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Cultural quotient: Evolving culturally intelligent business scholar-practitioners
Analytical competency is an essential skill when it comes to the present-day business scenario of the world. However, these days we see a shift in the business needs when it comes to working in a globalized environment. Not only is the intelligence quotient (IQ) looked at but organizations these days are in pursuit of individuals who have another side to their profile - the culturally intelligent side (assessed using the cultural quotient). The need of such a skill can be attributed to the fact that organizations are now churning out their human side of addressing the employees when it comes to ensuring that they blend in the organization with ease. Acquiring a workforce which possesses high cultural intelligence can be a tough task; however, training employees to become culturally competent can be a doable task. Like any other personality trait which can be imbibed over time through constant analysis and observation, cultural competency is one such area which may be cultivated through various methodologies and practices. 2018, IGI Global. -
Using Analytics to Measure the Impact of Pollution Parameters in Major Cities of India
Coronavirus is airborne and can spread easily. Air pollution may have an impact on breathing and also keep the virus airborne. The levels of air pollution were impacted by the lockdown measures, restricting the vehicular and industrial pollutants. Therefore, there is a need to understand the relation between air pollution levels and the Coronavirus infection rate. The study aims to find the effect of various pollutants across major cities of India on the R-value. The pollution data was collected from the Governments official portal. The major pollutants on which the data was collected are PM2.5, PM10, NO, NO2, NOx, SO2, CO, and Ozone. The data on air pollution levels were also collected for the selected cities from April 2020 to April 2021. The spread is measured as the reproduction number at time t (Rt), which is an estimate of infectious disease transmissibility throughout an outbreak, or it is the rating of Coronavirus or any diseases ability to spread. The data is analysed using MS Excel and R Programming. Descriptive statistics and regularisation are performed on the data. The study results reveal that some pollutants positively and negatively affect the infection rate. However, the effect is very low, and it concluded that the pollution might not directly affect infection rates. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
A Comparative Analysis of Machine Learning Algorithms for Image Classification: Evaluating Performance
Image classification plays a crucial role in various applications, and selecting the most effective machine learning algorithm is essential for achieving accurate results. In this study, we conducted a comparative analysis of several well-known supervised machine learning techniques, including logistic regression, support vector machine (SVM), k-nearest neighbours (kNN), nae Bayes, decision trees, random forest, AdaBoost, and artificial neural networks (ANN). To assess the performance of these algorithms, we utilised different fonts of the English alphabet as our dataset and performed the analysis using the R programming language. We evaluated the algorithms based on standard performance criteria, such as the area under the Receiver Operating Characteristic curve (ROC), accuracy, F1 score, precision, and recall. Our research findings demonstrated that the classification performance varied depending on the training size of the dataset. Notably, as the training size increased, neural networks exhibited superior performance compared to other machine learning techniques. Consequently, we conclude that neural networks and SVM are the most effective algorithms for image classification based on our study. By conducting this comprehensive analysis, we contribute valuable insights into selecting appropriate machine learning algorithms for image classification tasks. Our findings emphasise the significance of considering the training dataset size and highlight the advantages of neural networks and SVM in achieving high classification accuracy. This study provides valuable guidance for practitioners and researchers in choosing the most suitable machine learning algorithm for image classification, considering their specific requirements and dataset characteristics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Classifying voice-based customer query using machine learning technique
Timely attention to issues raised by customers is critical. It is imperative that the average handling time is lesser, which in turn contributes to productivity. It was found from the data from the banking industry in the US that, on average, a customer service call last for seven minutes. The first two minutes are for the call to get redirected to the respective team. This study investigates a method using machine learning to classify and redirect the customers into the respective department directly based on their initial voice response or voice message. It will substantially reduce the service time. CRISP-DM methodology is being used to design the process of the study. The most frequently occurring issues and the department to which they are associated are created through machine learning from the dataset that contained product reviews and metadata of different issues. The programming languages that are used in this study are Python, HTML and Java. An interface is created by using HTML, which makes it quite user-friendly. The study tests the effectiveness of converting voice to text and interprets which department the call should be transferred to address the issue. A support vector machine and a logistic regression model were used for the prediction, and it was found that the models provided an accuracy of 83 and 84 percent, respectively. The study proves that using ML and voice recognition reduces the average handling time. 2021 Ecological Society of India. All rights reserved. -
Using Academic Performance Indicator to Evaluate the Cost to Company of Management Graduates
As the placement season hits CBS Business School, India, the pressure to get placed is at its peak. As the placement season draws to a close, the unplaced students storm the Directors office complaining about unfair treatment in the process. They lay blame on the random shortlisting followed by the Placement co-ordinator. Concerned with these allegations, the Director calls on faculty to investigate the situation. During the conversation one of the students, Rachit, expresses regret in not focusing solely on academics and instead on developing a more well-rounded profile. He feels that that is the reason for his failure to get placed. A fundamental question arises of how closely academic performance and Cost to Company (CTC) are related. Data is collected to examine the validity of the long-held belief that higher academic performance leads to higher paying job placement. 2022 NeilsonJournals Publishing. -
Unsupervised Feature Selection Approach for Smartwatches
Traditional feature selection methods can be time-consuming and labor-intensive, especially with large datasets. This studys unsupervised feature selection approach can automate the process and help identify important features preferred by a particular segment of users. The unsupervised feature selection method is applied for smartwatches. Smartwatches continue to gain popularity. It is important to understand which features are most important to users to design and develop smartwatches that are more engaging, user-friendly, and meet the needs and preferences of their target audience. The rapid pace of technological innovation in the smartwatch industry means that new features and functionalities are constantly being developed. Multi-cluster feature selection, Laplacian score, and unsupervised spectral feature are used. Conjoint analysis is done on the most common features in all three selection methods. The unsupervised feature selection technique is used for identifying the relevant and important features of new smartwatch users.The practical implication of the research is in the application of the technique in the new product design of smartwatches. The result of the study also informs smartwatch manufacturers and developers on the features they need to prioritize and invest in. This can ultimately result in better and more user-friendly smartwatches and a good overall experience for the user. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Predicting Consumer's Brand Switching Behaviour for Cell Phones
The IUP Journal of Marketing Management, ICFAI, Vol. XV, Issue 4, ISSN No. 0972-6845 -
An Expected Model of Management Program in India
Pravara Management Review, Vol 15, Issue 2, pp. 17-23, ISSN No. 0975-7201 -
A Predictive Modelling of Factors Influencing Job Satisfaction Through a CNN-BiGRU Algorithm
The fields of humanities, psychology, and sociology are where the word 'job satisfaction' originated. According to psychology, it is a condition in which a worker experiences his circumstances emotionally and responds by experiencing either pleasure or suffering. It is regarded as a variable in various sociological categories pertaining to how each employee assesses and thinks about his work. Because a satisfied employee contributes to and builds upon an organization's success, job satisfaction is intimately tied to an employee's performance and the quality of the work they do. As a result, job satisfaction directly correlates to an organization's success. The proposed strategy incorporates data preprocessing, feature selection, and model training. The missing value is a common feature of data preparation. Feature selection is chosen using the ANOVA F-Test Filter, the Chi-Square Filter, and the full Data Set Construction procedure. The model's efficacy can be evaluated with the help of CNN-BiGRU. The proposed technique is compared to two more models: BiGRU and CNN. It has been shown that our proposed technique outperforms two other models. 2023 IEEE. -
Detection of high-frequency pulsation in WR135: Investigation of stellar wind dynamics
We report the detection of high-frequency pulsations in WR 135 from short-cadence (10 minute) optical photometric and spectroscopic time series surveys. The harmonics up to the sixth order are detected from the integrated photometric flux variations, while the comparatively weaker eighth harmonic is detected from the strengths of the emission lines. We investigate the driving source of the stratified winds of WR 135 using the radiative transfer modeling code, CMFGEN, and find the physical conditions that can explain the propagation of such pulsations. From our study, we find that the optically thick subsonic layers of the atmosphere are close to the Eddington limit and are launched by the Fe opacity. The outer optically thin supersonic winds (Tross = 0.1 0.01) are launched by the He II and C IV opacities. The stratified winds above the sonic point undergo velocity perturbation that can lead to clumps. In the optically thin supersonic winds, dense clumps of smaller size (fVFF = 0.27 0.3, where fVFF is the volume filling factor) pulsate with higher-order harmonics. The larger clumps (fVFF = 0.2) oscillate with lower-order harmonics of the pulsation and affect the overall wind variability. 2024. The Author(s). -
Student engagement in community development: A strategy for whole-person development
Student engagement in community development has been closely linked to enhanced learning outcomes and whole-person development. The Centre for Social Action (CSA) at Christ University emerged as a student-led student-driven initiative to promote volunteerism and engagement in community development that enabled the student community to identify and work on development initiatives. The objective of the chapter is to examine the factors that influence student engagement in community development initiatives and explore the factors that motivate them to volunteer. It also looks at their perception of the benefits for the two main stakeholders in the process, namely the students themselves and the community that they work with. This chapter uses a qualitative framework, and the data is collected through in-depth interviews and focus group discussions with current and past volunteers with CSA. The participants in the study have been selected using purposive sampling techniques and represent students who have worked on the major initiatives undertaken by CSA, namely the activity centre and the various social awareness and sensitization initiatives. The interviews and the focus group discussions have been conducted on virtual meeting platforms, and the data has been analyses thematically. The research design lends itself to a rich exploration of student perception of their engagement in community development, their motivation, the benefits that they perceive of their engagement with the activities for both themselves and other stakeholders, and how it ties into the construct of whole-person development at the individual level and whole-person education at a broader level. 2024 Nova Science Publishers, Inc. -
Predicting Price Direction of Bitcoin based on Hybrid Model of LSTM and Dense Neural Network Approach
Bitcoin is a rapidly growing but extremely risky cryptocurrency. It marks a watershed moment in the history of cash. These days, digital currency is preferred to actual money. Bitcoin has decentralized authority and placed it in the hands of its users. Many people are joining the largest and most well-known Bitcoin mining pools as the risk of working alone is too great. In order to enhance their chances of creating the next block in the Bitcoins blockchain and decrease the mining reward volatility, users can band together to form Bitcoin pools. This tendency toward consolidation may also be seen in the rise of large-scale mining farms equipped with powerful mining resources and speedy processing capability. Because of the risk of a 51% assault, this pattern shows that Bitcoin's pure, decentralized protocol is moving toward greater centralization in its distribution network. Not to be overlooked is the resulting centralization of the bitcoin network as a result of cloud wallets making it simple for new users to join. Because of the easily hackable nature of Bitcoin technologies, this could lead to a wide range of security vulnerabilities. The proposed approach uses normalization and filling missing values in preprocessing, PCA for feature Extraction and finally training the model using LSTM-DNN Models. The proposed approach outperforms other two models such as CNN and DNN. 2023 IEEE. -
Covid-19, macroeconomic policies, and analysis of the inflation-unemployment dynamics in india
Indian economy could largely withstand the adversities of 2008 recession, the signs of a downturn were clearer by 2017 following the arrival of twin policies, Demonetization as well as the Goods and Services Tax. The COVID-19 pandemic has deepened the crisis leading to a significant reduction in production and total expenditure. Although India has resorted to a combination of conventional policies monetary as well as fiscal injections to face the economic crisis, it has had serious negative consequences on production and employment. We investigate the nature of relationship between inflation and unemployment during the recession and the pandemic times using the non-linear regression analysis. The results reveal that the recessionary phase has given way to a stagflationary situation owing to inflation persistence in the short run. We suggest the usefulness of a more comprehensive term structure strat?gy to deal with the adverse supply shocks and policy failures. Indian Institute of Finance. -
Sustainable environment protection and waste management in higher education institutions: A case study
Sustainable environment protection and waste management are global concerns that major cities are grappling with, and it is the most important environmental factor that higher educational institutions in India are considering right now. "Parivarthana, "-the recycling unit of the Centre for Social Action at Christ University, Bengaluru, is evolved as a paradigm for all higher education institutions in terms of long-term environmental protection through waste management and the efforts of student volunteers. The student volunteers have been successful in sensitizing all members of the University to the importance of environmental conservation, and there is rising evidence of accountability among all members regarding waste management. The basic sense of social responsibility of student volunteers toward environmental sustainability is the primary focus of this chapter. Student volunteers who have a higher sense of social responsibility have a better attitude toward their studies, which leads to higher academic accomplishment and a desire to take action to address environmental challenges. Their environmental awareness, climate change, the need to reduce greenhouse gas emissions, efficient use of natural resources, waste management, and sustainable consumerism have served as an example for students of other higher educational institutions. A qualitative method with a case study approach was applied for this research with In-depth interviews with all stakeholders of the unit. The objectives include the participants' understanding of the prevailing process of waste management in the unit, the relation between waste management and Climate change, and the role of the student volunteers and other stakeholders of the Higher Educational Institutions in bringing a model to Sustainable Development and Global Climate Change. 2024 Nova Science Publishers, Inc. -
Sustainable Waste Management and Womens Empowerment
Waste management is a problem faced by major cities. Rural migration to urban areas created unplanned residential areas and high population density, and temporary living structures have a direct impact on poor waste management systems in urban areas. From September 2020 until February 2021, a case study was conducted (the first lockdown period of the COVID-19 Pandemic) among women members from an urban slum in Bangalore with objectives to understand the prevalent process of waste management and comprehend the association between womens empowerment and sustainable waste management in a slum community. The purposive sampling technique was applied to select 10 women members of the slum community for this community-based participatory research as co-researchers from the slum community, along with all stakeholders. The results show that the women members could implement the immediate plans on waste management, including educating their neighbours on waste management, to ensure that a large part of the society they are living in is aware of it. The women members demonstrated their motivation and willingness in their actions in the slum neighbourhood concerning sustainable waste management. They applied their participatory activities to empower other women in the area by focussing on every stretch of the slum and educating on the management of waste. All the actions by the women members in the urban slum community and the stakeholders of waste management in that community intend to support the quality of life and strengthen the resilience to climate change through sustainable waste-management and are reflected in SDG 3, SDG 5, SDG 11, and SDG 13. 2024 CRC Press. -
Clinical Study Macular Oedema
Prior to the development of the ophthalmoscope, macular oedema remained mostly unknown. Macular oedema is caused by fluid buildup in the retinal layers around the fovea. It causes vision loss by changing the functional cell connection in the retina and stimulating an inflammatory reparative response. The clinical profile, aetiology, and varied types of Macular Oedema are hence the focus of research, and also to investigate the aetiology of macular oedema as well as the various forms of macular oedema in patients attending Krishna Hospital in Karad. The male to female ratio among the 60 participants was 2.53:1. Macular oedema is the major cause for loss in vision which is common vitreo retinal diseases, with diabetes being the most prevalent cause (35% of cases) in our study. Its early detection and treatment are critical for preventing blindness. It is consequently critical to understand the aetiology, pattern, and chronicity of macular oedema in order to customize treatment and monitor response to it. RJPT All right reserved. -
Handwritten Telugu Character Recognition Using Machine Learning
The Telugu language is the most prominent representative within the Dravidian language family, predominantly spoken in the southeastern regions of India. Handwritten character recognition in Telugu has significant applications across diverse fields such as healthcare, administration, education, and paleography. Despite its importance, the Telugu script differs significantly from English, presenting distinct challenges in recognizing characters due to its complexity and diverse character shapes. This study explores the application of machine learning, particularly delving into deep learning techniques, to improve the accuracy of Telugu character recognition. This paper proposes a model to recognize handwritten Telugu characters using Convolutional Neural Network (CNN). The proposed study demonstrates the accuracy in identifying diverse handwritten Telugu characters. We assess the system's performance against conventional and machine learning methodologies and preprocess an extensive dataset to guarantee strong model training. The proposed model excels in accurately predicting visually similar but distinct characters, achieving an impressive accuracy rate of 96.96%. 2024 IEEE. -
Textual and media-based self-learning modules: Support for achievement in algebra and geometry
Owing to the importance of a subject like mathematics in the teaching and learning of science, self-learning often poses a challenge to the educator. The objective of this study is to analyse the enhancement of the textual and the media form of self-learning modules to teach algebra and geometry to eighth graders considering their retention levels. A pre-Test post-Test single-group quasi experimental design was tested and tried out on 49 participants of a school. The 20 modules of self-learning material covering content in the topics of algebra and geometry in the textual and media-Assisted forms of self-learning were administered over three months. The findings of the study revealed the ability of media-Assisted self-learning modules to enhance achievement in the post-Test when compared to the pre-Test. The textual-Assisted learning modules were able to enhance significant difference in the achievements in geometry, but not of algebra. The delayed post-Test results were found to indicate an improved achievement in mathematics. 2022 IGI Global. All rights reserved. -
Exploring the factors of learning organization in school education: therole of leadership styles, personalcommitment, andorganizational culture
Purpose: This study aims to test the conceptual model of the factors of learning organization and explore the degree of mediation of organizational culture in the relationship between leadership styles, personal commitment, and learning organization in school education. Design/methodology/approach: The learning organization profile (LOP) and OCTAPACE profile served to measure learning organization and organizational culture, respectively. The researchers developed scales to measure principals leadership styles and teachers personal commitment. Data included 750 school teachers. Findings: This study found a good fit in the proposed conceptual model. The organizational culture had a significant mediating effect on the path of leadership styles and learning organization and a significant mediating effect on the path of personal commitment and learning organization. Originality/value: To promote a more comprehensive learning culture, school principals should consider two specific organizational mechanisms: the intangible cultural components (such as corporate values, beliefs, and norms) and the tangible structural components (such as organizational structure and workflow systems). These two domains play a crucial role in creating a conducive learning environment. 2024, Jacqueline Kareem, Harold Andrew Patrick and Nepoleon Prabakaran. -
Transformational educational leaders inspire school educators commitment
Introduction: Transformational school leaders play an important role in promoting educational innovation and restructuring by creating a vision for the future, building a culture of collaboration, and empowering others to become leaders themselves. Through their leadership style, they inspire and motivate others to work towards a common goal, leading to positive change and growth within the educational system. The aim of this study is to measure the impact of transformational leadership on various types of commitment that school teachers have in Bengaluru, India. Methods: A survey was conducted using standardised instruments to measure the leadership style of principals and personal commitment of teachers. The data was collected from 1,173 school teachers through a questionnaire and analysed using SPSS V23 statistical software. Results: The study found that transformational leadership had a significant impact on the different types of commitment that teachers possess in school education. The three domains of commitment - commitment towards the institution, student development, and self-development - were positively influenced by transformational leadership. Discussion: Transformational school leaders play an important role in promoting educational innovation and restructuring by creating a vision for the future, building a culture of collaboration, and empowering others to become leaders themselves. This study provides evidence that transformational leadership has a positive impact on different types of commitment among school teachers in Bengaluru, India. Leaders of school management are advised to take into account the three domains of commitment of their teachers to facilitate organisational learning through more integrative methods. Copyright 2023 Kareem, Patrick, Prabakaran, B, Tantia, M. P. M. and Mukherjee.