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Key management solutions for database as a service: A selective survey
In todays scenario, efficient data processing is a fundamental and vital issue for almost every scientific, academic, or business organization. To tackle this issue, organizations end up installing and managing database systems to satisfy different processing needs. In case of adopting a traditional solution, the organization needs to purchase the necessary hardware, deploy database products, establish network connectivity, and hire professional people who run the system. But this solution is getting impractical and expensive as the database systems and problems become larger and complicated (El-Khoury et al., 2009). Again, traditional solution entails different costs from the perspective of the investments involved. These concerns are handled efficiently to a great extent by the fast developing technology that goes by the name, cloud computing.. 2014 by Taylor & Francis Group, LLC. -
Kingship and Vedic Literature: Inflections, Deflections and Reflections
This chapter seeks to examine the figurations and configurations of 'kingship' reflected in different Vedic literary narratives in general and particularly aims at foregrounding how 'kingship' that happens to be one of the oldest forms of political governance, originated in Vedic times and how it became multifaceted with the passage of time. This chapter particularly seeks to employ three epistemological lenses - govern(mentality), sacral (infra)structuralism and planetarity - to lay down how the Vedic notion of 'kingship' underwent 'intensive' changes and how it stood in conformity with varied dimensions of contemporary political ecology. Besides that, this chapter aims at bringing out how Vedic notion of 'kingship' embodies the limits of 'human' by means of performing a liaison between the Almighty and ordinary human beings. Finally, at the end, royal haecceities of Vedic 'kingship' are critically taken up to facilitate readers to grasp the ontological and onticological fluidity of Vedic understanding of 'kingship'. 2024 selection and editorial matter, Nizar Zouidi; individual chapters, the contributors. -
Knowing Human Gaze
Studies have examined the understanding of human gaze in animals. Gaze following in human infants has been successfully demonstrated, showing that infants can follow the eye direction of another though the ability to represent the intentions of gaze behaviour emerges only after the onset of object permanence or a period over eighteen months of age. Comparative studies indicate that gaze following or gazing at humans vary in different species of animals. Wolves for example were observed to look least at human experimenters during a performance task, whereas dogs turned to look more often and monkeys looked to a lesser extent at their experimenters. It is of interest to discuss that gaze following is different from understanding gaze. Dogs have been observed to be successful in gaze following and almost at par with young children. However, the intention of another's gaze is not as clearly understood by dogs as in humans. We (Ittyerah and Gaunet 2009) have shown that the response of dogs to the gaze of their caretakers did not differ between guide dogs of the blind and pet dogs of sighted people. Both groups of dogs seemed to have responded to the head direction of their caretakers during a search task, indicating that the visual status of the caretaker did not affect the dog's understanding of human gaze. Further some breeds of dogs may respond more often to gaze, while larger inter ocular distances in large dogs could facilitate their response to visual cues. Therefore awareness of interactions between breed and physical size could contribute to studying gaze and cognition among dogs. 2012 Nova Science Publishers, Inc. -
Knowing human gaze
Studies have examined the understanding of human gaze in animals. Gaze following in human infants has been successfully demonstrated, showing that infants can follow the eye direction of another though the ability to represent the intentions of gaze behaviour emerges only after the onset of object permanence or a period over eighteen months of age. Comparative studies indicate that gaze following or gazing at humans vary in different species of animals. Wolves for example were observed to look least at human experimenters during a performance task, whereas dogs turned to look more often and monkeys looked to a lesser extent at their experimenters. It is of interest to discuss that gaze following is different from understanding gaze. Dogs have been observed to be successful in gaze following and almost at par with young children. However, the intention of another's gaze is not as clearly understood by dogs as in humans. We (Ittyerah and Gaunet 2009) have shown that the response of dogs to the gaze of their caretakers did not differ between guide dogs of the blind and pet dogs of sighted people. Both groups of dogs seemed to have responded to the head direction of their caretakers during a search task, indicating that the visual status of the caretaker did not affect the dog's understanding of human gaze. Further some breeds of dogs may respond more often to gaze, while larger inter ocular distances in large dogs could facilitate their response to visual cues. Therefore awareness of interactions between breed and physical size could contribute to studying gaze and cognition among dogs. -
Language and identity formations of second-generation migrants in Deepak Unnikrishnan's temporary people
Decades of migration to the Gulf nations have led to the existence of second-generation migrants who were born and raised in migrant lands. The chapter uses the novel Temporary People (2017) by Deepak Unnikrishnan as a primary text to explore the role language plays in second-generation migrant identity formations and the assimilation process. The national language, Arabic, is situated in the specific socio-political context, a site where ideologies and power relations are reproduced. By identifying a gap in the language education policy, it reveals how migrant's inability to communicate in the Arabic language has complex implications on their identities and notions of belongingness. The chapter explores language's power to naturalize norms and hierarchical structures within society that can hinder the assimilation process and highlights the migrant-citizen divide. It shows how notions of temporariness and Othering in migrants are inherent within the language politics of the land. The chapter reaffirms language-identity relations and points to revaluating migrant language policies. 2023, IGI Global. All rights reserved. -
Leading and learning in inhospitable terrain
This chapter explores the obstacles that minority women in K-12 education leadership must overcome, emphasizing the critical importance of acknowledging barriers and prejudices. Notwithstanding its underrepresentation, their leadership demonstrates a steadfast dedication to diversity and offers distinctive viewpoints. Mentorship programs, educational institutions, and policymakers all play a crucial role in promoting diversity via inclusive practices and supportive policies. The recommendations include fostering an environment of inclusiveness, providing training on diversity, implementing precise career trajectories, and acknowledging and commemorating the accomplishments of a wide range of individuals. Collaborative endeavours and inclusive approaches aim to establish educational leadership that is fair, diverse, and student-focused. Addressing inequalities is critical to establishing inclusive and resilient educational environments where mental health should be regarded as a fundamental right, highlighting the convergence of mental health and human rights. 2024, IGI Global. All rights reserved. -
Leaf Disease Identification in Rice Plants Using CNN Model
Rice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Fungal, bacterial and viral are different classes of diseases damaging rice crops which results in low and bad yield as per quality and quantity of the crop. Some of the most common diseases affecting plants are fungal blast, fungal brown spot, fungal sheath blight, bacterial blight and viral tungro. The deep learning CNN model with ResNet50V2 architecture was used in this paper to identify disease on the paddy leaves. Mobile application proposed in this paper will help farmers to detect disease on the leaves during their regular visit. Images were captured using this application. The captured images were tested using the trained deep learning model embedded with mobile application. This model predicts and displays input images along with the probabilities compared to each disease. The mobile application also provides necessary remedies for the identified disease with the help of hyperlink available in mobile application. The achieved probability that the model can truly classify the input image in this project was 97.67%, and the obtained validation accuracy was 98.86%. A solution with which farmers can identify diseases in rice leaves and take necessary actions for better crop yield has been demonstrated in this paper. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Learn, unlearn, and relearn: A step towards bringing resilience in business organizations in the post-COVID-19 regime
The world on a whole has undergone a paradigm shift in its journey with the onset of the COVID-19 threat. Business houses of any stature tremendously suffered towards their consistent and competitive survival. Means and measures are few to implement and very challenging in reaping the benefits. Sheer fall in GDP, dropping in the rate of industrialization and productivity are no unknown facts in the present-day scenario. Indians are unfortunate to embrace the pandemic at the juncture of planning and forecasting of India becoming a five trillion dollar economy by 2025. 2022, IGI Global. All rights reserved. -
Legal and Bioethical View of Educational Sectors and Industrial Areas of 3D Bioprinting
Recent advancements in three-dimensional printing (3D printing) within the medical field, particularly in the realm of 3D bioprinting, have shown tremendous potential in transforming various medical therapies, offering new approaches to treat organ failure and injury. However, amidst this optimism, several significant ethical and legal challenges remain unresolved before the application and transplantation of 3D bioprinted technology and organs in human subjects can become a reality. This chapter focuses on exploring the ethical and legal constraints associated with 3D bioprinting technology from both educational and industrial perspectives, recognizing their crucial roles as cornerstones for future applications. Furthermore, the analysis of 3D bioprinting technology will be conducted through the lens of the fundamental medical ethics principle, Primum non nocere; First, do no harm. Moreover, the pressing need for effective and timely standalone laws to regulate the subject of 3D printing is emphasized. This urgency arises from the grave concerns posed by the future implications of this technology on Indias scientific research and medical practice. The aim of this paper is to provide a comprehensive examination of the ethical and legal challenges posed by 3D bioprinting technology. By considering both educational and industrial perspectives, this research seeks to shed light on the complexities surrounding the application and transplantation of 3D bioprinted organs. Additionally, the analysis through the principle of Primum non nocere will contribute to the understanding of the ethical implications inherent in this innovative technology. Ultimately, this study advocates for the formulation of appropriate regulations and guidelines through the implementation of effective standalone laws, ensuring the responsible development and utilization of 3D printing technology in the realm of scientific research and medical practice in India. 2024 Scrivener Publishing LLC. -
Leveraging Blockchain Technology forInternet ofThings Powered Banking Sector
Banking sector contributes to 70% of Indian Gross Domestic Product (GDP) and for India to meet its economic aspirations, it should enable this vivacious sector to grow at 810 times of its current pace, in the next ten years. This pace of active growth requires a double engine of sophisticated technology and a tech enabled, scalable, and a secured banking system. Implementing BlockchainTechnology (BCT) in the banking sector, provides a realistic solution which when coupled with devices connected by the Internet of Things(IoT), will result in secured, fast-paced, cost effective, and transparent growth of the sector. The prevalence of personalized banking, secured banking, connected banking, and digital banking are use cases, made possible through interface with IoT. This chapter delves into the opportunities in the banking sector to be explored and challenges to be met in the BCT-IoT implementation process. BCT- and IoT-based opportunities such as peer-to-peer lending, Know Your Customer (KYC) updation, Cross-border transfer payments, syndicate lending, fraud reduction are some of the banking operations that are elaborated. To strengthen the banking network, the consensus algorithm of Blockchainnetwork is much required and the use of IoT devices to act as nodes is pertinent. The blend of both in the banking space has to be further reinforced. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Leveraging Deep Learning in Hate Speech Analysis on Social Platform
The scope and usage of the Internet have surpassed the expected growth and have proven beyond the basic purpose of being used for networking and telecommunications. It serves as the backbone of the web, and one of the predominant domains that uses the Internet is social media. The concept was conceived in the early 1990s and went on to grow as a powerful medium of people networking along with the Internet. Social networking sites (SNS) acquired a predominant element of the Internet owing to their use and services they offer through the Internet. A few of the most used social networking sites include Twitter and Facebook, which are used synonymous to expressions of text. These SNS allow the users to post photos, videos, and other multimedia content along with text and voice messages that are shared among other users. As with any technology or application, these also have the risk of users posting offensive material and textual content. Hate is being spread through messages, which are in the form of text and also through other materials posted. There is no control to check for the message for the hate content as and when it is posted, and by the time it is deleted by admins, it could have already reached millions of users. This chapter proposes a technique for detecting hate texts in reviews from registered users in the Twitter dataset. The proposed work makes use of improved principle component analysis (IPCA) and modified convolution neural network (MCNN) for detecting hate texts. The advantage of natural language processing is used for building an automated system for the analysis of syntax and semantics of the words. The proposed methodology consists of phases like pre-processing, feature extraction, and process to classify the text. The white spaces in the text are removed through normalization in the pre-processing phase, and also remove special characters such as question marks, punctuations, and exclamatory symbols to remove stop words. The features that are pre-processed are then subjected to feature extraction using IPCA. A set of correlated features are made used for identifying more important features in the data set under consideration. Next, the classification is done for identifying the hate text or for any language abuse. MCNN is applied for the classification of the text into HATE and NON-HATE from the text with better accuracy. The experiments prove that the proposed method has a high level of accuracy even for a large dataset. The results show that the proposed method has better performance in terms of precision, recall, and F-measure when compared with other state-of-the-art methods. 2024 Taylor & Francis Group, LLC. -
Leveraging Employee Data to Optimize Overall Performance: Using Workforce Analytics
Consistent employee performance is necessary for timely achievement and business success. Many key performance indicators influence an employees organizational performance, such as employee satisfaction, employee work environment, relationship with managers and coworkers, work-life balance, and many more. It becomes critical to regularly understand how these factors are connected to employee performance. One such method that is commonly used in companies is workforce analytics. It is a process that uses data-based intelligence for improving and enhancing management decisions in hiring and constructing compensations in alignment with employee performance. This also helps the management make data-based decisions and predictions, which helps in cost reductions and increases the overall profit. This chapter aims to analyze and report the workforce-related data and visualize the performance of 1,470 employees using published IBM human resources (HR) data made available at https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003357070/bb25a486-c036-4524-ab00-446f8eda3fd1/content/www.Kaggle.com xmlns:xlink=https://www.w3.org/1999/xlink>Kaggle.com. The chapter considers the following factors - job involvement, job satisfaction, performance rating, relationship satisfaction, environmental satisfaction, employee tenure, work-life balance, and income level - for data analysis and visualization of employee performance. The chapter aims to adopt descriptive, diagnostic, and predictive analysis using various software like Python, the Konstanz Information Miner (KNIME), and Orange. The visualization will be made using Tableau, Power BI, and Google Data Studio. Thus, the chapter gives a comprehensive insight into the meaning and importance of workforce analytics, different technologies used in workforce analytics, workforce analytics trends and tools, challenges of workforce analytics, and the process of implementation of workforce analytics. 2024 selection and editorial matter, Alex Khang, Sita Rani, Rashmi Gujrati, Hayri Uygun, and Shashi Kant Gupta; individual chapters, the contributors. -
Leveraging Financial Data to Optimize Automation: An Industry 4.0 approach
Industry 4.0 is a transformative approach that leverages advanced technologies to enhance business efficiency and productivity. Automation is a crucial aspect of next-generation industry, and leveraging financial data is essential to optimizing the automation process. This chapter discusses the role of financial data in optimizing automation processes using an I-4.0 approach. Financial data is derived from various sources and can be collected through different methods, such as automated data collection, manual entry, or using sensors and Internet of Things (IoT) devices. The integration of these sources can pose challenges for businesses. The chapter outlines techniques for automation optimization, such as machine learning, predictive analytics, and business process reengineering. Optimizing automation using financial data offers various benefits for businesses, including cost savings, improved quality, and increased profitability. However, there are challenges that businesses face in leveraging financial data, including the integration of various data sources and formats and the need for skilled personnel to analyze and interpret the data. The successful implementation of automation and optimization of processes can lead to sustainable growth and enhanced operations, making it crucial for businesses to remain competitive in the I-4.0 era. By leveraging financial data to optimize automation processes, businesses can maximize their potential and drive growth. Overall, this chapter highlights the significance of financial data in automation optimization and provides insights into the benefits and challenges that businesses must consider when leveraging financial data for optimization. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors. -
Leveraging FinTech for the Advancement of Circular Economy
During the past six decades, there has been a lot of emphasis on increasing production and fulfilling the demands of the fast-growing population. As a result, there has been unprecedented utilization and depletion of natural resources and harm to the environment. It was rightly realized by government and policymakers that there is an indispensable need to align economic development with the environment. In other words, the world needs to pursue environmentally friendly economic development. In order to achieve sustainable development, the thought leaders devised a new approach called circular economy. The circular economy focuses on reusing and recycling materials to reduce the consumption of natural resources and minimize waste creation. In recent years, financial technology commonly known as FinTech has become a significant part of commercial activities across many industries. FinTech has benefited organizations and users in terms of cost and time saving with a high degree of reliability. This article outlines the ways in which FinTech supports the cause of a circular economy. It also explores the impediments in this path. 2024 Scrivener Publishing LLC. -
Leveraging machine learning models for intelligent hazard management
[No abstract available] -
Leveraging transparency and privacy through blockchain technology
Blockchain is a conveyed record innovation that can be utilized to keep exchanges in a safe and straightforward way. This makes it a promising innovation for various applications, for example inventory network the executives, monetary administrations, and medical services. One of the vital advantages of blockchain is its capacity to guarantee information consistency. This is on the grounds that all information on the blockchain is put away in a disseminated way, and every hub in the organization has a duplicate of the record. This makes it truly challenging for any one party to mess with the information. One more key advantage of blockchain is its straightforwardness. All exchanges on the blockchain are public, and anybody can see them. This can assist with building trust and straightforwardness among partners. Blockchain can likewise present difficulties regarding information security. This is on the grounds that all information on the blockchain is put away in a public record. This implies that anybody with admittance to the blockchain can see the information, including delicate data, for example individual recognizable proof numbers (PII). There are various ways of tending to the difficulties of information protection in blockchain. One methodology is to utilize encryption to safeguard delicate information. Another 2024, IGI Global. All rights reserved. -
Leveraging unsupervised machine learning to optimize customer segmentation and product recommendations for increased retail profits
The retail sector's success hinges on understanding and responding adeptly to diverse consumer behaviours and preferences. In this context, the burgeoning volume of transactional data has underscored the need for advanced analytical methodologies to extract actionable insights. This research delves into the realm of unsupervised machine learning techniques within retail analytics, specifically focusing on customer segmentation and the subsequent recommendation strategy based on clustered preferences. The purpose of this study is to determine which unsupervised machine learning clustering algorithms perform best for segmenting retail customer data to improve marketing strategies. Through a comprehensive comparative analysis, this study explores the performance of multiple algorithms, aiming to identify the most suitable technique for retail customer segmentation. Through this segmentation, the study aims not only to discern and profile varied customer groups but also to derive actionable recommendations tailored to each cluster's preferences and purchasing patterns. 2024, IGI Global. All rights reserved. -
Life skills for personal well-being
This investigation examines the integrative and transformative qualities of service learning in higher education, specifically focusing on its contribution to developing personal well-being-related life skills. By integrating significant community service with academic goals, service learning provides a comprehensive educational experience. Its defined components, theoretical framework, and real-world applications underscore the subject's significance. Student experiences and case studies illustrate its influence on empathy, resiliency, and communication. Strategic implementation approaches serve as a compass for purposeful undertakings. Service learning connects theoretical concepts with practical application, cultivating globally literate and socially conscious individuals who can navigate the everchanging realm of higher education. 2024, IGI Global. -
Light Tracking Bot Endorsing Futuristic Underground Transportation
Controlling a bot machine that uses non-conventional energy form, i.e. light is said to have an upper hand in pioneering transportation system. The expanding request of making the streets more secure has persuaded a ton of organizations to create finest autonomous vehicles. This paper will concentrate on the potential outcomes of utilizing just light-sensing gadgets alone for the light tracking bot using advanced color detection algorithm. The algorithm would help the bot in sensing the color of light and act accordingly, for instance green color to proceed, red color to stop. This particular requisition has high scope in real time application over the emergent underground transportation system; speculating on how the emerging innovative advances fit to the fiddle urban areas of the 21st century. 2020, Springer Nature Switzerland AG. -
Lilliputians' dilemma: Survival strategies of small states in South Asia
One of the most striking features of contemporary international politics is asymmetrical power relations among states. With the birth of the United Nations, the sovereign equality of the states began to be fully respected, at least in principle. During the Cold War, small states gained much importance when superpowers tried to co-opt them. Small states situated in specific geo-strategic areas were seen as 'assets' or 'trouble spots' depending on their ideological leaning. 1 Given the fact that small states constitute majority in terms of numbers in global politics, but at the same time facing numerous politico-security and economic issues, several interesting questions arise. Do small states feel secured in regional and international politics dominated by big and middle powers? What survival strategies do they adopt to secure themselves? How does this translate to South Asian region that is commonly viewed as 'India-dominant'? Do small states of South Asia follow similar or differing strategies to safeguard their security? South Asia offers a right case to look at the issue of survival strategies of small states in regional politics from both theoretical and empirical contexts. 2024 selection and editorial matter, Adluri Subramanyam Raju and R. Srinivasan. All rights reserved.