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Sustainability in hospitality: The pathway to destination well-being in the "City of Lakes" Udaipur
With the rising popularity and a surge in demand for the "City of Lakes" Udaipur, the lake ecosystem has become vulnerable to various anthropogenic activities and pollution. The restricted structure of hotels on the lakefront faces various challenges in maintaining environmental regulations. This chapter explores hotels on the lakeside in Udaipur, which includes heritage hotels and modern accommodations, and their sustainability practices, such as energy efficiency, waste management, water conservation, and eco-design in hospitality architecture. Best practices in Udaipur's hospitality industry are explored through observation, document analysis, and interviews. The chapter establishes how circular economy builds environmental quality while regenerating resources. The implications of the study indicate a transformation of tourism governance in Udaipur by local authorities and academicians, which indeed can contribute to achieving a destination's well-being by addressing the challenges posed by the thriving tourism economy. 2024, IGI Global. -
Unheard and Unseen: Exploring the Disenfranchisement of Perinatal Loss in North-Indian Men
Mental distress is recognised as common following perinatal loss. But often, existing literature and bereavement care standards focus on women, leaving a gap in understanding mens grief. This qualitative study examined the emotional experiences of males from some Northern states of India, who had experienced perinatal loss, with a focus on grief disenfranchisement. Eleven participants were interviewed using a semi-structured guide. Thematic analysis unveiled themes on the intersection of religiosity and grief, social structuring of grief patterns, gender-based grieving, inhibited expression of grief in men, disenfranchisement of grief, self-focused coping, coping with the help of others, and interpersonal barriers to emotional disclosure. The findings provide valuable insights, helping mental health practitioners better understand mens experiences of perinatal loss and develop more effective support strategies. 2024 SAGE Publications. -
Chatbot Service Quality in Banking : Analyzing Indian Banking Customer Perceptions and Influence on Customer Satisfaction and Value
Purpose: The study has two objectives: first, to determine the quality of chatbot services provided by Indian banks; second, to assess the influence of chatbot service quality variables on customer satisfaction and customer value. Research Methodology: The study used a quantitative methodology, selecting individuals at random from a group of Indian banking clients. We used a questionnaire to collect data from the selected sample as part of a causal research investigation. We made use of SPSS and Python for this analysis. Customer satisfaction and value were taken into account as the dependent variables in our study. The seven elements of service qualityfunctionality, convenience, security, design, customization, enjoyment, and assurancemade up the independent variables. Findings: According to this study, client satisfaction and value were significantly shaped by the quality of the services provided. Customers value was significantly impacted by functionality and enjoyment, and their satisfaction was greatly influenced by assurance, design, and personalization. The unexpected negative impact assurance had on customer value is noteworthy and calls for more research. Practical Implications: In the highly competitive banking industry, this research has important ramifications for banks. It highlighted how important service quality is, which led banks to give priority to customer pleasure and think about making strategic changes. Banks could obtain a competitive advantage by improving the quality of their services, improving chatbot services, and implementing a customer-centric strategy by utilizing the research findings that have been presented. Our research helped banks evolve with the needs of their customers in mind, enabling them to gain credibility, repeat business, and long-term success in the ever-changing banking services market. Originality/Value: This study examined how consumers in Indian banks perceive the value and satisfaction of chatbot services and how they use them. The study provided useful recommendations and concepts to improve the general consumer experience. 2024, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Highly Luminescent MOF and Its in Situ Fabricated Sustainable Corn Starch Gel Composite as a Fluoro-Switchable Reversible Sensor Triggered by Antibiotics and Oxo-Anions
Frequent use of antibiotics and the growth of industry lead to the pollution of several natural resources which is one of the major consequences for fatality to human health. Exploration of smart sensing materials is highly anticipated for ultrasensitive detection of those hazardous organics. The robust porous hydrogen bonded network encompassing a free-NH2 moiety, Zn(II)-based metal-organic framework (MOF) (1), is used for the selective detection of antibiotics and toxic oxo-anions at the ppb level. The framework is able to detect the electronically dissimilar antibiotic sulfadiazine and nitrofurazone via fluorescence "turn-on"and "turn-off"processes, respectively. The antibiotic-triggered reversible fluoro-switching phenomena (fluorescence "on-off-on") are also observed by using the fluorimetric method. An extensive theoretical investigation was performed to establish the fluoro-switching response of 1, triggered by a class of antibiotics and also the sensing of oxo-anions. This investigation reveals that the interchange of the HOMO-LUMO energy levels of fluorophore and analytes is responsible for such a fluoro-switchable sensing activity. Sensor 1 showed the versatile detection ability which is reflected by the detection of a carcinogenic nitro-group-containing drug "roxarsone". In view of the sustainable environment along with quick-responsive merit of 1, an in situ MOF gel composite (1@CS; CS = corn starch) is prepared using 1 and CS due to its useful potential features such as biocompatibility, toxicologically innocuous, good flexibility, and low commercial price. The MOF composite exhibited visual detection of the above analytes as well as antibiotic-triggered reversible fluoro-switchable colorimetric "on-off-on"response. Therefore, 1@CS represents a promising smart sensing material for monitoring of the antibiotics and oxo-anions, particularly appropriate for the real-field analysis of carcinogenic drug molecule "roxarsone"in food specimens. 2022 American Chemical Society. -
Combined weighted feature extraction and deep learning approach for chronic obstructive pulmonary disease classification using electromyography
The COVID-19 outbreak has led to a rise in respiratory disease-related deaths, including Chronic Obstructive Pulmonary Disease (COPD). Early diagnosis of COPD is crucial, but it can be challenging to distinguish between different chronic pulmonary diseases due to their similar symptoms, leading to misdiagnosis and time-consuming manual inspections. To address this issue, this paper explores the use of a deep learning model to differentiate COPD from other lung diseases using lung sound captured during Electromyography (EMG). The model includes steps such as noise removal, data augmentation, combined weighted feature extraction, and learning. The model's efficacy was evaluated using various metrics, including accuracy, precision, recall, F1-score, kappa coefficient, and Matthews correlation coefficient (MCC), with and without augmentation. The results show that the model achieved 93% accuracy and outperformed other existing state-of-the-art deep learning models, increasing the robustness of clinical decision-making. The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023. -
Data visualization and toss related analysis of IPL teams and batsmen performances
Sports play a very significant role in the development of the human persona. Getting involved in games like Cricket and other various sports help us to build character, discipline, confidence and physical fitness. Indian Premier League, IPL provides the most successful form of cricket as it gives opportunities to young and talented players to show case their talents on various pitch. Decision-makers are the utmost customers for all fundamentals in the sports analytics framework. Sports analytics has been a smash hit in shaping success for many players and teams in various sports. Sports analytics and data visualization can play a crucial role in selecting the best players for a team. This paper is about the Toss Related analysis and the breadth of data visualization in supporting the decision makers for identifying inherent players for their teams. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Impact of Innovative Technology on Quality Education: The Resourceful Intelligence for Smart Society Development
Quality education is the systematic learning and execution road map that build confidence among the learners and develop employability skills. Innovative techniques are the central facilitators of providing quality education for the younger generation. The economists, scientists, management experts, and research initiators are putting their efforts to develop a certain sustainable system in quality education through innovative technology. This is about digital equity, customized education, activity-based classroom, where the young mind is to be in synchronizing with the technology to explore new possibilities of learning and accomplishment. The research initiative reveals the system of implementing the innovative technology for quality education that has a direct impact on smart society development. The principal outcomes of the research initiative include the innovative ideas that transform the traditional education system into a dynamic education framework. The framework includes the integration of tools and techniques for standard mode of operations that reflects the productive and realistic education system. The researchers gracefully interconnected the concepts, methods, and applications of a quality education system that will open up new vistas for future research initiatives in the area of digital education, industry-institution collaboration, developing smart society, and economy of a nation at large. There is significant level of impact of innovative technology on quality education that leads to independent employability skills, creative, and innovative projects for facilitating future generation. All the influencing factors of resourceful intelligence together have great impact on smart society development that leads to provide modern facilities for the residents of smart society and create favorable environment for the future generations. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Enhancing performance of WSN by utilising secure QoS-based explicit routing
Wireless sensor networks (WSN) are infrastructure less and self-configured a wireless network that allows monitoring the physical conditions of an environment. Many researchers focus on enhancing the performance of WSN in order to provide effective delivery of data on the network, but still results in lower quality of services like energy consumption, delay and routing. We tackle this problem by introducing a new routing algorithm, QoS-based explicit routing algorithm which helps in transmitting the data from source node to destination node on WSN. We also involve clustering process in WSN based on genetic algorithm and particle swarm optimisation (GA and PSO) algorithm. We proposed identity-based digital signature (IBDS) and enhanced identity-based digital signature (EIBDS) that involves reduction of computation overhead and also increasing resilience on the WSN. We also use advanced encryption standard (AES), for ensuring the security between nodes and avoid hacking of data by other intruders. Copyright 2020 Inderscience Enterprises Ltd. -
An energy efficient authentication scheme based on hierarchical ibds and eibds in grid-based wireless sensor networks
Wireless sensor network is a peculiar kind of ad hoc network, consists of hundreds of tiny, resource constrained as sensor nodes. Clustering is a demanding task in such environment mainly due to the unique constraints such as energy efficiency and dynamic topology. In this paper, a novel energy efficient cluster-based routing algorithm is proposed on which hierarchical identity-based digital signature (IBDS) and enhanced-identity-based digital signature (EIBDS) scheme is concerning in grid-based wireless sensor networks. Firstly we form clusters using multi-parameters-based type-2 fuzzy logic algorithm. This paper proposes an improved ant colony optimisation algorithm, which optimises the energy consumption on data transfer in a WSN. Each node in a sensor network is authenticated using elliptic curve cryptography (ECC). After a set of simulation tests on NS-3 simulator, our proposed work achieves good performance for various metrics. Copyright 2020 Inderscience Enterprises Ltd. -
A Survey on Enhancing System Performance of Wireless Sensor Network by Secure Assemblage Based Data Delivery
To provide secure data transmission in Cluster Wireless Sensor Networks (CWSNs), the challenging task is to provide an efficient key management technique. To enhance the performance of sensor networks, clustering approach is used. Wireless Sensor Network (WSN) comprises of large collection of sensors having different hardware configurations and functionalities. Due to limited storage space and battery life, complex security algorithms cannot be used in sensor networks. To solve the orphan node problem and to enhance the performance of the WSN, authors introduced many secure protocols such as LEACH, Sec-LEACH, GS-LEACH and R-LEACH, which were not secure for data transmission. The energy consumption in existing approach is more due to overhead incurred in computation and communication in order to achieve security. This paper studies about different schemes used for secure data transmission. We are proposing new methodology called IBDS and EIBDS that will increase the performance of WSN by reducing computational overhead and also increases resilience against the adversaries. 2017 IEEE. -
Machine Learning Model Enabled with Data Optimisation for Prediction of Coronary Heart Disease
Cardiovascular disorders remain leading cause for mortality worldwide, necessitating robust early risk assessment. Although machine learning models show promise, most rely on conventional preprocessing, which lacks model portability across datasets. We propose an integrated preprocessing pipeline enhancing model generalizability. Our methodology standardises features solely based on training statistics and then transforms test data identically to prevent leakage. We handle class imbalance through synchronised oversampling, enabling consistent performance despite distribution shifts. This framework was evaluated on an open-source dataset of clinical parameters from an African cohort using classifiers like support vector machines and gradient boosting. All models achieved upto 80% accuracy. Remarkably, evaluating the identical models on five external European and Asian datasets maintains 80% - 86% accuracy. Our reproducible data conditioning strategy enables precise and transportable heart disease risk prediction, overcoming population variability. The framework provides the flexibility to readily retrain models on new data or update risk algorithms for clinical implementation in diverse locales. Our work accelerates the safe translation of machine learning to guide cardiovascular screening worldwide. 2024 IEEE. -
Detecting Deepfake Voices Using a Novel Method for Authenticity Verification in Voice-Based Communication
The widespread use of deepfake technology in recent years has given rise to grave worries about the alteration of audio-visual material. The integrity of voice-based communication is particularly vulnerable to the threat posed by deepfake voice synthesis. The development of cutting-edge methods for the identification of deepfake voices is examined in this paper, which also offers a thorough analysis of current approaches, their advantages, and disadvantages. The research presents a novel method for detecting deepfakes in voice recordings that uses signal processing, machine learning, and audio analysis to separate synthetic voices from authentic voices. By achieving superior accuracy in differentiating between real and deepfake voices, and proposed method supplies a strong barrier against the misuse of voice synthesis technology for malicious purposes, also go over the research some of the possible uses for this technology, like voice authentication system security and social media platform content moderation. The paper's insights will support continued efforts to strengthen the authenticity of voice communication in the digital age and reduce the risks associated with deepfake voice synthesis. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Impact of Leverage on Valuation of Non-Financial Firms in India under Profitabilitys Moderating Effect: Evidence in Scenarios Applying Quantile Regression
The firms valuation (FV) is the key element for all stakeholders, particularly the investors, for their investment decisions. The main impetus of this research is to estimate the effects of the debt ratio (DR, i.e., leverage) on the FV (i.e., assets and market capitalisation) of the non-financial firms listed in India. The quantile panel data regression (QPDR) on the secondary data of 76 non-financial BSE-100 listed firms in India is employed. This study also checks the effect of the net profit margin (NPM) as profitability on the association between DR and FV. The QPDR estimates result in multiple quantiles and provide evidence in scenarios. The findings reveal a positive relationship of DR to assets only in higher quantiles, i.e., 90%ile), and a negative association of DR is found with a market capitalisation in all quantiles. Under the interaction effect, profitability (NPM) does not affect the association of DR with assets but negatively affects the association of debt ratio with market capitalisation in the middle (50%) quantile. The findings indicate that leverage (DR) affects a firms value. The studys outcomes are helpful to all stakeholders, particularly investors, to realise the leverage (DR) as a critical indicator of FV before making any investment decisions. Managers should also consider lower debt ratios for better firm value. The present analysis is original and holds novelty in the form of the moderating role of the net profit margin, i.e., the profitability of the firm between DR and FV in the non-financial firm in India. To the best of our knowledge, no such studies have been performed to look for the association of the debt ratio with a firms value under the effect of profitability in different quantiles using quantile regression. 2023 by the authors. -
A modern approach of swarm intelligence analysis in big data: Methods, tools, and applications
Swarm intelligence is one of the most modern and less discovered artificial intelligence types. Until now it has been proven that the most comprehensive method to solve complex problems is using behaviours of swarms. Big data analysis plays a beneficial role in decision making, education domain, innovations, and healthcare in this digitally growing world. To synchronize and make decisions by analysing such a big amount of data may not be possible by the traditional methods. Traditional model-based methods may fail because of problem varieties such as volume, dynamic changes, noise, and so forth. Because of the above varieties, the traditional data processing approach will become inefficient. On the basis of the combination of swarm intelligence and data mining techniques, we can have better understanding of big data analytics, so utilizing swarm intelligence to analyse big data will give massive results. By utilizing existing information about this domain, more efficient algorithm can be designed to solve real-life problems. 2023, IGI Global. All rights reserved. -
Surface adsorption and anticorrosive behavior of benzimidazolium inhibitor in acid medium for carbon steel corrosion /
Journal of Applied Electrochemistry, Vol.52, Issue 11, pp.1659–1674, ISSN No: 0021-891X (Print) 1572-8838 (Online).
Corrosion inhibition property of a newly synthesized 3-(4-chlorobenzoylmethyl) benzimidazolium bromide inhibitor against carbon steel corrosion in 1 N 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 250 ppm. 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. -
Evaluation of Corrosion Mitigation Performance of 1-(3,4,5-Trimethoxyphenylmethylidene)-2-Naphthylamine (TMPNA) Schiffs Base on Carbon Steel Using Electrochemical, Thermodynamic and Theoretical Approaches
A novel Schiff base,1-(3,4,5-trimethoxyphenylmethylidene)-2-naphthylamine(TMPNA) has been synthesized using naphthylamine and 3,4,5-trimethoxybenzaldehyde.The effective corrosion resistance and inhibition effect of TMPNA was studied at different concentrations in water medium on carbon steel by electrochemical techniques. The protective behavior of the passive film formed by the inhibitor was characterized through electrochemical impedance spectroscopy with an increased charge transfer resistance of 954 ?.cm2. The inhibition efficiency exhibited a gradual increase up to 92% with increase in schiff base concentration. Potentiodynamic polarization studies revealed that corrosion current decreased to 0.35 10?5A/cm2 with the addition of the inhibitor, TMPNA. Through various electrochemical studies such as impedance, polarization and electrochemical noise analysis (ENA), the concentration of TMPNA was optimized to 300ppm at which the maximum corrosion resistance was observed. Inhibition efficiency was found to decrease with increase in temperature. Also, the increased activation energy (Ea) value of 27kJ/mol confirmed that the inhibitor hindered the metal dissolution reaction. Adsorption of TMPNA on carbon steel/electrolyte interface was found to obey Langmuir adsorption isotherm. Scanning electron microscope (SEM) was used to evaluate the surface morphology. The Quantum chemical analysis (QCA) revealed that there was an electron transfer between TMPNA and the metal surface at ? 6.340eV. Molecular dynamic simulation study was carried out to investigate the adsorption of TMPNA on Fe (1 1 0) surface and adsorption energy value for the gaseous form was found to be ? 4197cal/mol. 2020, Springer Nature Switzerland AG. -
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. -
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) -
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. -
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.