Browse Items (1422 total)
Sort by:
-
Efficient handwritten character recognition of modi script using wavelet transform and svd
MODI script has historical importance as it was used for writing the Marathi language, until 1950. Due to the complex nature of the script, the character recognition of MODI script is still in infancy. The implementation of more efficient methods at the various stages of the character recognition process will increase the accuracy of the process. In this paper, we present a hybrid method called WT-SVD (Wavelet Transform-Singular Value Decomposition), for the character recognition of MODI script. The WT-SVD method is a combination of singular value decomposition and wavelet transform, which is used for the feature extraction. Euclidean distance method is used for the classification. The experiment is conducted using Symlets and Biorthogonal wavelets, and the results are compared. The method using Biorthogonal wavelet feature extraction achieved the highest accuracy The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Elevating industries: Cloud computing's impact on industry-integrated IoT
[No abstract available] -
Elevating medical imaging: AI-driven computer vision for brain tumor analysis
Artificial Intelligence (AI) applications in the realm of computer vision have witnessed remarkable advancements, reshaping various industries and solving complex problems. In this context, this research focuses on the use of convolutional neural networks (CNNs) for classifying brain tumors - a crucial domain within medical imaging. Leveraging the power of CNNs, this research aimed to accurately classify brain tumor images into "No Tumor" and "Tumor" categories. The achieved test loss of 0.4554 and test accuracy of 75.89% exemplify the potential of AI-powered computer vision in healthcare. These results signify the significance of AI-driven image analysis in assisting healthcare professionals with early tumor detection and improved diagnostics, underlining the need for continuous refinement and validation to ensure its clinical effectiveness. This research adds to the expanding research and applications that harness AI and computer vision to enhance healthcare decisionmaking processes. 2024, IGI Global. All rights reserved. -
EM AND THE BIG HOOM by Jerry Pinto
[No abstract available] -
Embarrassment in the Context of Negative Emotions and Its Effects on Information Processing
Negative emotions are feelings of sadness arising out of negative evaluation of oneself by self or others. Embarrassment is characterized as a negative emotion which is experienced as a threat to ones social identity. This chapter discusses the differences between embarrassment and related negative emotions, namely shame, guilt and humiliation and its effects on information processing. Around 45 articles have been reviewed in the process, which were selected based on their relation to either negative emotions in general or specifically to one or more of them. The study uses the interactional (bio-psycho-social) approach to determine the antecedents and consequences of experiencing embarrassment and how it affects information processing. It further explores gender differences in the experience of negative emotions. Given that the existing evidence reveals many contradictory findings in the experience of negative emotions, this chapter conceptualizes certain factors that might influence this experience. It also provides some reasons for variations in experience of embarrassment and related negative emotions, on the basis of gender. This chapter concludes by proposing the complexity of embarrassment as an emotion and a conceptual framework of a continuum on which the experiences of embarrassment may lie and the factors determining the placement of these experiences with their cognitive implications. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020, Corrected Publication 2020. -
Emerging Novel Functional Materials from Biomass for Environmental Remediation
The Earth faces complex environmental challenges caused by both human activities and natural processes, affecting all life forms and ecosystems. Biomass-derived materials, sourced from renewable resources, serve as effective adsorbents, catalysts, and ion exchangers, providing sustainable solutions to environmental issues like water and air pollution, soil contamination, and waste management. Their significance lies not only in their biodegradability and sustainability but also in standardized testing and scalability considerations. The field of functional materials from biomass has the potential to transform environmental remediation, leading to a cleaner and more sustainable world. Here, we aimed to portrait the key approaches and recent developments in emerging functional materials from biomass tailored for environmental remediation, delving into their fundamental theories and concepts, various applications, and potential to reshape the remediation landscape. It evaluates the sustainability and biodegradability aspects of these materials, addresses challenges, and peers into the dynamic and rapidly evolving future of this field. Collaborative efforts between researchers, industry, and policymakers are pivotal to establishing guidelines and regulations ensuring the safe and responsible use of these materials. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Emerging technology adoption and applications for modern society towards providing smart banking solutions
The rapid advancement of emerging technologies has brought significant transformations to various sectors, including banking and finance. This chapter explores the adoption and application of emerging technologies in modern society, particularly focusing on their role in providing smart banking solutions. Technologies such as artificial intelligence (AI), blockchain, internet of things (IoT), and biometrics are revolutionizing traditional banking practices, enabling enhanced security, efficiency, and personalized services for customers. Through a comprehensive analysis of current trends and case studies, this chapter highlights the impact of these technologies on improving customer experiences, streamlining operations, mitigating fraud risks, and fostering financial inclusion. Additionally, it discusses the challenges and opportunities associated with the integration of these technologies into banking systems, including regulatory concerns, data privacy issues, and the need for skill development among banking professionals. 2024, IGI Global. All rights reserved. -
Emerging world of the metaverse: An Indian perspective
[No abstract available] -
Empathy and compassion as fundamental elements of social cognition
This investigation into compassion and empathy highlights their crucial functions in social cognition, which influence engagements in various settings. Cultural dimensions underscore the significance of human connection by highlighting the societal influences that shape empathetic behaviours. The correlation between compassion, empathy, and mental health underscores their capacity to cultivate resilience. They make valuable contributions to communication and conflict resolution within interpersonal relationships. Efficacious interventions provide opportunities for individual development. Ethical considerations emphasize the importance of maintaining a delicate equilibrium between self-care and empathy. Ongoing technological and neurological research promises an expansion of applications. Cultivating kindness and compassion revolutionizes societies, ushering in an era of more significant global interdependence where mutual comprehension underpins all human engagements. 2024, IGI Global. -
Empirical Assessment of Artificial Intelligence Enablers Strengthening Business Intelligence in the Indian Banking Industry: ISM and MICMAC Modelling Approach
Considering the context of the issue based on literature survey and expert opinion, this study investigates the drivers of Artificial Intelligence (AI) implementation, which further strengthens the Business Intelligence (BI) in taking better decision-making industries in India. For the purpose of serving the objective of examining the enablers towards having a smarter AI ecosystem in banking, the relevance of identified enablers from exhaustive literature survey were discussed with the experts from banking sector and AI professionals. Based on their opinion, 15 final enablers were defined based on the data collected have been put through Interpretive Structural Modelling (ISM) that reveals the binary relationship between the enablers to draw a hierarchical conclusion, and then assess the enablers about their independence, linkage, autonomous character, and dependence based on their calculated driving and dependence power through MICMAC analysis. The ISM and MICMAC integrated approaches have been used to establish interdependence among the enablers of AI in banking in India context. The study reveals that strong algorithms result in building quality AI information, and also the efforts from management related to commitment, financial readiness towards technological advancement, training, and skill development are quite essential in making the baking system smarter and would enable the industry to take better management decision. 2023 selection and editorial matter, Deepmala Singh, Anurag Singh, Amizan Omar & S.B Goyal. -
Employee attrition and absenteeism analysis using machine learning methods: Application in the manufacturing industry
HR analytics has been envisaged as recent research trend for providing a comprehensive decision support system to the top level management in terms of employee's performance, recruitment and behaviour analysis. Globally, organizations are using technology to support and ease HR processes. Every organization should give maximum value to every available human resource, and they should minimize the attrition and absenteeism rate and ensure what are the factors that contribute towards employee attrition as well as the causes for workmen absenteeism. The ultimate objective is to correctly identify attrition and absenteeism in order to assist the company to improve retention tactics for key personnel and increase employee satisfaction. Through this chapter, a machine learning-based model is proposed to get quick results for such employee attrition and workmen absenteeism. The model is trained and tested for its accuracy. The result shows that the proposed model has high sensitivity. The managerial implications are also discussed for taking informed decisions. 2023, IGI Global. All rights reserved. -
Employee motivation for sustainable entrepreneurship: The mediating role of green hrm
This chapter aims to explore the relationship between employee motivation and sustainable entrepreneurship with a specific focus on the mediating role of green human resource management (HRM). As organizations increasingly recognize the importance of environmental sustainability, understanding the mechanisms through which employee motivation translates into sustainable entrepreneurial behaviors becomes crucial. By integrating concepts from the fields of entrepreneurship, sustainability, and HRM, this study proposes that Green HRM practices play a mediating role in fostering employee motivation for sustainable entrepreneurship. The findings of this research provide valuable insights for organizations seeking to enhance their sustainability efforts by leveraging employee motivation and implementing effective Green HRM strategies. 2023, IGI Global. All rights reserved. -
Employees Job Satisfaction, Work-Life Balance, and Health During the Pandemic
The impact of the COVID-19 pandemic on private enterprises has been particularly noticeable in the IT and non-ITES sectors. Work came to a complete halt due to the ensuing lockdown, severely affecting businesses and further harming industries like aviation and hospitality. Widespread job losses, shortened workweeks, minimum wage reductions, short-term leave policies, and even company closures have been the results. To understand the extent of these impacts, a descriptive study was conducted online in AprilMay 2021, involving 2439 white-collar workers from various private companies. Convenient sampling methods were used to gather data on the experiences of employees in these sectors during the pandemic. The survey's findings demonstrate a positive but weak association between Work-Life Balance and Health Stress (r?=?0.24, p?<?0.01) and a positive low correlation between Work-Life Balance and Job Satisfaction (r?=?0.23, p?<?0.01). Therefore, work-life balance and job satisfaction among employees were significantly correlated throughout the epidemic. Additionally, there was a negative moderate correlation between Health Stress and Job Satisfaction (r?= ?0.48, p?<?0.01), indicating that as Health Stress decreases, Job Satisfaction increases at moderate levels. The implications of the study were discussed further. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Empowering families: Strategies for effective child and adolescent treatment
This chapter examines the importance of family involvement in infant and adolescent psychological practices and interventions. It emphasizes the significance of involving families in the therapeutic process, which leads to enhanced treatment outcomes, increased parent and carer satisfaction, and a higher probability of long-term success. It discusses evidence-based interventions that effectively engage and empower parents and carers, such as parent education, family therapy, and parent-child interaction therapy. Despite the numerous advantages, family involvement may face cultural differences, language barriers, stigma, and lack of awareness. Mental health professionals must adopt culturally sensitive approaches, combat stigma, and provide ongoing support and education to surmount these obstacles. When families are actively involved and empowered, they establish a strong support network beyond therapy sessions, promoting resilience and positive change for the child's development and well-being. 2024, IGI Global. All rights reserved. -
Empowering Gender Equality in Business Sustainability: A STARA (Smart Technologies, Artificial Intelligence, Robotics, and Algorithms)-Centric Exploration of Socio-Technological Innovation for Modern Business Environments
Technological paradigms worldwide are evolving at a breakneck pace. Workplaces are evolving, organizations are shifting, and businesses are seeking to sustain themselves based on technological development. In recent times, STARA (Smart Technologies, Artificial Intelligence, Robotics, and Algorithms) has emerged as an all-inclusive technological framework that seems a promising benefactor for businesses to thrive through technological adoption. But business sustenance is not all about driving profits. As much as they need to be digitally ready, they are still very much human, with their existence depending on their underlying workforces. Numerous socio-cultural aspects, gender inequality being one of them, plague business sustainability. The following paper seeks to explore corporate socio-technological landscapes. It seeks to substantiate ways gender inequality can be tackled via conscious STARA adoption while holistically ushering the way for business sustainability and success. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Empowering indigenous adolescents: Life skills development and transformative student engagement through service-learning
This chapter synthesizes results from examining service-learning initiatives tailored for Indigenous adolescents. The authors emphasize customized educational approaches, community collaboration, and cultural sensitivity. The Paniya Tribes case study in Wayanad illustrates efforts of this kind that seek to address historical inequities and enhance students' academic performance, life skills, and engagement. The enduring impact extends beyond academics, empowering young people to take on leadership roles. Cultural sensitivity and the responsible application of technology are two factors that can significantly impact Indigenous education's trajectory in the future. Implementing suggested strategies and optimal methods advances inclusive and culturally attuned education, thereby preserving Indigenous cultures and fostering sustainable development. 2024, IGI Global. All rights reserved. -
Empowering Renewable Energy Using Internet of Things
The massive communication of information over network gadgets associated with the internet trades data starting from one to another with no sort of human cooperation. As innovation is advancing, interconnected organizations give data to each other to impart. The energy utilization is happening at an extremely quick rate, debilitating the assets in delivering it at a similar rate, and the entirety of this requires a transformation to save energy. Information is the focal point of the Internet of Things (IoT), and it has all the information to which there was no entrance before; this information can be utilized in the revolution of the energy management framework. By utilizing advanced IoT innovations, the embracement of renewable can be upgraded signifcantly further. The reconciliation of IoT in renewable energy is empowering its development by and large. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
Empowering women through livelihood interventions: Case studies from an impoverished community
This chapter looks at the influence of a livelihood project in empowering women belonging to an impoverished community from one of the most backward regions of the state of Karnataka in Southern India. Jamkhandi taluq of Bagalkote district is one of the poorer taluqs in the state, with a sex ratio of 938 and a female literacy rate of 50.75%. The Centre for Social Action began working in the area around a decade ago. The livelihood project was an offshoot of a project on Population displacement that was undertaken in the region. CSA adopted the Self-Help Approach (SHA) to meet the needs of this community. This gave the necessary impetus for the creation of a livelihood project for disadvantaged women. The central theme of the chapter is to study the extent of empowerment that is evident among the project's women beneficiaries. This chapter presents the evidence of empowerment using the qualitative case study methodology using ten cases. The theoretical framework provided by the 'Three Dimensional Model of Women Empowerment' is used to present the analysis. Document review and in-depth interviews are the prominent data sets used to present the study's major findings. The hybrid approach to coding and thematic analysis is used to integrate the insights from the theory used as well as observations from the study. Both within-case analysis and cross-case analysis are used for analysis. The personal, relational, and societal dimensions of empowerment are presented through themes emerging from the data. The implication of the chapter is the reiteration of the efficacy of the model in empowering women. This model can be replicated in other project areas, and livelihood strategies can be adopted extensively. 2024 Nova Science Publishers, Inc. -
Encouraging sustainable living through HR initiatives
This chapter examines how human resources (HR) professionals can facilitate organizational change in the direction of environmental responsibility in the context of sustainable human resource management. HR establishes itself as a strategic catalyst for concrete transformations in employee conduct and organizational culture by implementing performance management integration, waste reduction, and sustainable commuting initiatives. The study emphasizes tangible instances, demonstrating how human resource initiatives surpass theoretical concepts to promote a dedication to environmental stewardship actively. In ecological sustainability, HR professionals serve as catalysts for organizations, imparting knowledge and devising strategies to direct progress. This thorough examination offers practical recommendations for incorporating environmentally conscious principles into the operations of organizations, thereby promoting long-term sustainability. 2024, IGI Global. All rights reserved. -
Energy efficiency and conservation using machine learning
This chapter explores the fascinating nexus between machine learning (ML), energy efficiency, and conservation, concentrating on a captivating case study that makes use of the oneAPI framework. Optimizing energy consumption has become crucial due to the increased interest in sustainable practices. By investigating the use of oneAPI in energy efficiency projects, we examine the possibility of ML techniques to overcome this difficulty. We demonstrate how ML algorithms can accurately model and anticipate energy usage patterns through a thorough analysis of real-world data. Additionally, we discuss the importance of feature engineering, algorithm selection, and data pretreatment in creating accurate energy consumption models. The case study emphasizes the wider implications of utilizing ML to support energy-saving initiatives in addition to demonstrating the effectiveness of oneAPI. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.