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Management and Sales Forecasting of an E-commerce Information System Using Data Mining and Convolutional Neural Networks
The exponential development of e-commerce in recent decades has enhanced convenience for individuals. Compared to the conventional business environment, e-commerce is characterized by increased dynamism and complexity, resulting in several obstacles. Data mining assists individuals in effectively addressing these difficulties. Traditional data mining cannot efficiently use big data in the power provider industry. It heavily relies on time-consuming and labor-intensive feature engineering, and the resulting model could be more easily scalable. Convolutional Neural Networks (CNN) can efficiently use vast amounts of data and autonomously extract valuable elements from the original input, resulting in increased effectiveness. This article utilizes a CNN to extract valuable insights from e-commerce information to forecast commodities sales accurately and proposes a CNN-based Sales Forecasting Model (CNN-SFM). The findings indicate that using data mining and CNN yields a high level of precision in forecasting forthcoming people buying capacity data. The correlation variable between actual usage information and projected usage information was 0.98, and the highest mean error was just 1.78%. Data mining can effectively extract hidden relevant information and forecast future consumption habits for e-commerce systems. CNN demonstrates proficiency in accurately predicting forthcoming consumption power and trends. The Research Publication. -
Esther reimagined: feminist essence in Sara Josephs narrative
Gynocentric approaches to biblical women uncover narratives of liberation and empowerment. These perspectives highlight the gaps and omissions in the representation of women within the overarching metanarrative of the Bible. Sara Josephs novel, Esther, serves as a feminist reimagining of the biblical story of Esther, offering a pluralistic lens through which to examine the experiences and lives of women against the backdrop of patriarchy. This paper utilises the feminist hermeneutic method to critically engage with the narrative, drawing on the feminist frameworks established by scholars such as Elizabeth Fiorenza and Esther Fuchs. It argues that biblical women can be reinterpreted as positive role models, saviours, heroines, and vital contributors to an extraordinary narrative of survival and redemption. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Theoretical and experimental validation of thermal and heat transfer performance of novel ethylene glycol - Cr2AlC nanofluids
Synthesizing stable nanofluids with favourable thermal properties that can cater to practical applications is a challenge over the past few years. This paper presents the preparation and analyzes the thermal efficiency of the novel nanofluid prepared by the suspension of nanocrystalline Cr2AlC MAX phase powder in ethylene glycol (EG). Incorporation of h-BN, MoS2, Al2O3, and Cr2AlC showed a thermal conductivity enhancement at 303 K when compared to EG. Accurate experimental models for the thermal conductivity and the viscosity of EG + Cr2AlC nanofluids are estimated. The theoretical analysis of the flow profiles of EG + Cr2AlC/Al2O3/MoS2/h-BN nanofluids is carried out with Blasius and Sakiadis flow models. The Cr2AlC MAX phase possesses both ceramic and metal properties that help these nanofluids to show high heat transfer performance. The results show that 0.50 wt% EG + Cr2AlC nanofluid displays maximum improvement in heat transfer performance. There is a substantial rise in the thermal conductivity when both temperature and weight fraction increase. The simulated flow of the nanofluid past a plate indicated superior heat transfer and thermal profiles for the EG + Cr2AlC nanofluids. For the flow past a moving plate, the nanofluid possesses less skin friction at the plate, which is favourable for various practical applications. 2022 Elsevier Ltd -
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. -
Corporate Social Performance and Firm Location: Empirical Evidence
The study addresses the relationship between firm location and the corporate social performance (CSP) of manufacturing enterprises in India. The study argues that a higher number of multinational corporations (MNCs) at a location leads to higher social performance. An environment and social involvement (ESI) index, based on ISO26000 and National Voluntary Guidelines, has been used to measure the corporate social performance of manufacturing enterprises. The data are obtained through questionnaires from a survey of 121 medium-sized manufacturing enterprises in the national capital region in India and analyzed through one-way ANOVA and linear regression. Results reveal that the presence of MNCs at the location of enterprises is significant to their CSP. The findings of the study aggregate to make original and substantive contributions to the CSP literature on the geography of strategic management. This research is valuable for social responsibility practitioners in developing countries for start-ups and small and medium enterprises who are seeking to enhance their understanding to formulate pragmatic and effective strategies to improve CSP. 2023 IGI Global. All rights reserved. -
Does Credit Rating Revisions Affect the Price of Common Stock: A Study of Indian Capital Market
The current investigation aims to assess the effect of credit assessment changes on the share prices of Indian companies from 2009 to 2019. The data of top 100 companies listed on National Stock Exchange (NSE) across 10 industries stem from CMIE databases. The excess stock return is compared with the market in a 15-day window around credit rating changes. The event effect on share prices is more in the pre-event window compared to the post-event window. Positive abnormal stock returns around upgrades through downgrades are statistically significant compared to upgrades. Credit ratings are not significant across industries, and agency nationality is a critical factor for calculating the intensity of price reaction. 2021 K. J. Somaiya Institute of Management. -
Corporate social responsibility: a cluster analysis of manufacturing firms in India
Purpose: This paper aims to identify the corporate social responsibility (CSR) patterns of Indian manufacturing firms using a CSR index based on ISO26000 and Indias National Voluntary CSR Guidelines. Design/methodology/approach: A total of 121 manufacturing enterprises in the national capital region (NCR) were surveyed. The questions related to the involvement of CSR in business strategy, involvement in CSR planning, involvement in environmental activities, involvement in social activities, monitoring, evaluation and involvement in CSR, reporting and policy and deployment of CSR. A two-step cluster analysis using log-likelihood measures was used to identify groupings in the data set based on their performance across the seven issues. Findings: The two distinctive segments identified adopted intermediate CSR activities, and one undertook advanced CSR activities. Research limitations/implications: This study has several limitations. First, the survey data were drawn exclusively from medium-sized enterprises in the NCR. Second, all the indicators in the CSR index were equally weighted. Originality/value: This paper contributes to the literature by grouping manufacturers CSR activities based on seven dimensions suggested in ISO26000 and Indias National Voluntary Guidelines. The results of this study can help managers, boards and regulators better understand CSR and identify ways to improve it further. 2023, Emerald Publishing Limited. -
Barriers to corporate social responsibility implementation in the medium size manufacturing sector: an interpretive structure modelling approach
Purpose: Corporate social responsibility (CSR) practices are gaining momentum globally but their implementation becomes problematic due to the presence of barriers. So, this study aims to identify the barriers to CSR implementation among manufacturing enterprises, develop their classification and establish relationships among the barriers. Design/methodology/approach: An exhaustive list of barriers was identified from the literature, and following surveys and expert opinions, 19 critical barriers were extracted. Interpretive structure modelling was used to understand the hierarchal and contextual relationships among barriers of CSR implementation. Findings: The results show that are no autonomous variables present in the study. The proposed conceptual framework presents the hierarchy and interlinkage of barriers to CSR implementation in manufacturing enterprises. The results also indicate that rigidity in culture and corruption in the system and within the governance system of the country are the two most influential barriers that impede CSR implementation in manufacturing enterprises. Originality/value: The interactions among CSR barriers provide policymakers, industrial practitioners and managers with a framework to recognise and evaluate mutual relationships and interlinking among barriers. CSR training and undertaking CSR in collaboration can help medium enterprises overcome these barriers and prepare strategies to mitigate their impact. 2021, Emerald Publishing Limited. -
How Can Small and Medium Enterprises Effectively Implement Corporate Social Responsibility?: An Indian Perspective
The current study is a strategic approach to corporate social responsibility (CSR); the aim is to put forward the factors of CSR activities that enhance its effectiveness for small and medium enterprises (SMEs). To achieve this objective, the factors were extracted from the literature and described along with trusteeship theory of Mahatma Gandhi, and an exploratory study was conducted and data were collected using structured questionnaire based on pretested scale from 158 SMEs and tested using partial least square regression (PLSR). The statistics shows the overall model fit, and the findings indicate a significant relationship with effective CSR. The results of the study are in accordance with the previous research work, and we also find that environment-related CSR and partnership are crucial for the effectiveness of CSR in SMEs, stakeholders role are important and SMEs CSR practice is still informal. The variables identified from study will help SMEs in establishing a formal approach towards CSR and meeting the needs of business and society in the twenty-first century. 2019 International Management Institute, New Delhi. -
Promoting Sustainability Through Corporate Social Responsibility: Insights and Barriers of Medium-Sized Manufacturing Enterprises in India
The current study aims to explore if effective corporate social responsibility leads to corporate sustainability in medium-sized manufacturing enterprises. Using the factors, an exploratory examination was performed to assess their suitability in Indian context, and data were collected from 121 manufacturing companies using structured questionnaire based on pretested scale, and the proposed relationships were tested through partial least square structural equation modelling (PLS-SEM). The results show overall model fit and empirical examinations support causal relationships between effective corporate social responsibility and corporate sustainability (CS). The results indicated that effective CSR mediated the relationships between corporate sustainability and integration of CSR into corporate policy and priority of the board towards CSR. The results of this study are useful for medium-sized enterprises to establish a formal approach towards CSR and meet the needs of business and society in the 21st century. Copyright 2022, IGI Global. -
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. -
A Representation-Based Query Strategy to Derive Qualitative Features for Improved Churn Prediction
The effectiveness of any Machine Learning process depends on the accuracy of annotated data that is used to train a learner. However, manual annotation is expensive. Hence, researchers adopt a semi-supervised approach called active learning that aims to achieve state-of-the-art performance using minimal number of samples. Although it boosts classifier performance, the underlying query strategies are unable to eliminate redundancy in selected samples. Redundant samples lead to increased cost and sub-optimal performance of learner. Inspired by this challenge, the study proposes a new representation-based query strategy that selects highly informative and representative subsets of samples for manual annotation. Data comprises messages of a set of customers sent to a service provider. Series of experiments are conducted to analyze the effectiveness of the proposed query strategy, called 'Entropy-based Min Max Similarity' (E-MMSIM), in the context of topic classification for churn prediction. The foundation of E-MMSIM is an algorithm that is popularly used to sequence proteins in protein databases. The algorithm is modified and utilized to select the most representative and informative samples. The performance is evaluated using F1-score, AUC and accuracy. It is observed that 'E-MMSIM' outperforms popular query strategies, and improves performance of topic classifiers for each of the 4 topics of churn prediction. The trained topic classifiers are used to derive qualitative features. These features are further integrated with structured variables for the same group of customers to predict churn. Experiments provide evidence that inclusion of qualitative features derived using E-MMSIM, enhance the performance of churn classifiers by 5%. 2013 IEEE. -
Predicting customer churn: A systematic literature review
Churn prediction is an active topic for research and machine learning approaches have made significant contributions in this domain. Models built to address customer churn, aim to identify customers who are at a high risk of terminating services offered by a company. Hence, an effective machine learning model indirectly contributes to the revenue growth of an organization, by identifying at risk customers, well in advance. This improves the success rate of retention campaigns and reduces costs associated with churn. The aim of this study is to explore the state-of-the-art machine learning techniques used in churn prediction. A systematic literature review, that is driven by 5 research questions and rigorous quality assessment criteria, is presented. There are 38 primary studies that are selected out of 420 studies published between 2018 and 2021. The review identifies popular machine learning techniques used in churn prediction and provides directions for future research. Firstly, the study finds that churn models lack generalization capability across industry domains. Hence, it identifies a need for researchers to explore techniques that extend beyond model experimentation, to improve efficiency of classifiers across domains. Secondly, it is observed that the traditional approaches to churn prediction depend significantly on demographic, product-usage, and revenue features alone. However, recent papers have integrated social network analysis-related features in churn models and achieved satisfactory results. Furthermore, there is a lack of scientific work that utilizes information-rich content of customer-company-interaction instances via email, chat conversations and other means. This area is the least explored. Thirdly, there is scope to investigate the effect of hybrid sampling strategies on model performance. This has not been extensively evaluated in literature. Lastly, there is no formal guideline on correct evaluation parameters to be used for models applied on imbalanced churn datasets. This is a grey area that requires greater attention. 2022 Taru Publications. -
A Sampling-Based Stack Framework for Imbalanced Learning in Churn Prediction
Churn prediction is gaining popularity in the research community as a powerful paradigm that supports data-driven operational decisions. Datasets related to churn prediction are often skewed with imbalanced class distribution. Data-level solutions, like over-sampling and under-sampling, have been commonly used by researchers to address this problem. There are limited number of case studies that attempt to evolve these data-level solutions by integrating them with computationally advanced frameworks, like ensembles. Ensembles primarily employ algorithmic diversity using a fixed set of training instances to achieve superior performance. This study aims to introduce algorithmic diversity in ensembles by modifying the fixed set of training instances using diverse sampling strategies to increase predictive performance in imbalanced learning. Data is acquired from the world's largest open hotel commerce platform company. A four-part series of experiments is conducted to analyze the effectiveness of sampling techniques and ensemble solutions on model performance. A new sampling-based stack framework called 'Stacking of Samplers for Imbalanced Learning' is proposed. The framework combines the prediction capabilities of sampling solutions to stimulate the information gain of the meta features in ensemble. It is observed that the proposed framework leads to improvement in model performance with AUC of 86.4% and top-decile lift of 4.7 for customers of the hotel technology provider. Additionally, results show that the framework records a higher information gain for meta features used in a stack, compared to commonly used stack frameworks. 2013 IEEE. -
Resilience in Children from Different Socioeconomic Backgrounds: An Exploratory Study
Poverty, violence, substance abuse, family dissonance and illness represent a few potential vulnerabilities in the lives of children who are at risk of failing in their future prospects. It is thus essential to explore resilience in children, owing to the excess or deficit of exposure and access in a childs life. This study aims at exploring the resilience of children of the age group 710years, from different socioeconomic backgrounds. The socioeconomic status was determined using the Kuppuswamy socioeconomic scale and these children had parents with authoritarian and permissive parenting styles which were screened through the Parenting Styles and Dimensions Questionnaire which act as risk factors for the children. Data was collected through individual semi-structured interviews with the participants and was analysed using thematic analysis. For the lower socioeconomic status group, the main themes identified were social interaction and competence, overcoming distress and future focus, and for the upper socioeconomic status group, the main themes identified were social interaction and competence and emotional management. The study paves the way for further exploration of the impact of economic status on childrens wellbeing and might inform changes at a clinical, research and policy level. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
COVID-19 and stress of Indian youth: An association with background, on-line mode of teaching, resilience and hope
Background: COVID-19 pandemic causes serious threats to physical health and triggers wide varieties of psychological problems, including anxiety and depression. Youth exhibit a greater risk of developing psychological distress, especially during epidemics influencing their wellbeing. Objectives: To identify the relevant dimensions of psychological stress, mental health, hope and resilience and to examine the prevalence of stress in Indian youth and its relationship with socio-demographic information, online-mode of teaching, hope and resilience. Method: A cross-sectional online survey obtained information on socio-demographic background, online-mode of teaching, psychological stress, hope and resilience from the Indian youth. A Factor Analysis is also conducted on the recompenses of the Indian youth on psychological stress, mental health, hope and resilience separately to identify the major factors associated with parameters. The sample size in this study was 317, which is more than the required sample size (Tabachnik et al., 2001). Results: About 87% of the Indian youth perceived moderate to a high levels of psychological stress during the current COVID-19 pandemic. Different demographic, sociographic and psychographic segments were found to have high stress levels due to the pandemic, while psychological stress was found to be negatively correlated with resilience as well as hope. The findings identified significant dimensions of the stress caused by the pandemic and also identified the dimensions of mental health, resilience and hope among the study subjects. Conclusion: As stress has a long-term impact on human psychology and can disrupt the lives of people and as the findings suggest that the young population of the country have faced the greatest amount of stress during the pandemic, a greater need for mental health support is required to the young population, especially in post pandemic situations. The integration of online counselling and stress management programs could assist in mitigating the stress of youth involved in distance learning. 2023 The Author(s) -
A Cross-Sectional Study on Mental Health of School Students during the COVID-19 Pandemic in India
The broad objective of the present study is to assess the levels of anxiety and depression of school students during the COVID-19 lockdown phase and their association with students background, stress, concerns and social support. In this regard, the present study follows a novel two stage approach. In the first phase, an empirical survey was carried out, based on multivariate statistical analysis, wherein a group of 273 school students participated in the study voluntarily. In the second phase, a novel Picture Fuzzy FFA (PF-FFA) method was applied for understanding the dynamics of facilitating and prohibiting factors for three categories of focus groups (FG), formulated on the basis of attendance in online classes. Findings revealed a significant impact of anxiety and depression on mental health. Further, PF-FFA examinedthe impact of the driving forces that steered children to attend class as contrasted to the the impact of the restricting forces. 2022 by the authors. -
Cloud computing security for public cloud using ciphers and queueing petri nets
Cloud computing is the most used word in the domain of Information Technology, which is making colossal differentiations in the IT business. Nowadays, a massive proportion of data is being made, and the masters are discovering better approaches for managing this data. In a general sense, the word cloud implies a virtual database that stores immense data from various clients. There are three sorts of cloud public, private and hybrid. A public cloud is fundamental for general customers where customers can use cloud benefits free or by paying. Private cloud is for explicit associations, and hybrid one is in a broad sense a mix of both. Cloud offers diverse kind of administrations, for instance, IAAS, PAAS, SAAS where administrations like a stage for running any application, getting to the enormous information extra room, can use any application running under the cloud are given. The cloud similarly has a shortcoming concerning the security for the data warehouse. In a general sense, public cloud is inclined to data modification, data hacking and therefore, the integrity and privacy of the data are being undermined. Here in our work our motive is to verify the information that will be taken care of in the public cloud by using the multi-stage encryption. The estimation that we have proposed is a mix of Rail Fence cipher and Play Fair cipher. 2020, IJSTR. -
School corporal punishment, family tension, and students internalizing problems: Evidence from India
There is considerable evidence that parental corporal punishment (CP) is positively associated with childrens behavioral and mental health problems. However, there is very little evidence addressing whether CP perpetrated by teachers or school staff is similarly associated with problematic student functioning. To address this gap in the research literature, data were collected from students in a locale where school CP continues to be widely practiced. Participants were 519 adolescents attending public or private schools in Puducherry, a city in eastern India. Students completed surveys assessing school CP, internalizing problems, social support, and resilience. The results indicated that 62% of the students reported experiencing school CP in the past 12 months, with males and those attending public schools being significantly more likely to report school CP than females and those in private schools. Youth who reported school CP reported more anxiety and depression. That relation was more pronounced in youth who reported family tension. Social support and resilience did not moderate the relations. The findings add to the substantial evidence about negative associations regarding the use of CP but in a new venuethe school, and provide some evidence for the need to change how students are disciplined in schools in India and elsewhere. 2016, The Author(s) 2016. -
Youth of North East States of India: Issues, Concerns and Need for Mental Health Support as Perceived by NCC Officers
The youth of North-East India are in disadvantaged situations as compared to youth from the rest of the country in all respects. The objective of this article was to examine the views of the NCC Officers of North-East states about youth welfare in the region as they have first-hand experience in dealing with youth. Participants views were obtained on-line, by using a Semi-structured Questionnaire in the form of Google Form. A group of 142 NCC Officers provided feedback. Data collected were subjected to thematic analysis. Findings disclosed that youth of North-East states experience a range of challenges including poverty, lack of internet facilities, inability to attend NCC camps due to ongoing classes, substance dependence, lack of guidance and support leading to dropout and lack of values. The NCC Officers opined that a good number of North-East youths require mental health support and career guidance, in addition to mental health awareness. 2023 Taylor & Francis Group, LLC.