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Beyond Bollywood and Hindi: making a case for other language films in India
[No abstract available] -
Effect of Subtitles on Gaze Behavior during Shot Changes: An Eye-tracking Study; [Efecto de los subtulos en el comportamiento de la mirada durante los cambios de plano: un estudio de seguimiento ocular]
The study provides a comprehensive picture of the effect of subtitles on the gaze behavior of the participants while watching continuity editing and discontinuity editing style cinema. Three video clips (with English subtitles and without subtitles) of continuity editing and discontinuity editing styles were presented to participants. The video clips came from English movies and the participants were not native English speakers. Entry time, dwell time, first fixation time, scan path, and average fixation duration were taken as dependent variables in this within-group study. The eye-tracking data gathered were subjected to repeated measures of two-way ANOVA and paired t-test. Results revealed that the appearance of subtitles at the bottom of the screen changed the eye movement pattern of the participants during the shot changes. Timing of the subtitle starting point (before the cut or after the cut) also affected the gaze behavior. The editing style, however, did not make any difference in the gaze behavior of participants while watching subtitled video clips. Further, participants preferred reading subtitles to seeing visual images even if the subtitles were presented during the shot changes. 2023. International Journal of Psychological Research provides open access to all its contents under the terms of the license creative commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) -
Indias environmental policy paradox: dissecting Indias budgetary allocations for environment
This paper examines Indias environmental policies and budget allocations from 20162024, revealing a focus on infrastructure that may overshadow environmental conservation. Significant discrepancies between policy rhetoric and budgetary commitments suggest that there is a need for realignment. Advocating an environment-centric approach, the study calls for increased budgetary commitments to environmental protection, a strategic shift away from fossil fuels, and stringent regulatory oversight, all essential to ensure sustainable development in India. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Bounds of Sombor Index for F-Sum Operation
Graph operations have a major impact in the aspects of theory and empirical literature of the domain. For relating the molecular topology to any real chemical attribute, the conversion of the relevant details embedded into chemical structure to some numeric value becomes so vital which ultimately paves the way for the emergence of topological indices. Topological descriptor acts as an effective graph invariant in chemical graph theory associated with certain molecular structure. Recently, the study on the sombor index is initiated by I.Gutman [16]. In the article, we utilise combinatorial inequalities, including the general sum-connectivity index, the first general zagreb index and few other indices in their formulations, for the determination of bounds for sombor index for the F-sum operation of connected graphs. Palestine Polytechnic University-PPU 2023. -
The paradox of workplace flexibility: navigating through the case of Career Pandit
Learning outcomes: The learning objectives are intended to stimulate the students comprehension of the various challenges faced by Indian startups in the digital ecosystem. With the changing working dynamics in organizations around the globe, managers are expected to explore unconventional business models to facilitate operational growth. The case study is a valuable resource for graduate students to enhance and evolve their critical thinking and solution-oriented skills as forthcoming managers of digital businesses. Students should be able to analyze the case, respond to the questions and evaluate the consequences of workplace flexibility, moonlighting and its applicability in an organizational context. With the Indian Government introducing schemes such as the Digital India initiative and Startup India, it is predicted that numerous startups will opt for digital business standards and a remote work approach. The case bridges classroom theories and a real-life digital company to help students connect with emerging market scenarios. Case overview/synopsis: During the digital era, India witnessed a shift in companies work culture, which amplified when COVID-19 hit the country. Organizations started to work remotely and experienced the numerous benefits it brought. The comfort of working from home was greater for digital businesses whose significant operations could be performed online. However, is it really that productive for digital companies to telecommute? The case illustrates how a digital company, Career Pandit, formed in 2018, unfurls and expands its business and further highlights the challenges the pandemic raised concerning people management. In addition to the discussion, the purpose of the case is to determine the implication of workplace flexibility and moonlighting and how Indian startups cope with the uncertain future challenges it brings. Complexity academic level: Under graduate and postgraduate students. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2023, Emerald Publishing Limited. -
Competitive and contagion effect of initial public offerings in India: An empirical study
This study aims to empirically examine the impact of initial public offerings (IPOs) on the equity share prices of industry rivals. The cross-industry sample comprises 13 companies across six different industries in the Indian market. The study investigates four key variables: the stock returns of industry rivals before and after the IPO of a new market entrant, as well as the daily traded volume of both the market entrant and industry rivals in the days following the IPO. The analysis reveals a significant association between the stock prices of industry rivals before and after the listing date of a market entrant, as evidenced by the adoption of three distinct time windows. However, no significant relationship is observed between the daily traded volume of market entrants and industry rivals. The results reveal the presence of the competitive and contagion effect and the lack of active capitalisation of this short-term phenomenon by investors. 2023 The Author -
Personality and Psychological Predictors of Instagram Personalized Ad Avoidance
The purpose of this paper is to apply the meta-theoretical model of motivation and personality (3M) of Mowen to study consumers ad avoidance in the context of online personalized advertisements on Instagram. The current study developed a theoretical framework that links personality traits with reactance arousal and ad avoidance behaviours. Based on the data analysis, it was found that consumers with higher general self-efficacy tend to have more reactance arousal (situational level trait) compared to ad irritation, ad skepticism (surface traits), and ad avoidance behaviours towards personalized advertising on Instagram. The findings will help advertisers and marketers in segmenting the market better based on young users efficacy levels, navigational habits, personality traits, functional motives, and demographic variables to effectively reach the targeted consumers. 2023 IGI Global. All rights reserved. -
Modelling temperature-dependent malaria transmission vector model considering different levels of immunity in host population
Malaria is spread by female Anopheles mosquitoes, which complete their life cycle by feeding on human blood. Parasites from the mosquito's saliva enter the human bloodstream through a mosquito bite. Thus, the link between humans and mosquitoes to parasites is established. According to WHO statistics, malaria appears widespread in tropical and subtropical locations around the equator, including most of Sub-Saharan Africa, Latin America, and Asia. The most prevalent causes of malaria transmission might be amicable temperature, which aids in the growth of the mosquito life-cycle, and a failure to maintain the local socio-economic condition, which reduces individual immunity. This study proposes the vector-host model to understand the spread of malaria infection. A vector model is used to understand the effects of temperature on the development of egg, larval, pupal, and adult mosquito populations. Furthermore, the role of immunity is being explored using the host model. Numerical simulations support the influence of temperature on disease transmission. The study draws attention to the fact that, along with issues like global warming and climate change, managing the socio-economic conditions of the area (healthcare facilities, environmental improvement) is essential for malaria eradication. CSP - Cambridge, UK; I&S - Honda, USA, 2023 -
Dynamic Connectedness and Volatility Spillover Effects of Indian Stock Market with International Stock Markets: An Empirical Investigation Using DCC GARCH
This study employs the DCC-GARCH model to investigate the dynamic connectedness between the Indian and significant global stock markets. Specifically, we examine daily log returns data of the National Stock Exchange (NSE) index and several international indices, including the United States, Australia, China, Germany, England, Japan, and Taiwan. Our analysis indicates a significant level of volatility spillover between the Indian stock market and the international stock market. Notably, we observe a significant positive spillover effect from the S&P 500 and FTSE 100 to the Indian stock market, suggesting contagion effects. Additionally, we find bidirectional spillover between the Indian stock market and the Nikkei 225 and Hang Seng, indicating a high level of interdependence between these markets. Our research contributes to the growing literature on the dynamic connectedness of stock markets and has important implications for policymakers and investors in emerging economies such as India. Overall, this study provides valuable insights into the nature and extent of spillover effects between the Indian and international stock markets. 2023 University of Pardubice. All rights reserved. -
Analysing the Impact of Perceived Risk, Trust and Past Purchase Satisfaction on Repurchase Intentions in Case of Online Grocery Shopping in India
The Indian online grocery market has been propelling since last few years. The size of online grocery market in 2020 was estimated as $2.9 billion and it is further anticipated to reach at the compound annual growth rate (CAGR) of 37.1% during 2021 to 2028. Companies such as Amazon, Flipkart grocery, BigBasket, Grofers and Jiomart have been coming up with new attractions for consumers such as providing timely no contact delivery, accepting various digital modes of payment and offering several discounts which have fascinated consumers towards buying their regular grocery from various online platforms. Corona virus has also fuelled up the safety concerns of people; due to which a large section of the citizens are working from home and are dependent on the online platform for various purposes including grocery shopping. This has provided several growth opportunities to the online grocery market. This research investigates about the purchase behaviour of customers towards online grocery shopping. The study aims to understand the purchase behaviour of e-grocery shoppers of India and to examine the association between satisfactions with online purchase, trust on online grocers, perceived risk and online repurchase intention of grocery items. The study uses primary data collected from 555 online grocery buyers. The findings of the study indicate that online customer satisfaction is a significant factor that influences repurchase intentions of online grocery shopping. Perceived risk negatively influence trust as well as repurchase intentions. Trust is found to be a mediating factor between shopping satisfaction and repurchase intentions. The study also builds and tests an online customer behavioural model with actual purchasing behaviour and identifies the continued presence of perceived risk, shopping satisfaction and trust in grocery e-retailing. 2023 IMI. -
Improved Random Forest Algorithm for Cognitive Radio Networks' Distributed Channel and Resource Allocation Performance
Modified Random Forest (MRF) machine learning algorithm aimed at improving the distributed channel allocation and resource allocation performance in cognitive radio networks (CRNs). The purpose of this research is to enhance the efficiency and effectiveness of CRNs by optimizing the allocation of channels and resources. The proposed MRF algorithm is developed by adapting and modifying the random forest technique to address the specific challenges of CRN allocation. Experimental evaluations demonstrate that the MRF algorithm achieves higher accuracy and efficiency compared to existing routing techniques and channel allocation algorithms like ACO and PSO. It exhibits a high packet delivery ratio, increased throughput, and reduced delay in channel selection, thus improving the overall performance of CRNs.The implications of this research are twofold. On a theoretical level, this study contributes to the field by extending the capabilities of the random forest algorithm and adapting it to the domain of CRNs. The modified algorithm demonstrates the potential of machine learning techniques in addressing allocation challenges in wireless communication systems. The findings emphasize the importance of advanced algorithms in improving the efficiency and effectiveness of channel and resource allocation processes. 2023, Success Culture Press. All rights reserved. -
RIEMANN SOLITONS ON (?,?)-ALMOST COSYMPLECTIC MANIFOLDS
In this paper, we study almost cosymplectic manifolds with nullity distributions admitting Riemann solitons and gradient almost Riemann solitons. First, we consider Riemann soliton on (?,?)-almost cosymplectic manifold M with ? < 0 and we show that the soliton is expanding with (Formula Presented) and M is locally isometric to the Lie group G?. Finally, we prove the non-existence of gradient almost Riemann soliton on a (?,?)-almost cosymplectic manifold of dimension greater than 3 with ? < 0. 2023 Korean Mathematical Society -
Efficient Ultra Wideband Radar Based Non Invasive Early Breast Cancer Detection
Ultra Wideband radar systems have emerged as a good alternative for non-invasive and harmless breast cancer detection. In this paper, bistatic and monostatic radar systems are proposed, which detects the deep-rooted and smallest formation of the tumor in the breast. The source signal for transmission through the breast is a seventh derivative Gaussian Ultra Wideband pulse. This pulse is shaped using the proposed sharp transition bandpass Finite Impulse Response filter. The pulse shaper filter design has a sharp transition, hence efficient for shaping very short-duration pulses, achieving higher data rate and less interference issues. Also, the pulse tightly fits the Federal Communication Commission spectral mask, thus achieving higher spectral utilization efficiency and meeting the signal safety standards for transmission through the breast. The shaped pulse fed to the antenna of the radar system provides higher antenna radiation efficiency and radiating power due to the concentration of power in the main lobe, sidelobe suppression, and less channel loss. Tumor detection is based on the time and frequency domain analysis of the backscattered signals from the tumor. These signals have higher amplitude, higher electric field intensity variations, and an increase in the scattering parameter values due to the presence of tumor. Simulation results show significant changes in the electric field intensity for normal and malignant breast tissue for tumor sizes ranging from 4 mm to 0.5 mm. To accurately detect the location of tumor inside the breast, Specific Absorption Rate (SAR) analysis is carried out. It is observed that the energy absorption in the cancerous breast is higher than that of the normal breast, thereby aids to detect the location of the tumor accurately by identifying the coordinates of the maximum value of SAR. The results obtained with an experimental setup consisting of fabricated heterogeneous breast phantom with tumor and monostatic radar closely confirms with the simulation results. 2013 IEEE. -
Cooperation affects NGO staff performance patterns
In order to optimise employee productivity and overall profitability, non-profits must invest heavily in their human resources. Contrarily, the focus of this study will be on the value of cooperation and the strategies the non-governmental organisation (NGO) should use to improve the performance of the bank as a whole. Once the data have been collected using quantitative and qualitative techniques, SPSS descriptive statistics will be utilised to maintain the findings and support the research hypothesis. According to the study, qualities like trust, camaraderie, job happiness, and benefits directly impact employees productivity at the bank. The degree of teamwork among co-workers directly affects how productive an employee is. Using the statistical program SPSS, managers and staff of NGOs were surveyed; the results revealed a favourable correlation between employee performance and NGO cooperation. When employees cooperate at work, their productivity increases, and the efficacy of the organisations they work for rises. Good news for charitable organisations. Because of this, the collaborative NGO outperforms the non-collaborative NGO in terms of productivity. It was found that better communication results in greater cooperation amongst NGOs. Copyright 2023 Inderscience Enterprises Ltd. -
PROTECTING DATA AND PRIVACY: CLOUD-BASED SOLUTIONS FOR INTELLIGENT TRANSPORTATION APPLICATIONS
The interaction between transportation networks and intelligent transportation systems has been revolutionized by cloud computing. However, the reliance on cloud-based solutions raises security and privacy concerns. This article examines the challenges of safeguarding data and privacy in intelligent transportation applications and emphasizes the potential of cloud-based solutions to resolve these issues. Organizations can protect sensitive data and user privacy by employing encryption, access controls, threat detection mechanisms, and privacy protection measures. Adopting these cloud-based solutions will encourage the extensive adoption of intelligent transportation applications while infusing users and stakeholders with confidence. 2023 SCPE. -
Mathematical Modeling for Evaluating the Mechanical Properties of High Strength Concrete with Natural Zeolite and Additives
The cement manufacturing industry is a major contributor to atmospheric pollution, primarily due to carbon dioxide emissions. Consequently, there is a pressing need to develop eco-friendly concrete capable of mitigating air pollution by sequestering atmospheric carbon dioxide. In this context, the incorporation of Natural Zeolite in concrete has been investigated, as it can absorb environmental carbon dioxide. This study explored the effects of partial cement replacement with Natural Zeolite (5%) and varying percentages of Silica Fume, Metakaolin, and Fly Ash (5%, 10%, and 15%) on the mechanical properties and carbon sequestration potential of High Strength Concrete (HSC). Comprehensive testing was conducted to evaluate the split tensile, compressive, and flexural strengths of the modified HSC. Experimental results indicated that the addition of Natural Zeolite and Metakaolin enhanced the strength of HSC, with Mix 3 displaying a higher 90-day compressive strength compared to the reference mix. The findings suggest that incorporating Natural Zeolite and other supplementary cementitious materials in concrete has the potential to alleviate environmental pollution. The dataset, comprising 900 samples, exhibited no autocorrelation or multicollinearity issues, making it suitable for multiple regression analysis. The statistically significant regression models developed in this study can effectively predict concrete strength. (2023). All Rights Reserved. -
Text summarization using residual-based temporal attention convolutional neural network
To address the computational complexity and limited to large data Enhanced Residual based Temporal Attention Convolutional Neural Network (ERTACNN) with Improved Initialization strategy-based Aquila Optimization Algorithm (IIAOA) is proposed. Initially the document is pre-processed to get structured data and given to feature extraction. Then the features are selected with Aquila Optimization Algorithm to remove redundant or unrelated features from high-dimensional data, from which the entropy values are calculated and given to proposed classifier. In this classification, the temporal attention mechanism is combined with classifier to compute attention weight and accompanied with important time points for classifying the documents. Finally, the proposed method is implemented in python and evaluated against existing works which achieves 70.34, 55.6 and 72.4 Recall Oriented Understudy for Gisting Evaluation (ROUGE) score than existing approaches. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
The Illiberal turn in Indian democracy: shifting the trajectory of Indias foreign policy
Long-standing democracies such as India were not exempt from the global trend of democratic retreat. India has come under increasing international attention due to certain domestic policies such as the revocation of Article 370 of the Indian Constitution, the National Register of Citizens and Citizenship (Amendment) Act passed under the Bharatiya Janata Party government. In addition to Indias democratic decline being reflected in global democratic rankings, this has induced strains on Indias foreign relations. In its pursuit of becoming a leading power, Indias perceived democratic backsliding is likely to influence the direction of its foreign policy. To discern the impact of its perceived illiberal turn on its foreign engagement, the role of democracy in Indias foreign policy needs to be explored. While attempts have been made to understand democratic backsliding through a theoretical lens, the impact of a nations democratic status on its foreign relations and policy remains a largely unexplored area. 2023 Taylor & Francis. -
The role of guilt-shame proneness and locus of control in predicting moral injury among healthcare professionals
Despite the advances in studies conducted among healthcare professionals to explore the impact of the pandemic on their mental health, a large population still continues to display COVID-19 related psychological complaints. There has been recent awareness of moral injury related guilt and shame among doctors and nurses. However, the factors associated with moral injury have not received much attention, due to which the issue still persists. This study aims to explore the role of guilt-shame proneness, and locus of control in predicting moral injury among healthcare professionals. MISS-HP, PGI Locus of Control, and GASP scales were administered to a sample of 806 healthcare professionals. Pearson correlation coefficient indicated a significant positive relationship between moral injury and guilt-shame proneness, as well as the locus of control. Regression analysis indicated a significant role of guilt-shame proneness and locus of control in predicting moral injury. In conclusion, while studying moral injury, it becomes equally important to consider these factors to understand the concept better. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Reaction of Indian Stock Market to Outbreak of COVID-19: An Empirical Analysis of Extreme Inter-day Movements
The contagious COVID-19 pandemic has been considered a massive global crisis since World War II and has disturbed business and economic activities across the globe. The current study examined the reaction of the stock markets to the outbreak of COVID-19, considering the extreme inter-day movements in the Indian stock market. The extreme inter-day movements in S&P CNX Nifty-50 have been identified during the study period from January 2020 to December 2021 and further classified into decline and gain events based on positive and negative announcements related to COVID-19. The study utilized an event study approach and panel regression for empirical investigation. The results of the event study analysis illustrate that the significant abnormal loss ranges from 12.86% to 2.47% for the major decline events and significant abnormal return from 8.43% to 3.23% for the gain events. The regression analysis results showed that real return and Central Bank Policy rate have a considerable impact on the abnormal returns during COVID-19. The studys findings are helpful to policy implications that identified the need to focus on financial education and strengthen the health and finance-related policies to deal with such pandemics in the future. 2023 MDI.