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Perceived Discrimination of Old Settlers in Sikkim
The old settlers in Sikkim are a community of mainland Indians whose ancestors had settled at least 15 years before the merger with India in 1975. At present, the total population of the community is less than three thousand individuals, comprising various ethnicities. This qualitative study focuses on the perceived discrimination of the old settlers, who form a demographic minority in the state. Data was collected using telephonic interviews from a sample of 11 old settlers. Thematic analysis indicated racial differences between the northeasterner indigenous community and mainland Indian old settlers as a major reason for perceived discrimination. The participants expressed the experience of negative emotional reactions, such as anger and disappointment, when they faced discrimination. The participants also felt betrayed by the government of India because they did not receive adequate protection for their rights when their identity in Sikkim changed from foreigners to citizens. Reactions to discrimination included migrating out of the state, experiencing negative emotions such as anger, disappointment and fear, and learned helplessness. 2022 Bhasker Malu, Santhosh Kareepadath Rajan, Nikhita Jindal, Aishwarya Thakur, Tanvi Raghuram. -
Regarding Deeper Properties of the Fractional Order Kundu-Eckhaus Equation and Massive Thirring Model
In this paper, the fractional natural decomposition method (FNDM) is employed to find the solution for the Kundu-Eckhaus equation and coupled fractional differential equations describing the massive Thirring model. The massive Thirring model consists of a system of two nonlinear complex differential equations, and it plays a dynamic role in quantum field theory. The fractional derivative is considered in the Caputo sense, and the projected algorithm is a graceful mixture of Adomian decomposition scheme with natural transform technique. In order to illustrate and validate the efficiency of the future technique, we analyzed projected phenomena in terms of fractional order. Moreover, the behaviour of the obtained solution has been captured for diverse fractional order. The obtained results elucidate that the projected technique is easy to implement and very effective to analyze the behaviour of complex nonlinear differential equations of fractional order arising in the connected areas of science and engineering. 2022 Tech Science Press. All rights reserved. -
Irrigation water policies for sustainable groundwater management in irrigated northwestern plains of India
Increasing global water shortage emphasizes the need for demand-side water management policies, especially in the agriculture sector, being the largest consumer of freshwater. Such policies are relevant in India, where groundwater depletion may have severe implications at various socio-economic levels. In this study, using mathe-matical modelling, we assess the feasibility of two alter-native irrigation water pricing policies (i) uniform wa-ter pricing policy and (ii) differentiated water pricing policy, wherein farmers growing less water-requiring crops (<4488 m3/ha) get an incentive for saving water, while those growing water-intensive crops pay for it. Us-ing a case study of Punjab, the breadbasket and one of the fastest groundwater-depleting states in India, alter-native cropping patterns are also suggested. The findings reveal that the current rate of groundwater withdrawal could not sustain agricultural intensification in the state. Although optimization of resource allocation has the pote-ntial to save water by 8%, this alone is unlikely to break the ricewheat mono-cropping pattern in Punjab. The analysis of two different volumetric irrigation water pricing policies shows that differentiated water pricing would be more effective in halting groundwater deple-tion in the state. However, adequate investment in irri-gation water supply infrastructure, mainly for installing water meters, is required to implement the policy. 2022, Current Science. All Rights Reserved. -
AGGRESSION AS A PREDICTOR OF GENERAL WELL-BEING AMONG PUBLIC HEALTH WORKERS
Social atrocities and discrimination make sanitary workers vulnerable to aggression which in turn disrupts their well-being. The issues concerning the psychological health of sanitary workers have been addressed less by researchers. The present study aimed to assess the level of aggression and general well-being among sanitary workers. An aggression questionnaire, consisting of four dimensions, namely physical aggression, verbal aggression, anger and hostility was used. The PGI general well-being measure and personal profile sheet consisting of socio-demographic details was given to 150 sanitary workers who were selected through purposive sampling method. The dimensions of aggression- anger and hostility were negatively correlated with the general well-being of the participants. Amongst the four dimensions of aggression, anger is found to be the predictor of general well-being. 2022 Australasian College of Health Service Management. All right reserved. -
Efficient detection of faults and false data injection attacks in smart grid using a reconfigurable Kalman filter
The distribution denial of service (DDoS) attack, fault data injection attack (FDIA) and random attack is reduced. The monitoring and security of smart grid systems are improved using reconfigurable Kalman filter. Methods: A sinusoidal voltage signal with random Gaussian noise is applied to the Reconfigurable Euclidean detector (RED) evaluator. The MATLAB function randn() has been used to produce sequence distribution channel noise with mean value zero to analysed the amplitude variation with respect to evolution state variable. The detector noise rate is analysed with respect to threshold. The detection rate of various attacks such as DDOS, Random and false data injection attacks is also analysed. The proposed mathematical model is effectively reconstructed to frame the original sinusoidal signal from the evaluator state variable using reconfigurable Euclidean detectors. 2022, Institute of Advanced Engineering and Science. All rights reserved. -
Blockchain Technology in the Fashion Industry: Virtual Propinquity to Business
The concept of fashion has been coupled with technology, where technology has become the protagonist. The transparency between an organization and a customer works as a catalyst, and the customer has taken a more mainstream role. With blockchain technology, companies can reconnect with customers and customers can track the journey of a product from its raw materials to the finished goods. The primary focus of the study is on services and data collected from the following sectors, namely fashion, apparel, and online platforms. The authors main goals are (1) to illustrate an overview of how big data is transforming the service industry, especially the fashion and design sector, and (2) to present various mechanisms adopted in the service industry. The study aims to investigate a model that fits through EXT-TAM and uses additional attributes of blockchain technology with a special reference to fashion apparel. The findings of this study depict a model, where PEOU, PU, and attitude are the major constructs and present a win-win scenario for both the customer and the organization. 2022 Authors. All rights reserved. -
Impact of Brexit on bond yields and volatility spillover across France, Germany, UK, USA, and India's debt markets
Britain's decision to exit the EU lead to disruptions in global markets. This study investigates the change in the return and volatility spillover pattern due to the repercussions of the Brexit vote between the US, France, the UK, Germany, and India's 10-year government bond yields by applying the VAR and GARCH-BEKK models. The findings demonstrate a substantial rise in the return spillover to India and USA 10-year government bond yields following the Brexit vote compared to the pre-Brexit vote era. In addition, the results showed evidence of unidirectional volatility spillover from India to France, bidirectional volatility spillover between the USA and India, and unidirectional volatility spillover from the UK to India 10-year government bond market post-Brexit vote. However, there was no interconnection between these markets before the Brexit vote. Therefore, the Brexit vote did affect and significantly increased the linkage between the US, France, the UK, and India's 10-year government bond market. The increase in correlation in India-US, India-UK, and India-France's 10-year government bond markets will help predict and have an important implication for hedgers, decision-makers, and portfolio managers if similar political events occur in the future. Sangeetha G. Nagarakatte, Natchimuthu Natchimuthu, 2022. -
Distillery effluent valorization through cost effective production of polyhydroxyalkanoate: optimization and characterization
The devastating effect of fossil plastics in the biosphere has tuned the concern for bioplastic production in the last few decades. Polyhydroxyalkanoate, a biopolyester, has a wide range of applications as they impose positive societal impact by being biodegradable and void of any ill-effects when used in vivo. Despite their eco-friendly nature, the outreach of PHA is bounded in industrial scale as the overall expense is highly comparable to conventional plastics. Therefore, in an attempt to attain a feasible production, the present study aims at utilizing raw distillery effluent for PHA production using Bacillus subtilis NCDC 0671. Different dilutions of spent wash (5%, 10%, 15%, and 20%) were assessed for PHA production in the modified medium among which 10% showed maximum PHA accumulation. Furthermore, statistical optimization by response surface methodology enhanced PHA synthesis to 6.3g/L which is 3.3-fold increases. FTIR and NMR characterization of the biopolymer from the optimized medium was similar to the previous literature which provides a promising approach for cost effective production. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
COVID-19 pandemic and preparedness of teachers for online synchronous classes
COVID-19 pandemic has forced educational institutes to shut down, and teachers are compelled to adopt technology ardently so that the teaching-learning process does not suffer. Gradually, it is being realised that synchronous online classes are required to enhance the teaching-learning experience. The major challenge in India is the lack of preparedness of the teachers, as most teachers have little experience with technology. Nevertheless, they have to adapt themselves quickly. However, to effectively use technology for synchronous online teaching, teachers have to be technology ready and proficient with utilising the platform used for online classes. This study attempts to understand the impact of teachers preparedness on the use of online platforms for synchronous teaching during the COVID-19 pandemic. This paper integrates the technology readiness index (TRI) and technology acceptance model (TAM), also known as the TR and acceptance model (TRAM), to investigate the phenomenon mentioned above. Copyright 2022 Inderscience Enterprises Ltd. -
Animal-Assisted Therapy for the Promotion of Social Competence: a Conceptual Framework
Developmental disorders have a substantial effect on the social competence of children affecting their overall psychosocial functioning. Social competence entails the process of being socially mature by establishing stable and adaptive patterns of social behavior. Animal-assisted therapy, as an alternative treatment modality, has offered some new prospects for improving social cognition. This conceptual paper, thus, attempts to throw light on how animal-assisted therapy can help improve social competence. The paper draws its knowledge from the existing theories and empirical work done to propose a conceptual framework that can enhance social competence by incorporating therapy animals. It can be concluded that animal-assisted therapy has found to improve different dimensions crucial for development of social competence. This further suggests the dire need to explore the effectiveness of human-animal interactions by utilizing it for improving social competence. 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Is Industry-Specific Value Premium Declining? Evidence from India
This article examines whether the literature promised value effect exists and the changing nature of value premium at the industry level. It also determines the value premiums strength by controlling the January effect within and across the regulated industry groups. This is done by utilizing the two most prominent pricing models: FamaFrench three- and five-factor, considering all listed firms trading at BSE India between 1999 and 2020. The results show that a significant value effect exists in 15 of the 17 regulated industry groups over 21.5 years, while sub-period analysis revealed variation in the value effect at industry-based portfolio returns. We developed quintile and multivariate portfolios within and across the industries. Results show that the industry-specific value premium has been relatively low in the current decade due to decreasing industry portfolio returns and increasing P/B ratios within industry groups. The study also used the GRS test to explore the explanatory power of models. Results indicated that the explanatory power of models has declined in post-crisis periods. While controlling the January effect, the value premium has slightly diminished within and across the industry groups in the recent decade. We also observed that investors who seek to allocate assets within and across industries are likely to have potentially predictable and pretty stable returns. While other countries have found industry-specific value premiums, no such study has been conducted in India. As a first attempt, these findings are relevant for investors and academia. 2022 Management Development Institute. -
Development of an Efficient and Secured E-Voting Mobile Application Using Android
Smart technologies, particularly the development of the Internet, are employed to enhance the quality of human existence. Thanks to the Internet's explosive expansion, more and more tasks can now be completed quickly and easily compared to the earlier times. E-voting is a relatively recent field that has been identified. Voting can be conducted in a variety of methods, including in person at a polling place, online, and via a mobile application. The security of applications cannot be disregarded given the internet's explosive growth. In order to prevent phishing attacks, we created an Android application and included a 3-step security process before voting. Students can now vote online from any location at any time using a mobile device. Android Studio is used to create and deploy the application. While creating the voting application, this research adheres to the software development life cycle. The result of this research is the creation of a mobile application that is user-friendly for students and serves as a practical tool for letting them vote with three levels of security. 2022 Anli Sherine et al. -
Improved Henon Chaotic Map-based Progressive Block-based visual cryptography strategy for securing sensitive data in a cloud EHR system
The core objective of secret sharing concentrates on developing a novel technique that prevents the destruction and leakage of original data during the distribution and encoding processes. Progressive Visual Cryptography (VC) is considered for the potential over the traditional VC schemes since the former does not require and does not suffer from the limitations of requiring a minimum number of participants during the process of encryption and sharing. The chaotic map-based Progressive VC is superior in facilitating predominant secrecy under sharing and encryption. In this paper, an Improved Henon Chaotic Map-based Progressive Block-based VC (IHCMPBVC) scheme is proposed to prevent the leakage and destruction of sensitive information during an exchange and encryption. This proposed IHCMPBVC technique uses the merits of Henon and Lorentz maps for effective encryption since it introduces the option of deriving non-linear behavior that results in sequence generation that covers the complete range with proper distribution in order to minimize the degree of leaks in sharing. The simulation results of the proposed IHCMPBVC technique investigated using entropy, PSNR, and Mean Square Error were improved at an average rate of 27%, 23%, and 31%, predominant to the baseline VC approaches considered in the comparison. 2022 The Authors -
The linkage between green banking practices and green loyalty: A customer perspective
The aim of this study is to explore the bank customers perceptions towards green banking practices. This study uses a convenient sampling method. Pre-tested questionnaires were employed to collect data. The data were collected conveniently from 358 bank customers. However, the final sample includes 304 responses after ignoring null responses (n = 304). The Structural equation modeling (SEM) was applied for the analyses. The significant results of the study indicate that green banking practices positively influence green image (p = 0.001) and green trust (p = 0.025), while it does not significantly affect green loyalty (p = 0.642). The mediation analysis reveals that green image mediates the relationship between green banking practices and green loyalty, while green trust does not mediate the relationship between the same. The results have practical implications for banking institutions in India to recognize the importance of environmental initiatives in influencing the decisions of bank customers. Deepthi S. Pawar, Jothi Munuswamy, 2022. -
Investigating the Impact of Emotional Contagion on Customer Attitude, Trust and Brand Engagement: A Social Commerce Perspective
Social Commerce networks are a powerful platform for spreading positive and negative emotional contagion, which is affecting users from different perspectives, i.e., psychology, attitude, buying decision. Emotional contagion is the phenomenon of having a person's emotions and behaviours directly trigger similar emotions or behaviour in other people. This research proposes a model to analyze the factors influencing emotional contagion that, in turn, impact consumer's attitudes, trust, and brand engagement. This study used a survey approach using a structured questionnaire. Primary data was collected from 174 social media users who shop online. The proposed model was tested using multiple regression analysis. The results demonstrated that effective content, visual or text, triggers customers' emotional contagion, influencing customer attitude and trust leading to brand engagement. The research study's findings can be used for deciding on content strategies of advertisements pertaining to social commerce. 2022 Academy of Taiwan Information Systems Research. All rights reserved. -
Sustainable Computing: A Determinant of Industry 4.0 for Sustainable Information Society
Rapid advancement in technology and continuous environmental degradation have attracted the attention of practitioners toward sustainable solutions. This study intends to promote Industry 4.0 information society research by comprehending sustainable ICT adoption in businesses to promote sustainable information society (SIS). Further, it extends the theory of planned behavior model and deploys a quantitative research approach. The findings from PLS-SEM confirm the perceived environmental responsibility (PER), a precursor for attitude (ATT), perceived behavioural control (PBC), and subjective norm (SN). Further, there is a significant positive influence of ATT, PBC, and SN on the adoption intention of sustainable ICT practices followed by the effect of adoption intention on sustainable information society (SIS). This study bridges the literature gap through a novel attitude behavior gap model and provides a possible understanding of how businesses might contribute to the creation of sustainable development and information society. 2022 Nishant Kumar et al. -
Seasonal Variation of Physicochemical Parameters and Their Impact on the Algal Flora of Chimmony Wildlife Sanctuary
Background and Objective: The lack of biodiversity knowledge and biodiversity loss are the two inevitable truths around us. Algae are the most crucial organism in our entire biodiversity. The seasonal variation of algal diversity can monitor the environmental changes of the freshwater ecosystem. The present study was conducted because the seasonal changes of algal diversity in Chimmony Wildlife Sanctuary were utterly unknown. Materials and Methods: The algal samples were collected and preserved from ten stations for three seasons (pre-monsoon, monsoon, post-monsoon). The physicochemical parameters of water like temperature, pH, total dissolved solids, total dissolved oxygen, total alkalinity and light intensity of the sampling stations were recorded. Results: The study revealed that the seasonal variation of physicochemical parameters provoked a change in the diversity of Algae. The Chimmony Wildlife Sanctuary has its highest algal diversity during pre-monsoon season. The Chlorophyceae Algae were dominant during the pre-monsoon season, while the Cyanophycean Algae were dominant during monsoon season. The ANOVA (two-way) analysis showed no significant difference between stations and there is a considerable difference between seasons for dissolved oxygen, alkalinity, temperature and total dissolved solids. While for pH, it showed no significant difference between seasons and stations but for light intensity, it showed a substantial difference between stations and seasons. A negative correlation was observed between algal species and seasons. The temperature and dissolved oxygen showed a negative correlation. Conclusion: The physicochemical parameters were changed according to the seasonal variation. Since Algae act as a biological pollution indicator for all the water resources, the study of algal flora according to the seasonal variation is crucial. 2022 Joel Jose and Jobi Xavier. -
A sustainable approach for fish waste valorization through polyhydroxyalkanoate production by Bacillus megaterium NCDC0679 and its optimization studies
Polyhydroxyalkanoates (PHAs) are considered as the only class of truly biodegradable and biocompatible polymers. Although extensive research has been carried out in producing them from a wide variety of organisms, their commercialization still faces hurdles majorly associated with the cost of production media. This research work exploits the use of discarded fish scale waste as a major media component for biopolymer production. The major novelty of the research work is the utilization of a Bacillus megaterium NCDC0679 for PHA production using fish scale waste that is not reported previously. Furthermore, a sequential and systematic statistical optimization strategy employing response surface methodology was used to trace out the level of the most significant variables and their interaction effects on PHA production add to the significant novelty of this work. The significance of the model developed was determined from the p values of ANOVA. Under optimized levels of glucose (50g/L), NaCl (0.125g/L), and fish scale hydrolysate concentration (62.5% v/v), maximum PHA yield of 6.33g/L was achieved in the shake flask culture system. This was found to be 5.50-fold higher than the unoptimized medium. The ANOVA results established the significance of the model (p < 0.05). The extracted polymer was characterized through Fourier-transform infrared (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Thus, the present investigation suggests an innovative method for valorization of fish scale waste for commercial production of PHA. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
A Malicious Botnet Traffic Detection Using Machine Learning
Detection of incorrect and malign data transfers in the Internet of Things (IoT) network is important for IoT safety to observe an eye on and prevent unwelcomed traffic flow to the network of IoT. For it, Machine Learning (ML) strategic methods are produced by several researchers to prevent malign data flows through the network of IoT. Nonetheless, because of the wrong choice of feature, a few malign Machine Learning models differentiate especially the movement of malign traffic. Still, what matters is the problem that needs to be deliberated in-depth to select the best features for better malign traffic acquisition in the network of IoT. Dealing with the challenge, a new process was proposed. 1st, the metric method of selecting a novel feature called the proposed CorrAUC, and hinged on CorrAUC, a new highlight for choosing the Corrauc algorithm name is also being developed, designed hinged on the system folding filter features precisely and select the active features of the choose ML method using AUC metric. After that, we apply a combined application Order of Preference by Similarity to Ideal Solution Using Shannon Entropy (TOPSIS) built on a bijective set which is soft to verify selected features for identification of malign 1traffic in IoT network. We test our method using data set of Bot-IoT and 4 dissimilar ML classifiers. Practical outcomeanalysis showed that our proposed approach works as well and can achieve greater than 96% results on average. 2022 Wolters Kluwer Medknow Publications. All rights reserved. -
Flexible and cost-effective cryptographic encryption algorithm for securing unencrypted database files at rest and in transit
To prevent unauthorized access to the databases and to ensure that the data of the databases is protected from intruders and insiders, the data is being encrypted at the storage locations. The same goal is achieved with Transparent Data Encryption, a feature that can be found in almost all database products. However, it has been observed that the non-datafiles are being ignored and there is no standard encryption for them like there is for datafiles. Moreover, there was no standard algorithm to encrypt them without relying on third-party tools. Therefore, This study provides a robust algorithm to perform the encryption. This presentation also describes the importance of non-datafiles encryption, and how some non-datafiles can pose a threat to data and infrastructure without encryption. The practical implementation of the non-data file encryption algorithm shows the authentic results. Further, unlike existing algorithms, the proposed algorithm gives the file owner full control over the encryption logic. In the encryption process, two levels of encryption logics are combined with a passcode lock, while the same combination of two levels of reversing encryption and passcode is used in the decryption process to convert encoded data back into text format. 2022 The Author(s)