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Antecedents of brand love leading to purchase intention towards refurbished video game consoles
This paper examines different constructs that influence purchase intention of refurbished video game consoles to assess its multi-factorial association with brand love. The data was collected from video game console cafes in the cities of Bangalore and Pune, India. The findings demonstrate that adoption determinants and social influence have a positive influence on brand love, while notably, environmental involvement has a positive influence on an individuals purchase intention. Brand love would not singularly influence positive purchase intention in the context of refurbished video game consoles. The paper clarifies that brand love alone cannot influence the purchasing decision of an individual in the context of refurbished video game consoles, the companies selling or remanufacturing these products can benefit by advertising these products as being environmentally involved. This is the first paper that examines the effects of brand love and purchase intentions in the context of refurbished video game consoles. Copyright 2023 Inderscience Enterprises Ltd. -
Bardic Destinies: A Comparative Study of European Poetic and Indian Kavya-Itihasa Tradition
This volume critically explores the cultural significance and fate of the literary in the European and the Indian traditions as it traces the history of the reception of works that have had a deep hold on the lives and sensibilities of people across time and cultures. The book grapples with three major concepts in the humanitiesthe literary, the philosophical/theological and the historical. It looks at Homers reception by Plato; Virgils reception by Christianity; the many responses that The Mahabharata has received over centuries and across cultures in India; and the reception of Kumaravyasas Kumaravyasabharata, among other works, and analyses the understanding of truth, time and history that influence the reading of these works in different times and cultural contexts. Part of the Critical Humanities across Cultures series, this book will be useful for scholars and researchers of philosophy, literature, history, comparative literature, cultural studies and post-colonial studies. 2024 Krishna Kanchith R. -
A study on "student preferece towards the use of Edmodo as a learning platfrom to create responsible learning environment" /
Procedia Social and Behavioral Sciences, Vol.144, pp.142-148, ISSN No: 1877-0428. -
Effects of bio-flocculated algae on the growth, digestive enzyme activity and microflora of freshwater fish Catla catla (Hamilton 1922)
In numerous ways, diets incorporating probiotics are beneficial to host animals. This study was conducted to evaluate the influence of bio-flocculated freshwater algae Chlorella vulgaris on the freshwater fish Catla catla. For the process of flocculating algae, probiotics Lactobacillus acidophilus (10307 MTCC) and Bacillus subtilis (MTCC 441) were used. The experimental fish were fed with Artemia franciscana enriched with flocculated algae for 60days. A control group was fed with unenriched A. franciscana. After the experimental period, there was a significant decrease in anaerobic bacteria and a significant colonization of candidate probiotics in guts of fish fed with flocculated algae-enriched Artemia. This treatment group also had a better growth performance with a higher average body length and weight (8.70.3cm, 5.830.9g) and survival % (981.02). High protease (7.8mg/protein?1) and lipase (2.56 mg/protein?1) activity were also found in the enriched A. franciscana-fed fish group. Comparatively, higher protein, lipid and PUFA/HUFA contents were also reported in this treatment group. The study found that flocculated algae-enriched A. franciscana has a positive impact on gut microflora, growth parameters and survival as compared to the unenriched group, and hence, the flocculated algae serve a dual purpose in rearing of C. catla. This study supports the inference that a bio-flocculated algae-incorporated diet is a preferable method for larval rearing aquaculture. 2020 John Wiley & Sons Ltd -
Detecting Fake Information Dissemination using Leveraging Machine Learning and DRIMUX with B-LSTM
Information integrity and public confidence are seriously threatened by the rapid expansion of fake news and misinformation that has resulted from the online broadcast of information. This work focuses on the detection of fraudulent information propagation utilizing machine learning techniques and the Digital Reputation and Influence Measurement Unit (DRIMUX) in order to address this problem. The use of Bidirectional Long Short-Term Memory (B-LSTM) networks into the detection process is something we really advocate. B-LSTM enables the capture of contextual dependencies from both past and future time steps, enhancing the understanding of sequential data. Additionally, DRIMUX provides reputation and influence measurements to assess the credibility of information sources. Experimental analyses on various datasets reveal the promising performance of the suggested methodology, highlighting its potential in preventing the spread of false information and protecting the veracity of digital information. 2024, Ismail Saritas. All rights reserved. -
Adoption of enterprise risk management erm practices in the zimbabwean banking sector
Corporate failures that occurred in the mid-1990s as well as the global financial crisis that unfolded in the US in 2007 and subsequent banking crises in many countries underscored the need for banking institutions to develop and implement robust risk management systems and controls to prevent the occurrences of such crises. Enterprise risk management (ERM) has emerged as the best practice approach that provided banks with means for mitigating and controlling risks giving rise to such financial crises. Attempts have been made to find out the factors driving the implementation of ERM and the majority of these studies had conflicting newlineconclusions on the effect of some of these factors. Further, weaknesses were noted in variables used by researchers as proxies for ERM adoption. It was noted that several studies used the appointment of a chief risk officer as a variable representing ERM adoption while a number of other researchers focused on surveys or renowned frameworks such as COSO to ascertain the extent of adoption of ERM. These approaches however, had shortcomings. This study therefore sought to address some of the above gaps in literature. The purpose of this study is to determine the degree of adoption of ERM newlinepractices as well to examine factors (adequacy of risk governance structure, newlinequality of organizational culture, intensity of regulatory environment and size of the bank) influencing the adoption and implementation of ERM by banks in Zimbabwe. A mixed method approach was utilized in this study. The population of the study comprised of 18 commercial banks which have been operating in Zimbabwe since the adoption of the multi-currency system in 2009. Respondents for the study were selected using the purposive sampling approach. This was to ensure the respondents had the right experience and expertise to answer questions on enterprise risk management practices newlinewithin their respective banks. -
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Economic and Urban Dynamics: Investigating Socioeconomic Status and Urban Density as Moderators of Mobile Wallet Adoption in Smart Cities
This research paper examines the complex correlation between socioeconomic factors, urban density, and the acceptance of mobile wallet technology in smart cities. The study investigates how socioeconomic status and urban density influence the adoption of mobile wallets. Smart cities have experienced a significant increase in the adoption of mobile payment solutions such as Apple Pay, and Google Pay, noted for their technological innovation and ability to enhance living standards. These digital payment platforms provide ease, security, and efficiency, revolutionizing how individuals engage in financial transactions and navigate urban environments. The study examines the many aspects that impact this phenomenon, focusing on the significance of comprehending how socioeconomic status and urban density influence the acceptance of mobile wallets. The study utilizes a meticulous research technique, which involves evaluating the reliability and validity of constructs, analyzing Heterotrait-Monotrait (HTMT) ratios, conducting tests for discriminant validity, and doing variance inflation factor (VIF) analysis. These measures are taken to ensure the strength and reliability of the report's conclusions. The research's importance is further supported by model fit statistics and hypothesis testing conducted through bootstrapping. The results emphasize that the inclusion of mobile wallet functions, the legal framework, and the development of smart city infrastructure have a substantial influence on the acceptance of mobile wallets. However, the impact of urban density on mobile wallet adoption is more intricate and multifaceted. This study provides significant insights into the dynamic field of technology uptake in urban regions, with implications for politicians, entrepreneurs, and urban planners seeking to promote financial inclusion and technological integration in smart cities. 2024 IEEE. -
Markov based genetic algorithm (M-GA): To mine frequent sub components from molecular structures
Processing the molecular compounds to identify the internal chemical structure is a challenging task in bio-chemical research. Popular approaches, mine the frequent subcomponents from the molecules with chemical and biological properties represented in the form of feature vector histogram. Though this helps to identify the absence or presence of mined feature, calculating the frequency of every frequent substructure involves sub graph isomorphism test which is an NP-Complete process. To overcome the above mentioned bottleneck we proposed Markov based Genetic algorithm (M-GA) in which the chemical descriptors were considered from two-dimensional representations of molecules that classify chemical compounds using mining significant substructure and generates the binary vector that generate pure active classes, singleton reactors, descriptor sets. This method scales down the process of mining substructures that are statistically significant from huge chemical databases. The results shows that the performance of proposed algorithm is improved compared to the existing algorithms. 2020, Research Trend. All rights reserved. -
An Novel Cutting Edge ANN Machine Learning Algorithm for Sepsis Early Prediction and Diagnosis
Early detection and diagnosis of sepsis can significantly improve patient outcomes, but current diagnostic methods are limited. The problem addressed in this paper is the early detection and diagnosis of sepsis using machine learning algorithms. Sepsis is a life-threatening condition that can rapidly progress and cause organ failure, leading to increased mortality rates. Early detection and treatment of sepsis are critical for improving patient outcomes and reducing healthcare costs. However, sepsis can be challenging to diagnose, and existing methods have limitations in terms of accuracy and timeliness This research proposes a new cutting-edge Optimized Artificial Neural Network machine learning algorithm for sepsis early prediction and diagnosis. The proposed algorithm combines different data sources, including patient vital signs, laboratory results, and clinical notes, to predict the likelihood of sepsis development. The algorithm was evaluated on a large dataset of patient records and achieved promising results in terms of accuracy, Precision and Recall. The proposed algorithm can potentially serve as a valuable tool for clinicians in the early detection and diagnosis of sepsis, leading to better patient outcomes. 2023 American Institute of Physics Inc.. All rights reserved. -
AI-enabled risk identification and traffic prediction in vehicular Ad hoc Networks
The proposed research presents a two-fold approach for advancing Vehicular Ad-Hoc Networks (VANETs). Firstly, it introduces a Residual Convolutional Neural Network (RCNN) architecture to extract real-time traffic data features, enabling accurate traffic flow prediction and hazard identification. The RCNN model, trained and tested on real- world data, outperforms existing models in both accuracy and efficiency, promising improved road safety and traffic management within VANETs. Secondly, the study introduces a Genetic Algorithm-enhanced Convolutional Neural Network (GACNN) routing algorithm, challenging traditional VANET routing methods with metaheuristic techniques. Experiments in various VANET network scenarios confirm GACNN's superior performance over existing routing protocols, marking a significant step toward more efficient and adaptive VANET traffic management. 2024 Author(s). -
Mitigating post-harvest losses through IoT-based machine learning algorithms in smart farming
This research paper explores the transformative potential of Internet of Things (IoT) technology in mitigating the longstanding issue of post-harvest losses within the agriculture sector. These losses, which encompass both quantitative and qualitative deterioration of food commodities from harvest to consumption, have posed persistent challenges, resulting in economic losses and food wastage. By delving into the current landscape of post-harvest losses and the application of IoT technology, the paper offers valuable insights into how IoT can be harnessed to reduce these losses effectively. It not only highlights the benefits and existing IoT solutions but also addresses the inherent challenges, providing recommendations for their resolution. Moreover, the research introduces a machine learning-based model, specifically Random Forest ML, to identify and prevent losses in tandem with IoT devices, empowering farmers with timely alert messages for informed decision-making, thus fostering a more sustainable and efficient agricultural ecosystem. 2024 Author(s). -
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Experimental Investigation of Salt Hydrate Phase-Change Material (Shape-Stabilized) Applied to a Solar Collector
A complex element of water heater by solar power involves the requirements of storage tank, which not only occupies considerable space but also adds com-plexity to the plumbing and installation procedures; this research marks the initial endeavor to practically utilize shape-stabilized (SS) phase-change material (PCM) within a tank-less, evacuated tube with direct absorption (ET-Direct Absorption) solar collector. The primary objective was to tackle challenge of storage of the solar power. A PCM (salt hydrate) was proposed, with different component concentrations explored to determine the most effective mixture. Once the optimal compound was identified, it underwent rigorous testing over numerous cycles to ensure its sustainable its storing capabilities. Additionally, the planetary system was charged in dormancy mode (without flow of water) and subsequently discharged at the rate of flows of 15, 25, and 35 liters per hour (LPH). Results indicated a note-worthy improvement in efficiency of the heat system in the stasis mode, which increases from 62 to 80% with the utilization of this heat storing cum collecting unit. Moreover, it was observed that transitioning from a rate of flow of 1525 LPH had minimal impact on the collec-tors heat gain, but using a rate of flow of 35 LPH sig-nificantly reduced efficiency of discharge. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Future perspectives on new innovative technologies comparison against hybrid renewable energy systems
The increase in the dispatchable amount of renewable energy and rural access to the point is proposed. The fuel is used to generate power and electrical energy for the machine. This causes the electricity to manage the single connection point to analyze the hybrid generations. Improving this hybrid generator of renewable power resources can be enabled for the analysis. Photovoltaic power sources have been introduced for converting the power loads and the dumps. The vehicle energy power management technique and the renewable energy system have been used for the analysis. This study shows how vehicle and renewable energy management can help develop geothermal against hydrothermal vents. Hydropower and vehicles can enable bioethanol for vehicle biodiesel. This study allows for the analysis of hydrothermal and biodiesel. In this study, the power of the energy enables the hybrid system, and the combination of the power generator to access the vehicle is proposed. 2023 -
Amorphous Ru-Pi nanoclusters decorated on PEDOT modified carbon fibre paper as a highly efficient electrocatalyst for oxygen evolution reaction
Amorphous Ru-Pi nanoclusters deposited on PEDOT modified carbon fibre paper electrode have been investigated as a potential oxygen evolution electrocatalyst. CFP/PEDOT/Ru-Pi electrode was prepared by electrodeposition of Ru-Pi nanoclusters on PEDOT decorated CFP using cyclic voltammetry (CV). Field emission scanning electron microscopy with energy-dispersive X-ray spectroscopy (FESEM-EDS), attenuated total reflection with Fourier-transform infrared spectroscopy (ATR-FTIR) and X-ray diffraction (XRD) were used for physicochemical characterization. Linear sweep voltammetric (LSV) studies corroborated that CFP/PEDOT/Ru-Pi has exhibited higher oxidation peak current when compared to other modified electrodes. CFP/PEDOT/Ru-Pi electrode has displayed better catalytic activity towards oxygen evolution reaction at low onset and over potential. The modified electrode has also offered better stability towards the oxidation reaction in phosphate buffer solution (PBS) and the working stability of these electrodes were determined using LSV and CV. 2021 Elsevier B.V. -
Surface adsorption and anticorrosive behavior of benzimidazolium inhibitor in acid medium for carbon steel corrosion
Corrosion inhibition property of a newly synthesized 3-(4-chlorobenzoylmethyl) benzimidazolium bromide inhibitor against carbon steel corrosion in 1N hydrochloric acid solution was studied and analyzed utilizing various electrochemical methods. Electrochemical impedance study inferred that the inhibition efficiency increased with increasing inhibitor concentration and give 93.5% at 250ppm. Potentiodynamic polarization study emphasized that inhibitor acted as a mixed type inhibitor and the adsorption of inhibitor on the metal surface followed Langmuir adsorption isotherm. The noise results were in good correlation with other electrochemical results obtained. The increase of inhibition efficiency with concentrations of inhibitor is attributed to the blocking of the active area by the inhibitor adsorption on the metal surface. The thermodynamic parameter values were calculated and discussed to explain the adsorption mechanism of inhibitor in an acidic medium. The protective surface morphology governed by the inhibited medium was investigated using the scanning electron microscopic technique. The surface roughness of the sample in the absence and presence of inhibitor was obtained using atomic force microscopic study. The effect and reactivity of the inhibitor are further clarified with quantum chemical analysis. Finally, the corrosion protection mechanism is proposed on the ground of experimental and theoretical studies. Graphical abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Nature B.V. -
Exploring the inhibition performance of tetrachloroferrate ionic liquid in acid environment using scanning electrochemical microscope and theoretical approaches
The corrosion inhibition performance of carbon steel by Benzyltributylammonium tetrachloroferrate ([BTBA]+[FeCl4]?)was investigated in 1 N HCl solution and compared with theoretical results. The electrochemical impedance results showed that [BTBA]+[FeCl4]?ionic liquid act as an effective inhibitor for carbon steel corrosion in acidic medium and maximum inhibition efficiency was found to be 99.5% at 400 ppm. The SECM results also confirmed the adsorption of [BTBA]+[FeCl4]?on carbon steel and thereby forming a relatively insulated surface at the interface. The adsorption of ferrate ionic liquid on carbon steel was found to obey Langmuir adsorption isotherm. Ionic liquid effectively inhibits anodic and cathodic reaction site thereby showed its mixed type inhibition behaviour. In presence of the inhibitor higher resistance values were obtained for impedance and polarization studies. The presence of ionic liquid and its surface protection tendency at the metal/solution interface was confirmed by SEM surface studies. UVVis and ATR-FTIR characterization also contributed in corroborating the complex formation between Fe2+ and ionic liquid. Monte Carlo simulation and quantum chemical parameters substantiated the experimental findings and gave further insights about the inhibition mechanism. 2020 Elsevier B.V. -
Probing the effect of newly synthesized phenyltrimethylammonium tetrachloroaluminate ionic liquid as an inhibitor for carbon steel corrosion
The corrosion protection effect of phenyltrimethylammoniumtetrachloroaluminate[PTMA]+[AlCl4]?as an inhibitor was explored in the present work. In this paper, the authors have explored a non-heterocyclicbased ionic liquid as a corrosion inhibitor for metal protection in the acid cleaning process of metal. In particular, a negative ion is designed based onthe lewis acid concept by which it could cover the maximum surface by the bigger molecule size. The inhibition efficiency was found to be steadily increasing as the concentration of the [PTMA]+[AlCl4]? ionic liquids increased.These studies revealed thatthe inhibitor exhibited a remarkable potential for corrosion protection on carbon steel in 1 N HCl solution. Stable corrosion protection efficiency (96%) was achieved for 1.3 mMof inhibitor. The adsorption of the inhibitive molecule was studied by Langmuir adsorption isotherm. The anti-corrosion effect of ionic liquid on the surface protection was revealed by scanning electron microscope (SEM)and lower surface roughness attained at an optimum concentration of inhibitor in atomic force microscope (AFM) analysis. In this study, with the view of the experimental and theoretical investigation (gaseous and aqueous forms of [PTMA]+[AlCl4]? ionic liquid in presence of HCl)was investigated, and finding deduced that the ionic liquid offered maximum dispenses with the heterocyclic group. In addition, to validate the experimental result, dynamic simulation studies were performed in both gaseous and liquid stimulation conditions. 2021 The Author(s) -
Evaluating prolonged corrosion inhibition performance of benzyltributylammonium tetrachloroaluminate ionic liquid using electrochemical analysis and Monte Carlo simulation
Corrosion inhibition performance of a newly synthesized ionic liquid Benzyltributylammonium tetrachloroaluminate [BTBA]+[AlCl4]?on carbon steel has been studied using electrochemical impedance and noise analysis in 2 N HCl medium. The synthesized product was characterized by ATR-FTIR and1H NMR spectroscopic studies. The investigation revealed that the synthesized ionic liquid, [BTBA]+[AlCl4]?showed a remarkable noise and charge transfer resistance against corrosion. The adsorption behaviour of [BTBA]+[AlCl4]- on metal surface was found to follow Langmuir adsorption isotherm. The inhibition efficiency is measured as a function of immersion time and exhibited prolonged protection against acidic corrosion. Results derived from UVVis spectra explained the complex formation between the metal surface and ionic liquid in acid medium. SEM/EDAX has been used to examine the surface protection offered by the ionic liquid. [BTBA]+[AlCl4]?ionic liquid exhibited good corrosion inhibitor property with an efficiency of 97% at the optimum concentration. Quantum chemical analysis and molecular simulation studies were performed to support the experimental data. 2019 Elsevier B.V.