuracy. In conclusion, the integration of machine learning models with metaheuristic techniques, such as the ABC algorithm, represents a significant advancement in disease prediction, driving progress in data-driven healthcare. 2024, Iquz Galaxy Publisher. All rights reserved.
Gupta D.; Rani B.K.; Verma I.; Ahamed S.K.; Arul Mary Rexy V.; Rajkumar N.; Vidhya R.G.
International Research Journal of Multidisciplinary Scope, Vol-5, No. 4, pp. 651-660.
https://doi.org/10.47857/irjms.2024.v05i04.01204 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210428409&doi=10.47857%2firjms.2024.v05i04.01204&partnerID=40&md5=53670bbcbb66dabffd66c89963fed8fd
Gupta D., Department of CSE, Manipal Institute of Technology Bengaluru, Bengaluru, India; Rani B.K., Department of Information Technology, Vasavi College of Engineering, Hyderabad, India; Verma I., School of Sciences, Christ (deemed to be) University, Delhi-NCR, Ghaziabad, India; Ahamed S.K., Department of CSE, Methodist College of Engineering and Technology, Hyderabad, India; Arul Mary Rexy V., Department of Commerce General, Saveetha College of Liberal Arts and Sciences, Chennai, India; Rajkumar N., Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology, Avadi, Tamil Nadu, India; Vidhya R.G., Department of ECE, HKBK College of Engineering, Bangalore, India
Zinc oxide/tin oxide nanoflower-based asymmetric supercapacitors for enhanced energy storage devices
Research on energy storage devices has focused on improving asymmetric supercapacitors (ASCs) by utilizing two different electrode materials. In this work, we have successfully prepared a unique material, ZnO/SnO2 nanoflower, via the hydrothermal method. Graphene oxide (GO) was synthesized by applying the modified Hummers' technique. The ZnO/SnO2 nanoflower was deposited on a polypyrrole (PPY) nanotube/graphene oxide composite (ZS/GP) in two steps: in situ chemical polymerization, followed by a hydrothermal method. Electrochemical properties of the prepared material nanocomposite were analyzed by applying cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS) techniques. An asymmetric supercapacitor (ASC) was constructed using ZS/GP nanocomposite as the positive electrode and Caesalpinia pod-based carbonaceous material as the negative electrode material, and its performance was investigated. As a result, the fabricated ASCs were found to have an excellent specific capacitance of 165.88 F g?1 at 1.4 V, with an energy density of 5.12 W h kg?1 and a power density of 2672 W kg?1. The prepared nanocomposite material for the ASC showed a cycle stability of 17k cycles at a current density of 5 A g?1. This study revealed that the electrode material ZS/GP nanocomposite is highly suitable for supercapacitor applications. The ASC device's extended cycle life experiments for 17k cycles produced a coulombic efficiency of 97% and a capacitance retention of 73%, demonstrating the promising potential of the electrode materials for greener as well as efficient energy storage applications while converting abundant bio waste into effective energy. 2024 The Royal Society of Chemistry.
Molahalli V.; Soman G.; Bhat V.S.; Shetty A.; Alodhayb A.; Hegde G.
https://doi.org/10.1039/d4ra05340k https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207328563&doi=10.1039%2fd4ra05340k&partnerID=40&md5=dbf5dd502b49fb108ea2a15db5d2f279
Molahalli V., Department of Physics, B.M.S. College of Engineering, Bull Temple Road, Bengaluru, 560019, India; Soman G., Department of Chemistry, Christ University, Hosur Road, Bangalore, 560029, India; Bhat V.S., Department of Materials Science, Mangalore University, Mangalagangotri, Karnataka, Mangaluru, 574199, India; Shetty A., Department of Chemistry, Christ University, Hosur Road, Bangalore, 560029, India; Alodhayb A., Department of Physics and Astronomy, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia; Hegde G., Department of Chemistry, Christ University, Hosur Road, Bangalore, 560029, India, Centre for Advanced Research and Development (CARD), Christ University, Hosur Road, Bangalore, 560029, India
Electrochemical investigations of chitosan/ZrO2-Bi2O3 composite for advanced energy and environmental applications
Chitosan/ZrO2-Bi2O3; Corrosion inhibition; Hydrogen evolution reaction; Polymer composites; Supercapacitors
Energy needs are on the rise, and the need for effective corrosion resistance measures are also vital to meet the requirements prevailing in society. A multifunctional Chitosan/ZrO2-Bi2O3 composite is synthesized, keeping electrochemical analysis of energy and environmental applications in mind. Various physicochemical methods confirm the impact of integrating ZrO2-Bi2O3 into chitosan, resulting in improved efficacy across applications. The electrocatalytic supercapacitance, hydrogen evolution reaction, and corrosion inhibition studies are carried out to evaluate the efficiency of the synthesized composite. The composite shows a specific capacitance of 636.5 F/g, ensuring the effective utility for supercapacitance applications. The lower overpotential of 135.2 mV is shown by the composite in the electrocatalytic hydrogen evolution reaction. The synthesized composite also shows 96.2 % efficacy in corrosion inhibition studies. The studies conducted demonstrate the increased effectiveness of chitosan when combined with bimetal oxide. The chitosan composite is therefore a competent catalyst for energy and environmental applications. 2024 Elsevier Ltd
Varghese A.; Sunaja Devi K.R.; Pinheiro D.; Jomy J.
https://doi.org/10.1016/j.jece.2024.113824 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201767450&doi=10.1016%2fj.jece.2024.113824&partnerID=40&md5=7163e7cbb30b088e211a41f3f61c5a80
Varghese A., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Sunaja Devi K.R., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Pinheiro D., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Jomy J., Department of Chemistry, Manipal Institute of Technology, Manipal Academy of Higher Education, Karnataka, Manipal, 576104, India
Unveiling the Indian REIT narrative-qualitative insights intoretail investors perspectives
Challenges; India; Perspective; Qualitative study; REITs; Retail investors
Purpose: The present study delves into the causes of relatively lower retail participation in the Indian REIT market. Specifically, it investigates investors' attitudes and perceptions towards REITs as a unique asset class. This paper provides a comprehensive understanding of the perception and factors influencing Indian retail investors' reluctance to participate in the REIT market. Design/methodology/approach: Qualitative research was conducted through semi-structured interviews to gather insights from non-investors in REITs. The data were transcribed and analyzed using content analysis techniques. Finally, coding techniques were used to identify broad study themes. Findings: According to the study results, many retail investors are unfamiliar with REITs. Even among those knowledgeable about REITs and with a favorable view, it is not commonly seen as a feasible investment option due to its early stage, unattractive returns and limited number of REITs. Practical implications: Developed countries have established REIT markets, while it is still in its infancy in developing countries such as India. Financial advisors, fund houses and the media should focus on educating investors to increase awareness. Originality/value: The study is the first qualitative investigation into the perception of retail investors to understand the reasons for lower retail engagement in the Indian REIT market. 2024, Emerald Publishing Limited.
Journal of Property Investment and Finance, Vol-42, No. 6, pp. 539-553.
https://doi.org/10.1108/JPIF-01-2024-0003 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192820721&doi=10.1108%2fJPIF-01-2024-0003&partnerID=40&md5=afddea9c5122d4961ffab04abfe40433
Swathi G.R., Department of Commerce, Christ (Deemed to be University), Bengaluru, India; Uma V.R., Department of Commerce, Christ (Deemed to be University), Bengaluru, India
Development of classical swine fever virus E2-protein based indirect ELISA for detection of antibodies against the virus in pigs
Classical swine fever (CSF) is an economically important and highly contagious disease of pigs caused by CSF virus, genus Pestivirus. Serological diagnosis of the disease is highly valuable for surveillance and thereby containment of spread of the disease. In this study, we have demonstrated the development of CSFV envelope glycoprotein E2-based indirect ELISA (E2-iELISA) for the detection of CSFV specific antibodies. The full-length E2 protein was expressed in E. coli and the purified protein was used as a coating antigen in indirect ELISA for detecting CSFV specific antibodies in pigs. A panel of 506 pig sera samples was used to validate the ELISA and the results were highly comparable to the results obtained with the commercial antibody detection kit (PrioCHECK CSFV Ab kit). The in-house E2-iELISA demonstrated high diagnostic sensitivity (95.4%) and specificity (95.5%), highlighting its potential application for sero-surveillance or monitoring of the disease in the swine population. The Author(s), under exclusive licence to Springer Nature B.V. 2024.
Gopinath S.; Hosamani M.; Joseph B.V.; Patil S.S.
Veterinary Research Communications, Vol-48, No. 5, pp. 3121-3129.
ISSN: 1657380; PubMed ID: 39088127; CODEN: VRCOD
Gopinath S., CHRIST UNIVERSITY, Karnataka, Bengaluru, 560029, India; Hosamani M., ICAR- Indian Veterinary Research Institute, Karnataka, Bengaluru, 560024, India; Joseph B.V., CHRIST UNIVERSITY, Karnataka, Bengaluru, 560029, India; Patil S.S., ICAR- National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Karnataka, Bengaluru, 560064, India