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Exploring tourists metaverse experience using destination spatial presence quality & perceived augmentation: metaverse exploration, physical expedition (MEPE)
A recent surge of interest surrounds metaverse tourism, with researchers highlighting its potential to revolutionize the tourism industry and attract new travellers. This article delves into the key features of a tourist's metaverse experience that influence their desire to visit a destination in the real world using systems theory. In addition, the current study also explores the moderating role of FOMO (Fear of missing out) in few of the proposed relationships. The study is a cross-sectional descriptive investigation carried out among Indian tourists chosen based on the simple random sampling technique and is analyzed using the Smart PLS software. The findings of the study reveal that several attributes of a tourist's metaverse experience, including entertainment, interaction, trendiness, novelty, and intimacy, significantly enhance both the perceived quality of spatial presence within the destination and the level of perceived augmentation experienced by tourists. Notably, both these factors then exert a significant positive influence on a destination's brand equity, ultimately explaining tourists' intentions to visit the physical location. Interestingly, the moderating role of Fear of Missing Out (FOMO) suggests that the relationship between brand equity and the likelihood of tourists undertaking a physical visit is strengthened as their perceived FOMO increases. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Exploring various nanomaterials in enhancing the performance of chiral nematic liquid crystal for blue phase display
This study aims to develop composite liquid crystal (LC) materials for energy-efficient blue phase (BP) display applications with enhanced luminescent and dielectric properties. Chiral nematic liquid crystal (CNLC) was systematically doped with nanomaterials, including nickel zinc ferrite (NZFO), single-walled carbon nanotubes (SWCNT), gold nanoparticles (GNPs), and strontium titanate (SrTiO3). Optimal doping concentrations (0.05 wt% for NZFO and SWCNT; 0.1 wt% for GNPs) enhanced photoluminescence, while SrTiO3 served as a luminescence quencher. Dielectric studies revealed a substantial reduction in the Freedericksz transition threshold voltage, particularly with NZFO (0.05 wt%), which halved the voltage. Optical texture and structural analysis confirmed that the CNLC structure remain intact while maintaining the BP temperature window (12 C). The reduced splay elastic constant in all doped CNLC revealed that the optimum quantity of nanomaterials is occupied in the disclination site of BP, resulting in a reduction of volume and associated free energy around the disclinations to reduce threshold voltage. These findings highlight the potential of nanomaterial-doped CNLCs, especially magnetic NZFO NPs, in enabling high-performance, low-power BP-based LC displays for advanced applications. 2025 Elsevier B.V. -
Exploring vector and raster data formats for geospatial visualization with python
The chapter uses Python to explore vector and raster data formats within geospatial visualization. It highlights their pivotal role across diverse environmental science, urban planning, and natural resource management domains. A nuanced comprehension of these formats is deemed essential for proficient geospatial visualization in Python, as they facilitate the storage and manipulation of spatial data. Vector data formats accurately represent points, lines, and polygons within a coordinate system. In contrast, raster data formats are tailored to depict continuous surfaces or grids of data. An array of libraries and tools are outlined for exploring and visualizing these geospatial data formats in Python, each serving distinct functionalities ranging from data manipulation to visualization. The chapter systematically introduces the concept of geospatial visualization, elucidates the disparities and application scenarios of vector and raster data formats, and subsequently elucidates various Python libraries and tools conducive to geospatial data manipulation and visualization. 2024 by IGI Global. -
Exploring White Knight Syndrome in an Indian Setting: A Grounded Theory Approach
White knights are individuals who enter into romantic relationships with damaged and vulnerable partners, hoping that love will transform their partners behaviour or life. Existing literature on white knight is limited to a handful of studies, primarily based on Western population. The present research aimed at developing a substantive theory on white knight syndrome in an Indian setting. The study follows a qualitative paradigm and the research design is grounded theory approach to be specific. Participants for the study were screened using Lamias white knight checklist. Data has been collected from eighteen young adults aged 1825years through semi-structured interviews. The data was analyzed using Strauss and Corbin grounded theory analysis. The study identified six phasespre-relationship phase, needs exploration phase, shining white knight phase, drained white knight phase, golden realization phase, and finally delayed breakup. Along with the phases, the study identified factors, characteristics, and types of white knight. The study has implications in the clinical and counselling field in identifying and understanding white knight tendencies. Additionally, the theory is applicable in the Indian setting highlighting the intricate interaction between culture, norms, roles, and the recent social factors. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Exploring women centric roles in contemporary Telugu movies /
The present study deals with the scenario of women centric films in the Telugu film industry, and how the characterization of these women characters is done in the select films. The films dealt with, are chosen from the contemporary era varying from 2000-2016. Various aspects of the roles have been explored in order to elicit the importance of these characters and also their contribution to the overall plot. -
Exponential heat source effects on the stagnation-point heat transport of Williamson nanoliquid with nonlinear Boussinesq approximation
The nonlinear two-point partial differential boundary value problem associated with the nano-pseudoplastic material flow and heat transport subject to nonlinear Boussinesq approximation is computed and explored statistically. Heat transportation features are analyzed by the consideration of an exponential space-related heat source and the Buongiorno model of nanofluids. The boundary-driven expressions of the physical phenomenon are coupled and highly complicated due to the consideration of nonlinear convection terms. Reasonable variables are employed to reform the partial differential equations into a system of ordinary differential expressions and are solved numerically. Furthermore, correlation and regression techniques are employed for the statistical evaluation of the phenomenon. The probable error is implemented to calculate the reliability of the computed correlation factors. The exponential index and Schmidt number are positively correlated with the reduced skin friction coefficient whereas the other parameters are negatively correlated with it. The heat transfer rate is improved predominantly by the nonlinear thermal convection parameter. The temperature is enhanced by the intensification of the exponential-based heat source factor. The temperature and concentration profiles are boosted by incrementing the Biot number values. 2021 Wiley Periodicals LLC -
Export performance of Indian textile industry in the post multi fibre agreement regime /
Artha Journal Of Social Science, Vol.13, Issue 4, pp.63-86, ISSN No: 0975-329X. -
Expression of dissatisfaction in relation to managerial leadership strategies and its impact in Iinformation technology organizations /
Skyline Business Journal, Vol.8, Issue 1, pp.29-35, ISSN: 1998-3425. -
Expressions of Women Survivors of Domestic Violence: Idioms of Distress
Domestic violence is prevalent worldwide; however, there are cultural differences in womens experiences of this phenomenon. This study used the concept of idioms of distress, to understand the impact of domestic violence on women survivors in India. A qualitative method was adopted, and semi-structured interviews were conducted with six women survivors of domestic violence. Using thematic network analysis, one global theme, four organizing themes and 19 basic themes emerged. The idioms of distress identified included, physiological idioms (such as aches and pains, nutritional deficiencies, reproductive), psychological idioms (such as depression, low self-confidence, change in aspirations and ambitions, mistrust, rumination) and behavioral idioms (such as crying, withdrawal, irritability, disturbed sleep). Of all the idioms, only nutritional deficiencies and the reproductive idioms were of concern to the survivors and their marital family. Implications for improving the screening of domestic violence are discussed based on the identified idioms and the responses toward them. 2019, National Academy of Psychology (NAOP) India. -
Extended Slash Modified Lindley Distribution to Model Economic Variables Showing Asymmetry
This article introduces a novel probability distribution to model economic variables with high kurtosis and heavy tails showing a decreasing trend. From a mathematical viewpoint, it corresponds to the distribution of the ratio of two independent random variables, one with the modified Lindley distribution and another with the beta distribution. In some sense, it can be described as an extended three-parameter version of the Lindley distribution that has the ability to model data with high kurtosis. After presenting this distribution in more in-depth details, a comprehensive analysis is given, including its associated functions, moments, skewness, and kurtosis characteristics. Furthermore, a parametric estimation work is carried out. A simulation approach is used to validate the performance of the obtained estimates. The applicability of the proposed distribution is demonstrated by fitting real-world data into various socioeconomic scenarios. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Extended virtual reality based memory enhancement model for autistic children using linear regression
Extended Virtual Reality has expanded its wings to almost each and every sector enabling immersive experience in various fields and has found applications in gamification, learning, healthcare, etc. This technology has aided in providing solutions to various problems in different fields, and healthcare is the most prominent one among them. Children suffering from ASD which is a developmental disorder affecting the brain that impacts how a person perceives external responses, are finding it increasingly difficult to get treated as the treatment methods are tedious. There are very few methods which are regarded as standardized means of treating autistic children but there are a few common traits that can be found in children affected by ASD which can be grouped under three common categories. They are lack of communication skills, lack of basic mathematical knowledge and low levels of remembrance. With the help of Gamification, which provides therapy by means of games to those affected, the kids affected by ASD can be treated, powered by the concept of Extended Virtual Reality. In this paper, we have developed a model to provide autistic children a real world experience of playing games which will help them in enhancing their skills without any external interferences. Children who play these Extended Virtual Reality based games show gradual improvement, for which the results can be facilitated with the help of a Linear Regression model, helping us predict future response times. The proposed model results in enhancement of memory levels of the kids as a result of the game and classifies kids based on their enhancement in memory into high, medium and low. The mean absolute error of the linear regression model is found to be 0.0394. 2024, The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden. -
Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives
Recently, we developed a machine-learning algorithm EMPaSchiz that learns, from a training set of schizophrenia patients and healthy individuals, a model that predicts if a novel individual has schizophrenia, based on features extracted from his/her resting-state functional magnetic resonance imaging. In this study, we apply this learned model to first-degree relatives of schizophrenia patients, who were found to not have active psychosis or schizophrenia. We observe that the participants that this model classified as schizophrenia patients had significantly higher schizotypal personality scores than those who were not. Further, the EMPaSchiz probability score for schizophrenia status was significantly correlated with schizotypal personality score. This demonstrates the potential of machine-learned diagnostic models to predict state-independent vulnerability, even when symptoms do not meet the full criteria for clinical diagnosis. 2020, The Author(s). -
Extensible Business Reporting Language (XBRL)- A Modern Age Business Language System and its Developments Scenario within India & Abroad
International Journal of Applied Financial Management Perspectives Vol. 1, No. 1, pp. 60-65, ISSN No. 2279-0896 -
Extensive long-term verbal memory training is associated with brain plasticity
The human brain has a remarkable capacity to store a lifetime of information through visual or auditory routes. It excels and exceeds any artificial memory system in mixing and integrating multiple pieces of information encoded. In this study, a group of verbal memory experts was evaluated by multiple structural brain analysis methods to record the changes in the brain structure. The participants were professional Hindu pandits (priests/scholars) trained in reciting Vedas and other forms of Hindu scriptures. These professional Vedic priests are experts in memorization and recitation of oral texts with precise diction. Vedas are a collection of hymns. It is estimated that there are more than 20,000 mantras and shlokas in the four Vedas. The analysis included the measurement of the grey and white matter density, gyrification, and cortical thickness in a group of Vedic pandits and comparing these measures with a matched control group. The results revealed an increased grey matter (GM) and white matter (WM) in the midbrain, pons, thalamus, parahippocampus, and orbitofrontal regions in pandits. The whole-brain corelation analysis using length ofpost-training teachingduration showed significant correlation with the left angular gyrus. We also found increased gyrification in the insula, supplementary motor area, medial frontal areas, and increased cortical thickness (CT) in the right temporal pole and caudate regions of the brain. These findings, collectively, provide unique information regarding the association between crucial memory regions in the brain and long-term practice of oral recitation of scriptures from memory with the proper diction that also involved controlled breathing. 2021, The Author(s). -
Extraction and characterization of biofuel from industrial waste organic pupae-silkworm
The current work carted out of analysis on the production of fuel from pupae fat extracted from silkworm, and exhaustive investigations were conducted to determine the characteristics of obtained fuel and its blends. The oily organic compounds derived from silkworm is effectively adopted to produce biofuel. The soxhlet extractor is utilized here to separate the oil content from pupae and obtained oil processed into biofuel by undertaking the transesterification process using NaOH as a fast reactive agent along with methanol. The rate of biofuel derived from pupae oil has been noticed to be 65-70 by vol%. The extracted fuels from the transesterification process were mixed with high-speed diesel at a rate of B10, B20, B30 and B40 on volume base. The most important physical and chemical characteristics of generated fuel and their mixture with conventional diesel were examined. The investigation results reveal that the fuel sample B20 satisfies all the requirements of ASTM standards. Pure biofuel shows that the lesser heating value, higher KV, flash point, fire point and density than that of conventional diesel. The blended samples reveal that all the properties are keep moving towards higher value with an increasing percentage of biofuel presence except calorific value. Finally results in evidence that, well suitable biofuel can be generated from organic waste material like silkworm and effectively use it in practical applications. BEIESP. -
Extraction and characterization of biofuel from industrial waste organic pupae-silkworm /
International Journal of Recent Technology And Engineering, Vol.8, Issue 3, pp.1603-1607, ISSN No: 2277-3878. -
Extraction and characterization of preformed mixed phase graphene sheets from graphitized sub-bituminous coal
In present paper, a facile method is reported to extract mixed phase nanometre-sized carbon sheets from sub-bituminous coal. The lattice constants (La and Lc) of sub-bituminous coal were calculated to be 4.82 and 1.41 nm, respectively. The aromatic layers and average number of carbon atoms in the aromatic lamellae were estimated as 5 and 8, respectively. The obtained graphene sheets exhibits broadened D and G band in addition to a very broad 2D bump. Defect to graphitic ratio is found to be 0.54 indicating less disorder in graphene nanomaterial formed. This is further corroborated by (ID/ID') ratio which was observed to be 3.40, confirming the defect has originated from boundary. The SEM analysis reveals the formation of large number of carbon layers with different shape in the nanometer scale range. Formation of graphene dots in the shape of hexagonal, spherical, graphene layers and corn shaped carbon nanotubes are noticed in the TEM image. -
Extraction and characterization of wrinkled graphene nanolayers from commercial graphite
A report on the synthesis of wrinkled graphene nano carbon from bulk graphite is presented here. The obtained graphene nano carbon comprises mixed phase, sp2-sp3 bonded disordered carbon network. The as synthesized samples were intercalated by Hummer's method and are separated by centrifugation and sonication to obtain few layer graphene sheets. The structural and chemical changes of the nanostructure was elucidated by Raman spectroscopy, XRD, SEM-EDS, XPS, FTIR and UV-Vis-NIR spectroscopy. Raman spectra confirmed the existence of highly graphitized amorphous carbon with five peaks in the deconvoluted first order Raman spectrum. The IR and XPS analysis confirms the incorporation of functional groups to graphitic basal plane. There was a shift in the peaks position and intensity with intercalation. The synthesized graphene sheet is found to be in the graphite to nanocrystalline graphitic trajectory. The SEM analysis revealed the formation of large area wrinkled graphene sheets. The nanostructure formed is effortlessly scalable and ideally suitable for nano carbon composites based nano electronic devices and switches. -
Extraction of features from video files using different image algebraic point operations
In the human-computer interaction (HCI) field, facial feature analysis and extraction are the most decisive stages which can lead to a robust and efficient classification system like facial expression recognition, emotion classification. In this paper, an approach to the problem of automatic facial feature extraction from different videos are presented using several image algebraic operations. These operations deal with pixel intensity values individually through some mathematical theory involved in image analysis and transformations. In this paper, 11 operations (point subtraction, point addition, point multiplication, point division, edge detecting, average neighborhood filtering, image stretching, log operation, exponential operation, inverse filtering, and image thresholding) are implemented and tested on the images (video frames) extracted from three different self-recorded videos named as video1, video2, video3. The videos are in .avi, .mp4 and .wmv format respectively. The work is tested on two types of data: grayscale and RGB (Red, Green, Blue). To assess the efficiency of each operation, three factors are considered: processing time, frames per second (FPS) and sharpness of edges of feature points based on image gradients. The implementation has been done in MATLAB R2017a. 2019 Association for Computing Machinery. -
Extraction of Fungal Chitosan by Leveraging Pineapple Peel Substrate for Sustainable Biopolymer Production
The cost-effective production of commercially important biopolymers, such as chitosan, has gained momentum in recent decades owing to its versatile material properties. The seasonal variability in the availability of crustacean waste and fish waste, routinely used for chitosan extraction, has triggered a focus on fungal chitosan as a sustainable alternative. This study demonstrates a cost-effective strategy for cultivating an endophytic fungus isolated from Pichavaram mangrove soil in a pineapple peel-based medium for harvesting fungal biomass. Chitosan was extracted using alkali and acid treatment methods from various combinations of media. The highest chitosan yield (139 0.25 mg/L) was obtained from the pineapple peel waste-derived medium supplemented with peptone. The extracted polymer was characterized by FTIR, XRD, DSC, and TGA analysis. The antioxidant activity of the fungal chitosan was evaluated using DPPH assay and showed an IC50 value of 0.22 mg/L. Subsequently, a transparent chitosan film was fabricated using the extracted fungal chitosan, and its biodegradability was assessed using a soil burial test for 50 days. Biodegradation tests revealed that, after 50 days, a degradation rate of 28.92 0.75% (w/w) was recorded. Thus, this study emphasizes a cost-effective strategy for the production of biopolymers with significant antioxidant activity, which may have promising applications in food packaging if additional investigations are carried out in the future. 2024 by the authors.