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Green synthesis of MgO nanoparticles and its antibacterial properties
Magnesium oxide nanostructured particles (NP) were prepared using a simple solution combustion technique using different leaf extracts such as Mangifera indica (Mango - Ma), Azadirachta indica (NeemNe), and Carica papaya (PapayaPa) as surfactants. The highly crystalline phase of MgO nanostructures was confirmed by PXRD and FTIR studies for 2h 500C calcined samples. To analyze the characteristics of obtained materialMaNP, NeNP, and PaNP for dosimetry applications, thermoluminescence (TL) studies were carried out for Co-60 gamma rays irradiated samples in the dose range 1050KGy; PaNP and NeNP exhibited well-defined glow curve when compared with MaNP samples. In addition, it was observed that the TL intensity decreases, with increase in gamma dose and the glow peak temperature is shifted towards the higher temperature with the increase in heating rate. The glow peak was segregated using glow curve deconvolution and thermal cleaning method. Kinetic parameters estimated using Chens method, trap depth (E), and frequency factor (s) were found to be 0.699, 7.408, 0.4929, and 38.71, 11.008, and 10.71 for PaNP, NeNP, and MaNP respectively. The well-resolved glow curve, good linear behavior in the dose range of 1050, KGy, and less fading were observed in PaNP as compared with MaNP and NeNP. Further, the antibacterial activity was checked against human pathogens such as Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. A visible zone of clearance was observed at 200 and 100?g/mL by the PaNP and NeNP, indicating the death of colonies by the nanoparticles. Therefore, PaNP nanomaterial is a potential phosphor material for dosimetry and antibacterial application compared to NeNP and MaNP. Copyright 2023 Rotti, Sunitha, Manjunath, Roy, Mayegowda, Gnanaprakash, Alghamdi, Almehmadi, Abdulaziz, Allahyani, Aljuaid, Alsaiari, Ashgar, Babalghith, Abd El-Lateef and Khidir. -
Application of fuzzy logic in multi-sensor-based health service robot for condition monitoring during pandemic situations
Purpose: The purpose of this study is to plan and develop a cost-effective health-care robot for assisting and observing the patients in an accurate and effective way during pandemic situation like COVID-19. The purposed research work can help in better management of pandemic situations in rural areas as well as developing countries where medical facility is not easily available. Design/methodology/approach: It becomes very difficult for the medical staff to have a continuous check on patients condition in terms of symptoms and critical parameters during pandemic situations. For dealing with these situations, a service mobile robot with multiple sensors for measuring patients bodily indicators has been proposed and the prototype for the same has been developed that can monitor and aid the patient using the robotic arm. The fuzzy controller has also been incorporated with the mobile robot through which decisions on patient monitoring can be taken automatically. Mamdani implication method has been utilized for formulating mathematical expression of M number of if and then condition based rules with defined input Xj (j = 1, 2, . s), and output yi. The inputs and output variables are formed by the membership functions Aij(xj) and Ci(yi) to execute the Fuzzy Inference System controller. Here, Aij and Ci are the developed fuzzy sets. Findings: The fuzzy-based prediction model has been tested with the output of medicines for the initial 27 runs and was validated by the correlation of predicted and actual values. The correlation coefficient has been found to be 0.989 with a mean square error value of 0.000174, signifying a strong relationship between the predicted values and the actual values. The proposed research work can handle multiple tasks like online consulting, continuous patient condition monitoring in general wards and ICUs, telemedicine services, hospital waste disposal and providing service to patients at regular time intervals. Originality/value: The novelty of the proposed research work lies in the integration of artificial intelligence techniques like fuzzy logic with the multi-sensor-based service robot for easy decision-making and continuous patient monitoring in hospitals in rural areas and to reduce the work stress on medical staff during pandemic situation. 2024, Emerald Publishing Limited. -
Impact of Digital Storytelling on Motivation in Middle School English Classrooms
Motivation is a key factor in the learning process, especially in language acquisition. This research examines the effects of using digital storytelling (DST) on motivation in English classrooms. The study, which used a mixed methods approach, involved 100 middle school students in Bengaluru selected through convenience sampling. Data collection methods included questionnaires and semi-structured interviews. Students were divided into experimental and control groups, with the former receiving DST-integrated instruction and the latter being taught using traditional methods. The results of the quantitative analysis showed a positive influence on motivation in the experimental group compared to the control group. Qualitative results showed that implementing DST increased students' motivation, engagement, and understanding of the English language more effectively than traditional teaching methods. Further research is encouraged to explore the full potential of DST to improve student language skills and motivation. 2024 IGI Global. All rights reserved. -
Impact of Digital Storytelling on Middle School Students' Attitudes Toward English Language Learning
The integration of digital storytelling (DST) into teaching has significantly influenced educational development, especially English language acquisition. This study examines the impact of DST-integrated pedagogy on students' attitudes and perceptions toward learning English. In a quantitative study using an experimental design, 200 middle school students were purposively selected and divided into control and experimental groups. The control group received the traditional method of language teaching, while the experimental group received the DST method. Data were collected through a survey and analysed using descriptive and Wilcoxon test. The results suggest that exposure to DST positively influenced students' attitudes and led to better understanding, engagement, and motivation in learning English in the treatment group. This suggests that incorporating DST into English lessons can improve teaching quality and students' overall progress. Further analysis is needed to fully explore the potential of DST-based instruction in developing language acquisition skills. 2024 IGI Global. All rights reserved. -
Organization justice impact on employee work engagement
Research methodology: For the study 200 employees of selected Educational Institutions in North NCR was taken as respondents. Data was collected using standard questionnaire containing standard scaled of distributive, procedural, interactional, trust and employee engagement. The relationships between justice perceptions and work engagement were analyzed using correlations and regression analysis. Findings: The analysis of the study indicates that there is a strong and positive relationship among organization justice and employee engagement. The study also indicates that procedural, interactional and distributive justice are inter related with each other. Further, distributive and interactional justice take precedence over procedural justice in determining job engagement, while distributive justice plays the most important role in determining organization engagement (OE), followed by procedural and interactional justice. Limitations: This paper adds to the very small number of studies that have investigated the role of interactional justice in enhancing job and OEs. It has also established inter-relationships between the three dimensions of organizational justice and their individual roles in determining job and OEs. 2020 SERSC. -
She Shores: A Study on the Lives, Challenges and Resilience of Women of the Koli Fishing Community in Mumbai
This study delves into the lives of women from the Koli fishing community in Mumbai, aiming to illuminate their unique life experiences and the daily struggles that often remain hidden beneath their prosperous facade. It endeavours to examine their agency and adaptive strategies employed to navigate these challenges. The research was conducted in Pachubandar, Vasai, located in the western suburbs of Mumbai, which stands as one of the prominent Koli settlements in the city. Employing a qualitative research approach coupled with an exploratory research design, the study engaged ten participants, comprising seven Koli women and three key informants from the community. Additionally, an observational analysis of four retail and wholesale fish markets in Mumbai was conducted to gain insight into the working conditions of Koli fisherwomen. This study adopts a gender-focused perspective to scrutinise the contextual vulnerabilities that shape the lives of Koli women. It underscores the paradox wherein, despite playing a pivotal role in sustaining both their families and the traditional fishing occupation, their contributions often go unnoticed. The Koli women face severe deprivation due to their limited access to property and decision-making authority. They find themselves entangled within traditional norms and patriarchal structures, which impede their access to essential assets and diverse livelihood resources. Although they significantly contribute to the fishery sector, their struggles, needs, and aspirations are frequently disregarded due to their lack of representation and involvement in decision-making bodies. The majority of these women work under precarious conditions, devoid of proper infrastructure, resources, and security. Furthermore, the evolving dynamics within the fishery sector, driven by rapid urbanisation and modernisation, have a profound impact on the lives and traditional livelihoods of Koli women. They now confront issues such as dwindling fish catches due to environmental degradation, heightened market competition, reduced livelihood spaces brought about by shifting urban and coastal landscapes, altered labour relations, and technological advancements. Consequently, they find themselves caught between the conflicting forces of tradition and modernity. The research also sheds light on the strategies devised by Koli women to resist and adapt to the uncertainties and challenges they encounter, ultimately safeguarding their livelihoods through self-organisation. The study emphasises the imperative to acknowledge their contributions as 'visible work' and advocates for the incorporation of gender considerations when formulating policies and development strategies within the fisheries sector. 2024 Meghna Roy. -
Educational Deprivation of the Tribes Insights from the Block-level Study
The paper examines the nature of tribal deprivation, with specific focus on the issue of education. The research delves into the supply- and the demand-side factors, which determined the state of education within a region. Reaffirming the deprivation faced by the tribal communities, the study identifies specific factors that cause marginalisation. It points to the failure of the uniform tribal development programme to deal with the context-specific problems and thereby achieving the targeted results. The paper suggests the importance of not assuming the homogeneity of tribal societies, and need for public policies that are sensitive to this fact, in order to translate the goal of empowerment into a reality. 2023 Economic and Political Weekly. All rights reserved. -
The mediating role of parental playfulness on parentchild relationship and competence among parents of children with ASD
Purpose: The difficulties of a child diagnosed with autism spectrum disorder (ASD) can lead to behaviours that are quite challenging for parents to understand and address. Most of the parental studies of ASD focus on the challenges faced by the parents. This study aims to adopt a strength-based model that investigates the mediating role of parental playfulness in the association between parentchild relationship and parental competence. Design/methodology/approach: This study is a quantitative study that adopts a correlational research design. The mediation analysis explores the role of parental playfulness as a mediator in the association between parentchild relationship and parental competence. The sample consisted of 120 parents of children diagnosed with ASD from India, selected using a purposive sampling technique. Findings: The mediation analysis results indicate that playfulness among parents of children with ASD was found to function as a partial mediator in the relationship between parentchild relationship and parental competence. This could suggest that more playful parents have better parentchild relationships and are competent in parenting. Research limitations/implications: These findings have importance in understanding the role of playful interaction on parentchild relationships and parenting competence, having implications for further research. Enabling playfulness in parenting will enhance children and parents to promote their relationship and thus feel competent to bring positive light in their lives. Practical implications: Most often, the clinicians are concerned with addressing only the autistic symptoms; it is also essential to look into parental well-being. Practical playful interaction training should help parents establish a rapport, understand, adjust and adapt with their child. Social implications: Practical intervention and training plans can be suggested to all family members to improve the condition of the child and the familys general well-being. As the study focused on the clinical population, the findings could provide useful inputs for mental health professionals and counsellors. Originality/value: There are some theoretical and empirical evidence that support positive outcomes of playfulness on personal well-being (Atzaba Poria, in press; Yue et al., 2016; Proyer, 2014). Although there has been some interest in the impact of childrens playfulness on their development (Bundy, 1997), little is known about the influence of parental playfulness on parents and children. Therefore, addressing these gaps, this empirical study focusses on investigating the role of parental playfulness in parentchild relationship and parental competence, rather than considering external challenges of parents based on the ASD childs behavioural challenges and autistic features. 2021, Emerald Publishing Limited. -
Mathematical analysis of histogram equalization techniques for medical image enhancement: a tutorial from the perspective of data loss
This tutorial demonstrates a novel mathematical analysis of histogram equalization techniques and its application in medical image enhancement. In this paper, conventional Global Histogram Equalization (GHE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Histogram Specification (HS) and Brightness Preserving Dynamic Histogram Equalization (BPDHE) are re-investigated by a novel mathematical analysis. All these HE methods are widely employed by researchers in image processing and medical image diagnosis domain, however, this has been observed that these HE methods have significant limitation of data loss. In this paper, a mathematical proof is given that any kind of Histogram Equalization method is inevitable of data loss, because any HE method is a non-linear method. All these Histogram Equalization methods are implemented on two different datasets, they are, brain tumor MRI image dataset and colorectal cancer H and E-stained histopathology image dataset. Pearson Correlation Coefficient (PCC) and Structural Similarity Index Matrix (SSIM) both are found in the range of 0.6-0.95 for overall all HE methods. Moreover, those results are compared with Reinhard method which is a linear contrast enhancement method. The experimental results suggest that Reinhard method outperformed any HE methods for medical image enhancement. Furthermore, a popular CNN model VGG-16 is implemented, on the MRI dataset in order to prove that there is a direct correlation between less accuracy and data loss. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
The presence of others increases prosociality: examining the role of dating Partners accompany on donation
Research in the field of prosocial behavior has shown that the presence of others has a significant effect on individuals prosociality. However, no research has explored such an effect of romantic partners presence. Studies in evolutionary psychology have shown benevolence/prosociality as an important factor when choosing a romantic partner. Therefore, in the present study, we hypothesized that people will donate more in the presence of dating partners to maintain a positive impression on them. The research followed a mixed-method approach. The first study, a vignette-based experiment showed that people believed the presence of a dating partner significantly enhances the chances of donation. The second study was a between-subject experiment that confirmed the findings of study 1 from both donors and receivers perspectives. The third study was a qualitative investigation, where a semi-structured interview method was used to find out how and why the presence of a dating partner may influence donation. The interviews showed that the presence of dating partners increases prosociality mainly because donors want to make a good impression and project the right image of them in their partners eyes. The research overall suggests that the human need for self-presentation that projects them more socially likable shapes their willingness to extend a helping hand to others in the presence of their romantic partners. 2024 Taylor & Francis Group, LLC. -
The development and primary validation of employee green behavior scale
Purpose: The increasing adverse impact of human behavior toward the environment has brought in changes in research focus on environmental behavior toward the workplace. Because the employee spends one-third of his day in his workplace, the initiatives taken by the employee also have an impact on the companys environmental stance. Therefore, the researchers gradually focus on employee green behavior (EGB) and its measurement. The study aims to devise a tool for measuring EGB. Design/methodology/approach: Two studies were carried out using the survey method using the purposive sampling technique. The data were collected (Studies 1 and 2) from managers and supervisors working in manufacturing companies located in Kolkata, India. Findings: The first study was done to extract the principal factors using an initial 30 items (N = 220). The result of the principal component analysis shows the emergence of three factors spread over 20 items with loadings above 0.40. The 20-item scale was again administered on managers and supervisors (N = 243). The second study was carried out to examine the convergent and discriminant validity as well as stability of the tool through confirmatory factor analysis (CFA) (N = 243). The result of CFA showed the presence of 16 items spread through three factors: practice and policy, digital use and recycle and reuse. Multiple fit indices support a three-factor model of the 16-item EGB scale. Research limitations/implications: The scale would be a good measure of EGB and can be used for further research. The EGB scale is a composite scale containing three major dimensions that can be used as a complete measure of EGB. Originality/value: The present research aims to fill the current gap by building a comprehensive tool for measuring EGB. The present scale has also addressed the shortcoming of the previous scale and tried to include varied proenvironmental behaviors exhibited in the workplace. 2024, Emerald Publishing Limited. -
SVD-CLAHE boosting and balanced loss function for Covid-19 detection from an imbalanced Chest X-Ray dataset
Covid-19 disease has had a disastrous effect on the health of the global population, for the last two years. Automatic early detection of Covid-19 disease from Chest X-Ray (CXR) images is a very crucial step for human survival against Covid-19. In this paper, we propose a novel data-augmentation technique, called SVD-CLAHE Boosting and a novel loss function Balanced Weighted Categorical Cross Entropy (BWCCE), in order to detect Covid 19 disease efficiently from a highly class-imbalanced Chest X-Ray image dataset. Our proposed SVD-CLAHE Boosting method is comprised of both oversampling and under-sampling methods. First, a novel Singular Value Decomposition (SVD) based contrast enhancement and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are employed for oversampling the data in minor classes. Simultaneously, a Random Under Sampling (RUS) method is incorporated in major classes, so that the number of images per class will be more balanced. Thereafter, Balanced Weighted Categorical Cross Entropy (BWCCE) loss function is proposed in order to further reduce small class imbalance after SVD-CLAHE Boosting. Experimental results reveal that ResNet-50 model on the augmented dataset (by SVD-CLAHE Boosting), along with BWCCE loss function, achieved 95% F1 score, 94% accuracy, 95% recall, 96% precision and 96% AUC, which is far better than the results by other conventional Convolutional Neural Network (CNN) models like InceptionV3, DenseNet-121, Xception etc. as well as other existing models like Covid-Lite and Covid-Net. Hence, our proposed framework outperforms other existing methods for Covid-19 detection. Furthermore, the same experiment is conducted on VGG-19 model in order to check the validity of our proposed framework. Both ResNet-50 and VGG-19 model are pre-trained on the ImageNet dataset. We publicly shared our proposed augmented dataset on Kaggle website (https://www.kaggle.com/tr1gg3rtrash/balanced-augmented-covid-cxr-dataset), so that any research community can widely utilize this dataset. Our code is available on GitHub website online (https://github.com/MrinalTyagi/SVD-CLAHE-and-BWCCE). 2022 Elsevier Ltd -
Lightweight Spectral-Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification
Of late, convolutional neural networks (CNNs) find great attention in hyperspectral image (HSI) classification since deep CNNs exhibit commendable performance for computer vision-related areas. CNNs have already proved to be very effective feature extractors, especially for the classification of large data sets composed of 2-D images. However, due to the existence of noisy or correlated spectral bands in the spectral domain and nonuniform pixels in the spatial neighborhood, HSI classification results are often degraded and unacceptable. However, the elementary CNN models often find intrinsic representation of pattern directly when employed to explore the HSI in the spectral-spatial domain. In this article, we design an end-to-end spectral-spatial squeeze-and-excitation (SE) residual bag-of-feature (S3EResBoF) learning framework for HSI classification that takes as input raw 3-D image cubes without engineering and builds a codebook representation of transform feature by motivating the feature maps facilitating classification by suppressing useless feature maps based on patterns present in the feature maps. To boost the classification performance and learn the joint spatial-spectral features, every residual block is connected to every other 3-D convolutional layer through an identity mapping followed by an SE block, thereby facilitating the rich gradients through backpropagation. Additionally, we introduce batch normalization on every convolutional layer (ConvBN) to regularize the convergence of the network and scale invariant BoF quantization for the measure of classification. The experiments conducted using three well-known HSI data sets and compared with the state-of-the-art classification methods reveal that S3EResBoF provides competitive performance in terms of both classification and computation time. 1980-2012 IEEE. -
Attitude of public towards higher education: Conceptual analysis /
Scholedge International Journal Of Multidisciplinary And Allied Studies, Vol.2, Issue 12, pp.19-28, ISSN No: 2394-336X. -
Analgesic and Anti-Inflammatory Potential of Indole Derivatives
Some indole analogues show a good analgesic activity but on the other hand, it has some serious side effects like gastric ulcer. Therefore, there is still a need to develop derivatives of non-steroidal anti-inflammatory drugs (NSAIDs) with fewer side effects. For this purpose, some indole derivatives were prepared with objectives to develop new derivatives with maximum efficacy and minimum side effects. 1-(1H-indol-1-yl)-2-(sstituephenoxy)-ethan-1-one derivatives (M1M4) were analyzed further by thin-layer chromatorgarphy (TLC), melting point, IR, and 1H-NMR. The synthesized compounds then underwent oral toxicity studies that include hematological, biochemical, and histopathological findings. The compound was then evaluated for invivo anti-inflammatory and analgesic activities on carrageenan-induced rat paw edema and acetic acid-induced writhing methods. As a result of the biological activities, promising results were obtained in the compound M2 (2-(2-aminophenoxy)-1-(1H-indol-1-yl)ethanone) and it was subjected to further studies. It was found that compound M2 was practically nontoxic, and no clinical abnormalities were found in hematology and biochemistry, correlated with histopathological observation. It also showed significant anti-inflammatory and analgesic activities at its oral high dose (400 mg/kg). The study suggested that compound M2 was found to have significant anti-inflammatory and analgesic activities. The possible mechanism of M2 might suggest being act as a central anti-nociceptive agent and peripheral inhibitor of painful inflammation. The possible mechanism of action of the compounds whose biological activity was evaluated was explained by molecular docking study against COX-1 and COX-2, and the most active compound M2 formed ?9.3 and ?8.3 binding energies against COX-1 and COX-2. In addition, molecular dynamics (MD) simulation of both M2s complexes with COX-1 and COX-2 was performed to examine the stability and behavior of the molecular docking pose, and the MM-PBSA binding free energies were measured as ?153.820 11.782 and ?172.604 9.591, respectively. Based on computational ADME studies, compounds comply with the limiting guidelines. 2022 Taylor & Francis Group, LLC. -
Experimental investigation and influence of filling ratio on heat transfer performance of a pulsating heat pipe
Experimental investigation of the two-phase system of a pulsating heat pipe taken into account useful heat transfer In the field of thermal management, many new prospective concepts and techniques have been developed, one of which is the pulsating heat pipe, a classic heat transfer technique. The PHP is constructed from 8 turns of copper tubes with inner diameters of 2 mm, wall widths of 1 mm, and a total length of 5324 mm. The CLPHP uses ethylene glycol as the functioning liquid at different fill proportions of 45 %, 55 %, 65 %, 75 %, and 85 % of its amount. The evaporator section is heated electrically by a plate heater ranging from 120 W to 600 W, and the condenser section is cooled by a continuous flow of cooling water. The results thermal resistance decreases gradually with an increase in heat transfer rate. It is apparent that a lower rate of thermal resistance is by a fill ratio of 55 %. The evaporator temperature is 181.57 C and the condenser temperature is 41.06 C for ethylene glycol measured for calculating heat transfer performance at 600 W, thermal resistance is 0.136 C/W, heat transfer coefficient is 526.45 W/m2-C, and enhanced heat transfer is thus good, exhibiting good improvement at a full percentage of 55 % and when compared with CFD results. 2023 Elsevier Ltd -
An equal split triple-band wilkinson power divider employing extended cross shaped microstrip line /
Microwave and Optical Technology Letters, Vol.60, Issue 10, pp.2488-2492. -
A molecular docking study of SARS-CoV-2 main protease against phytochemicals of Boerhavia diffusa Linn. for novel COVID-19 drug discovery
SARS-CoV-2, the causative virus of the Corona virus disease that was first recorded in 2019 (COVID-19), has already affected over 110 million people across the world with no clear targeted drug therapy that can be efficiently administered to the wide spread victims. This study tries to discover a novel potential inhibitor to the main protease of the virus, by computer aided drug discovery where various major active phytochemicals of the plant Boerhavia diffusa Linn. namely 2-3-4 beta-Ecdysone, Bioquercetin, Biorobin, Boeravinone J, Boerhavisterol, kaempferol, Liriodendrin, quercetin and trans-caftaric acid were docked to SAR-CoV-2 Main Protease using Molecular docking server. The ligands that showed the least binding energy were Biorobin with ? 8.17kcal/mol, Bioquercetin with ? 7.97kcal/mol and Boerhavisterol with ? 6.77kcal/mol. These binding energies were found to be favorable for an efficient docking and resultant inhibition of the viral main protease. The graphical illustrations and visualizations of the docking were obtained along with inhibition constant, intermolecular energy (total and degenerate), interaction surfaces and HB Plot for all the successfully docked conditions of all the 9 ligands mentioned. Additionally the druglikeness of the top 3 hits namely Bioquercetin, Biorobin and Boeravisterol were tested by ADME studies and Boeravisterol was found to be a suitable candidate obeying the Lipinskys rule. Since the main protease of SARS has been reported to possess structural similarity with the main protease of MERS, comparative docking of these ligands were also carried out on the MERS Mpro, however the binding energies for this target was found to be unfavorable for spontaneous binding. From these results, it was concluded that Boerhavia diffusa possess potential therapeutic properties against COVID-19. 2021, Indian Virological Society. -
Block chain-based security and authentication for forensics application using consensus proof of work and zero knowledge protocol
The technique that checks the origin, integrity, Zero-Knowledge authenticity of photographs is known as image authentication. Numerous studies on image authentication have revealed numerous trade-offs between four desirable features, namely robustness, security, flexibility, and efficiency. This study demonstrated a high-security Forensic Image (FI) as well as an authentication mechanism. Initially, the FI considered image registration with features for the Consensus method (CM) to generate blocks on each feature using a hypothesis test-based similarity measure. Because Proof-of-Work (PoW) blockchain technology is widely used, maintaining the Consensus PoW(CPoW) requires a massive amount of computing power. ZKP authentication is a critical cryptographic mechanism that authenticates network nodes without revealing the users identity or any other data given by the user. The blockchain stores the secret information, as well as the hash value of the original FI. This allows for the tracking of all medical pictures exchanged through the proposed blockchain network. The blockchain stores the private information as well as the hash value of the original medical image. The experimental results indicate the utility of the proposed approach with performance measures in contrast to established security analysis methods. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
A Study of Customer Satisfaction towards Selected Hotels in Bangalore
Golden Research Thoughts, Vol. 2, Issue No. 2, pp. 61-68, ISSN No. 2231-5063