Browse Items (11810 total)
Sort by:
-
A research note: More to ponder on the perspectives of sustainability of tourism destinations
This research note focused on tapping the research opportunities on the perspectives of sustainability on tourism destinations. Being a short communication, the research note was created using the literary sources that concentrated only on the sustainability of tourism destinations. Growing tourism attributes; need for positioning destinations in competitive industrial markets; rapid changes in tourism market characteristics, motives, and opportunities; and mainly to sustain the tourism resources for better future consumption and preservation were the primitive forces to undertake the research note, which would facilitate further research works in the arena. The communications highlighted the integral and in-depth aspects such as centrality of sustainability, tourists knowledge about sustainability, tourists responsibility towards sustainability of destinations and natural resources, destination behavior towards sustainability, blending culture and sustainability, and rural destinations and their relevance on a sustainable future. Beneficial keynotes for policy makers and others thereof were enumerated throughout the note. 2021, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
ENHANCING home security through visual CRYPTOGRAPHY
Home security systems in the recent times have gained greater importance due to increasing threat in the society. Biometrics deals with automated approaches of recognizing a user or verifying the user identity based on behavioral or physiological features. Visual cryptography is a scheme of secret sharing where a secret image is encrypted into shares which disclose no data independently about the original secret image. As the template of biometric are stored in centralized database due to the threats of security the template of biometric may be changed by attacker. If the template of biometric is changed then the authorized user will not be permitted to access the resource. To manage this problem the schemes of visual cryptography can be used to secure the face recognition. Visual cryptography offers huge ways for supporting such needs of security as well as additional authentication layer. To manage this problem the visual cryptography schemes can be used to secure digital biometric information privacy. In this approach the face or private image is dithered in two varied host images that is sheets and are stored in separate servers of data so as to assure that the original image can get extracted only by accessing both sheets together at a time and a single sheet will not be capable to show any data of private image. The main aim of the study is to propose an algorithm which is a combination of CVC and Siamese network. This research implements visual cryptography for face images in a biometric application. The Siamese network is essential to solve one shot learning by representation of learning feature that are compared to verification tasks. In this research face authentication helps in accomplishing robustness by locating face image from an n input image. This research explores the availability of using visual cryptography for securing the privacy to biometric data. The results of the proposed approach provide an accuracy of 93% which is found to be superior when compared with that of the approaches that are already in practice. 2020 -
Impact of COVID-19 on Delivery of Quality Hospitality Education in India
The Covid-19 pandemic caused many industries globally to undergo radical changes in their operational systems, disrupting the service delivery processes. The education industry is no exception to this phenomenon. India's higher educational institutions witnessed the immense challenge of taking the teaching process online with limited means and infrastructural support. This study aimed to assess the impact of the pandemic on the delivery of education online in India with particular reference to hospitality courses. A survey of 250 students and interview of 10 faculty members from 5 universities offering hospitality course across India showed that the online learning system is far from satisfactory and effective. Moreover, teachers need to undergo training sessions in order to improve their online teaching skills and create newer methods of imparting skills and evaluating students' performance. IJHTS -
Decolonizing Open Science: Southern Interventions
Hegemonic Open Science, emergent from the circuits of knowledge production in the Global North and serving the economic interests of platform capitalism, systematically erase the voices of the subaltern margins from the Global South and the Southern margins inhabiting the North. Framed within an overarching emancipatory narrative of creating access for and empowering the margins through data exchanged on the global free market, hegemonic Open Science processes co-opt and erase Southern epistemologies, working to create and reproduce new enclosures of extraction that serve data colonialism-capitalism. In this essay, drawing on our ongoing negotiations of community-led culture-centered advocacy and activist strategies that resist the racist, gendered, and classed structures of neocolonial knowledge production in the metropole in the North, we attend to Southern practices of Openness that radically disrupt the whiteness of hegemonic Open Science. These decolonizing practices foreground data sovereignty, community ownership, and public ownership of knowledge resources as the bases of resistance to the colonial-capitalist interests of hegemonic Open Science. The Author(s) 2021. -
Approach for Collision Minimization and Enhancement of Power Allocation in WSNs
Wireless sensor networks (WSNs) have attracted much more attention in recent years. Hence, nowadays, WSN is considered one of the most popular technologies in the networking field. The reason behind its increasing rate is only for its adaptability as it works through batteries which are energy efficient, and for these characteristics, it has covered a wide market worldwide. Transmission collision is one of the key reasons for the decrease in performance in WSNs which results in excessive delay and packet loss. The collision range should be minimized in order to mitigate the risk of these packet collisions. The WSNs that contribute to minimize the collision area and the statistics show that the collision area which exceeds equivalents transmission power has been significantly reduced by this technique. This proposed paper optimally reduced the power consumption and data loss through proper routing of packets and the method of congestion detection. WSNs typically require high data reliability to preserve identification and responsiveness capacity while also improving data reliability, transmission, and redundancy. Retransmission is determined by the probability of packet arrival as well as the average energy consumption. 2021 Debabrata Singh et al. -
Carcinogens in Food: Evaluating the Presence of Cadmium, Lead, in Poultry Meat in South India
Objective: Local chickens were spontaneously sampled and slaughtered in the central markets of Coimbatore, Erode, and Namakkal districts, South India. Materials and Methods: Wet digestion was used to extract lead (Pb), cadmium (Cd), and zinc (Zn) in their blood and selected different organs (intestine, breast, liver, and gizzard), and their concentrations were measured using an atomic absorption spectrophotometer. Results: Apart from the blood of chickens from Coimbatore and Namakkal, where Pb was not found, the concentrations of Pb in the blood and organs of chickens from the three towns ranged from 1.8 to 8.33 mg/kg, exceeding the maximum tolerance thresholds (0.1 mg/kg) in internal organs of poultry birds. Except for the intestine of chickens from the three areas, Cd was only found in the heart, blood, and gizzard of Erode chickens, as well as the liver and gizzard of Namakkal chickens, in concentrations ranging from 0.13 to 0.58. According to threshold level, the upper limit met the maximum limits (0.5 mg/kg). Zn was found in all sections of chickens from the three selected districts, with concentrations ranging from 4.96 to 174.17 mg/kg. Conclusion: Its concentrations were within the permissible limits (10-50 mg/kg) in some areas of certain chickens, but it surpassed the permissible limit in the liver of chicken from Coimbatore. Any organs and blood from local chickens sold in Coimbatore, Erode, and Namakkal areas can be hazardous to ones health. This work is licensed under a Creative Commons Attribution-Non Commercial 4.0 International License -
Improved Feature Selection Method for the Identification of Soil Images Using Oscillating Spider Monkey Optimization
Precision agriculture is the process that uses information and communication technology for farming and cultivation to improve overall productivity, efficient utilization of resources. Soil prediction is one of the primary phases in precision agriculture, resulting in good quality crops. In general, farmers perform the soil prediction manually. However, the efficiency of soil prediction may be enhanced by using current digital technologies. One effective way to automate soil prediction is image processing techniques in which soil images may be analyzed to determine the soil. This paper presents an efficient image analysis technique to predict the soil. For the same, a robust feature selection technique has been incorporated in the image analysis of soil images. The developed feature selection technique uses a new oscillating spider monkey optimization algorithm (OSMO) for the selection of features that are relevant and non-redundant. The new oscillating spider monkey optimization algorithm increases precision and convergence behavior by using an oscillating perturbation rate. A set of standard benchmark functions was deployed to visualize the performance of the new optimization technique (OSMO), and results were compared based on mean and standard deviation. Furthermore, the soil prediction approach is validated on a soil dataset, having seven categories. The proposed feature selection method selects the 41% relevant features, which provide the highest accuracy of 82.25% with 2.85% increase. 2013 IEEE. -
Decolonizing the Home at Home in the Pandemic: Articulating Women's Experience
Feminism bears the promise of liberation of and equality for women. Reading and teaching feminist texts, within the academia and in activist spaces, has provided the opportunity to explore what it means to become and be a woman. This article explores the experience of teaching a course on women's writing at the undergraduate level during the COVID-19 pandemic. Normally, a course on feminist writings is an occasion for self-reflection, thereby providing an opportunity to establish a dialogue between the domestic and the public. Such dialogues took place in secure institutional spaces such as classrooms or conference halls, without the intrusion of the domestic. However, as the teacher-student interaction shifted to an online mode during the pandemic, all the participants in this dialogue, including the instructor and the students, found themselves in domestic spaces, with family members listening. The article chronicles the anxieties of a woman instructor, as she teaches feminist texts from home to learners who are sitting behind computer screen in their homes and the possible impact of feminist ideas on the domestic spaces of all participants. 2022 The Author(s). Published by Oxford University Press on behalf of the English Association. All rights reserved. -
Female Director and Agency Cost: Does board gender diversity at Indian corporate board reduce agency conflict?
We examined the presence of women directors in top-level management and their effect on principal-principal conflict (PP) and principal-agent conflict (PA) on the firms listed on Indian stock exchange using a panel model approach. For analysis purpose, this study covers the sample of 75 companies belonging to various industries and listed in Bombay Stock Exchange Index, has been studied over thirteen financial years, i.e. from year 2006 to year 2019. This study uses panel data analysis, i.e. fixed effect model and random effect model. The proportion and presence (dichotomous) of women directors on top level management board is taken as the independent variable. Principalprincipal conflict measured by assets utilization ratio (AUR), and principal-agent conflict is been measured by dividend payout ratio (DPR), are taken as dependent variable in this study. The prime results of this study using panel data analysis, i.e. fixed effect (FE) and random effects (RE) estimation models point towards no significant impact of the female director (proportion and presence) on the firm's agency cost (PP and PA). 2021. Transnational Press London. All Rights Reserved. -
Development of an efficient real-time H.264/AVC advanced video compression encryption scheme
Multimedia is the combination of media such as text, graphics, video clips, and audio files. In todays world, multimedia plays an important role in many applications that we use in our daily lives. It is used in educational software, animation, sound, and text, as well as multi-media software. H.264/AVC video compression is extremely efficient in terms of compression. Despite this, H.264/AVC requires a lot of processing and consumes a lot of power insdespite of the fact that its compression efficiency is lower than that of H.264/AVC. We examine the various methods of Video H.264 Advanced Video Compression Standard Encryption Schemes in this paper. The performance of all types of encryption techniques will be evaluated using parameters such as cost overhead, delay, and encryption quality. This will provide us with a detailed comparative analysis of video encryption schemes, allowing us to determine which one is far more efficient for H.264/AVC. 2021 Taru Publications. -
Optimized Tree Strategy with Principal Component Analysis Using Feature Selection-Based Classification for Newborn Infant's Jaundice Symptoms
One of the most important and difficult research fields is newborn jaundice grading. The mitotic count is an important component in determining the severity of newborn jaundice. The use of principal component analysis (PCA) feature selection and an optimal tree strategy classifier to produce automatic mitotic detection in histopathology images and grading is given. This study makes use of real-time and benchmark datasets, as well as specific approaches for detecting jaundice in newborn newborns. According to research, the quality of the feature may have a negative impact on categorization performance. Additionally, compressing the classification method for exclusive main properties can result in a classification performance bottleneck. As a result, identifying appropriate characteristics for training the classifier is required. By combining a feature selection method with a classification model, this is possible. The major outcomes of this study revealed that image processing techniques are critical for predicting neonatal hyperbilirubinemia. Image processing is a method of translating analogue images to digital formats and manipulating them. The primary goal of medical image processing is to collect information useful for disease detection, diagnosis, monitoring, and therapy. Image datasets can be used to validate the performance of newborn jaundice detection. When compared to conventional approaches, it offers results that are accurate, quick, and time efficient. Accuracy, sensitivity, and specificity, which are common performance indicators, were also predictive. 2021 Debabrata Samanta et al. -
Factors Affecting Digital Visibility of Small and Medium Enterprises in India
This study sketches the importance of social media, integrated marketing communication, social customer relationship management and its transformation in the small and medium enterprises (SME). These factors can increase interaction and communication of SMEs with its customers. This study incorporates empirical method to elaborate how SMEs can increase visibility and reachability by gaining value through the usage of social media. Findings of the study highlight the challenges faced by SMEs with respect to visibility, examines the usage of different digital platforms by Indian SMEs which can resolve these difficulties and its impact on the business for improved visibility of SMEs when competition is hitting hard on all businesses. 2021 Management Development Institute. -
Cytogenetic Consequences Of Food Industry Workers Occupationally Exposed To Cooking Oil Fumes (Cofs)
Background: Cooking oil fumes (COFs) with smoking habits is a substantial risk that aggravates genetic modifications. The current study was to estimate the biological markers of genetic toxicity counting Micronucleus changes (MN), Chromosome Aberrations (CA) and DNA modifications among COFs exposures and control subjects inherent from South India. Materials and Methods: Present analysis comprised 212 COFs with tobacco users and equivalent number of control subjects. Results: High frequency of CA (Chromatid type: and chromosome type) were identified in group II experimental subjects also high amount of MN and DNA damage frequency were significantly (p < 0.05) in both subjects (experimental smokers and non-smokers). Present analysis was observed absence of consciousnessamong the COFs exposures about the destructive level of health effects of tobacco habits in working environment. Conclusion: COFs exposed workers with tobacco induce the significant alteration in chromosomal level. Furthermore, a high level of rate of genetic diseases (spontaneous abortion) were identified in the experimental subjects. This finding will be helpful for preventive measures of COFs exposed workers and supportive for further molecular analysis 2021,Asian Pacific Journal of Cancer Prevention. All Rights Reserved. -
Information Management Capacity and Supply Chain Performance: Mediating Effects of Supply Chain Practices, Competencies and Concerns
The present study aims to identify the impact of the information management capacity (IMC) of an organization on its supply chain performance (SCP). Also, this study attempts to understand the mediating role of the various components of supply chain management, namely, practices, competencies and concerns. A survey instrument was used to collect primary data from 250 SMEs which were selected randomly. Structural equation modeling (SEM) technique is used to test the hypotheses using SmartPLS. The final model indicated that information management capacity significantly influences the supply chain performance and supply chain management components, namely supply chain competence, practices and concerns mediate the relationship between information management capacity and supply chain performance. The results of this study provide a significant contribution to the theory of resource-based view. The number of managerial perspectives for improving operational capabilities was explained in this study. 2021 Management Development Institute. -
SCREEN TIME BEYOND GAMING AND SOCIAL MEDIA: EXCESSIVE AND PROBLEMATIC USE OF OVER THE TOP (OTT) PLATFORMS AMONG COLLEGE STUDENTS DURING COVID-19 PANDEMIC
There is a gap in existing literature regarding Over the Top (OTT) platform use contributing to the excessive and problematic screen time. We aimed to assess OTT platform use among college students and its associations with increased screen time, mental well-being, COVID-19 related anxiety and personality traits. A total of 1039 students from a college in India were invited to participate in this web-based survey. A majority of participants used OTT platforms regularly. Subscription to paid OTT platforms, poor mental well-being were associated with problematic OTT use; whereas personality trait of conscientiousness seemed to offer protection against problematic OTT use. 2021 Medicinska Naklada Zagreb. All rights reserved. -
Comic Memes and Sexist Humor in India: Tools for Reinforcement of Female Body-Image Stereotypes
Memes have been described as communicative and aesthetic practices that serve cultural, social, political purpose on a digital platform. Several studies, in the last decade, have attempted to study this digital aesthetic knowledge production as a powerful tool for political, racial, and gender-related discourses. Most often this knowledge is produced through comic multi-media texts. Many theorists believe that, digital media reinforces inequality, marginalization and such other social issues through the audio-visual-textual medium as much as it establishes the counter-discourses for equality, body activism, racial activism and the like. Speed and lack of censorship can be the cardinal reasons for the popularity of these memes. Among the mass-influencing gender-related memes are those encouraging fat-talk and body-image stereotypes. In the Indian context, 'Tag a Friend' memes is one such widely circulated meme which communicates body-shaming messages through sexist humor. It mainly targets the fat/colored/transgender women. The current study examines these memes using multimodal discourse analysis methodology. The paper attempts to investigate the revival/reproduction potential of color-shaming and body-shaming stereotypes via comic memes through Shiffman's memetic dimensions. The analysis establishes that memes can be a prominent site for the re-production of the problematic ideology of body/color shaming even in the 21st century. AesthetixMS 2021 -
Value Addition for Technology Start-Ups Through Physical Co-Location
Numerous economic theories, knowledge, social, and communication theories have extensively explored the phenomenon of physical co-location in various contexts. However, limited scholarly attention has been given to co-location in emerging contexts such as co-working spaces, predominantly used by start-ups. One of the critical questions examined is how co-location adds value to technology start-ups in the early and growth stages of their development. We chose a premium coworking space in Bangalore, Indias start-up capital, as the studys research setting during January March 2020. The qualitative research employed semi-structured interviews to explore the phenomenon. Our findings revealed that start-ups actively used co-located resources to explore, experiment, and validate new business ideas in the early stage. As they transitioned into the growth phase, they exploited co-located industry networks to expand into new markets. They also learned vicariously from other co-located resources and used them to solve complex problems and refined their processes and routines. As start-ups begin to grow and expand, co-location infrastructure-related costs are not justifiable, operations are less secure, and the meta culture of the co-located environment is in conflict with the firms operating culture. The results of this study have the potential to be significant for technology start-ups that are exploring new ways of working and addressing uncertainties during the early and growth stages of their development. 2021, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Multi-class SVM based network intrusion detection with attribute selection using infinite feature selection technique
An intrusion detection mechanism is a software program or a device that monitors the network and provides information about any suspicious activity. This paper proposes a multi-class support vector machine (SVM) based network intrusion detection using an infinite feature selection technique for identifying suspicious activity. Single and multiple classifiers generally have high complexity. To overcome all the limitations of single and multiple classifiers, we used a multi-class classifier using an infinite feature selection technique, which performed well with multiple classes and gave better results than other classifiers in terms of accuracy, precision, recall, and f_score. Infinite feature selection is a graph-based filtering approach that analyses subsets of features as routes in a graph. We used a standard dataset, namely the UNSW_NB15 data set generated by the IXIA perfect-storm tool in the Australian Centre for Cyber Security. This dataset has a total of nine types of attacks and 49 features. The comparative analysis of the manuscript work is done against eight different techniques, namely, hybrid intrusion detection system (HIDS), C5, one-class support vector machine, and others. The proposed work gave better simulation results using the 2015a Matlab simulator. 2021 Taru Publications. -
Selfie Segmentation in Video Using N-Frames Ensemble
Many camera apps and online video conference solutions support instant selfie segmentation or virtual background function for entertainment, aesthetic, privacy, and security reasons. A good number of studies show that Deep-Learning based segmentation model (DSM) is a reasonable choice for selfie segmentation, and the ensemble of multiple DSMs can improve the precision of the segmentation result. However, it is not fit well when we apply these approaches directly to the image segmentation in a video. This paper proposes an N-Frames (NF) ensemble approach for a selfie segmentation in a video using an ensemble of multiple DSMs to achieve a high-performance automatic segmentation. Unlike the N-Models (NM) ensemble which executes multiple DSMs at once for every single video frame, the proposed NF ensemble executes only one DSM upon a current video frame and combines segmentation results of previous frames to produce the final result. For the experiment, we use four state-of-the-art image segmentation models to make an ensemble. We evaluated the proposed approach using 81 videos dataset with a single-person view collected from publicly available websites. To measure the performance of segmentation models, Intersection over Union (IoU), IoU standard deviation, false prediction rate, Memory Efficiency Rate and Computing power Efficiency Rate parameters were considered. The average IoU values of the Two-Models NM ensemble, Two-Frames NF ensemble, Three-Models NM ensemble and Three-Frames NF ensemble were 95.1868%, 95.1253%, 95.3667% and 95.1734% each, whereas the average IoU value of single models was 92.9653%. The result shows that the proposed NF ensemble approach improves the accuracy of selfie segmentation by more than 2% on average. The result of cost efficiency measurement shows that the proposed method consumes less computing power like single models. 2021 IEEE.