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#MeToo and Times Up: Slippage of Facework in Malayalam Cinema and Industry
#MeToo and Times Up movements, the collective voice of trauma, solidarity and resistance appropriated world over, impacted India a decade since its inception. In the globalised Indian space, the movements evolved/were transplanted in different realms, lashing against democracys tacit silence. Finding resonance in the Indian cinema industry, many women articulated their trauma and protest in a fraternity, broadminded in spirit, patriarchal at heart. An evolutionary reading of #MeToo and Times Up movements as independent/extension of its predecessor with distinctive focus on Malayalam cinema and industry foregrounds riveting issues. Malayalam cinema industry, a case in point is popular for its projected broadminded outlook through films. Discursive readings unravel the inconsistencies and pluralistic divergent voices in this progressive industry, challenging its liberal positioning. With the tag of an industry receptive to ambient changes, how does its films become reflective or mutually inclusive? How does the industrys facework feed into the apparently challenging onscreen representations vis-a-vis the offscreen power hierarchies? Who delineates the boundary-work within the industry and cinema? A complementary reading of the onscreen versus offscreen negotiations problematises the gendered relationships, sexual economies, collective consciousness structured along multiple tangents. Understanding the ongoing confrontation between artistes associations like Association of Malayalam Movie Artistes (AMMA) and Womens Collective in Cinema, negotiation of inclusivity and extension of solidarity, together with the appropriations and assimilations have opened an alternative space to examine the grey areas dotting the silver screen. 2025 selection and editorial matter, Aysha Viswamohan; individual chapters, the contributors. All rights reserved. -
Decrypting Free Expression: AMMA-WCC Conflict and Comment Culture Rattling the Malayalam Film Industry
The chapter examines the gender-power dynamics in the Malayalam film industry through an analysis of a skit, a YouTube video and trolls related to a recent controversy involving the Association of Malayalam Movies Artistes (AMMA) and the Women in Cinema Collective (WCC). This analysis is supported by an exploration of the historical roots of sexism in the industry and a discussion about how it continues to perpetuate sexism in the industry. The study also investigates the emergence of WCC as a response to the actresss molestation case and the subsequent division within the industry. The research focuses on the Sthree Shaktheekaranam skit performed at AMMAs cultural show, a YouTube video, Oru Feminichi Kadha and a sample of trolls which targeted the WCC and women who refuse to comply with AMMAs patriarchal bias. The chapter analyses the content of these representations, highlighting the power play structuring them. The study sheds light on the contradictions and hypocrisy within the industry and its portrayal of progressive values while perpetuating regressive gender norms. 2024 selection and editorial matter, Francis Philip Barclay and Kaifia Ancer Laskar; individual chapters, the contributors. -
Machine learning and deep learning techniques for breast cancer detection using ultrasound imaging
One of the greatest causes leading to death in women is breast cancer. Its prompt and precise identification can reduce the mortality risk associated with the disease. With the help of computer-based detection, radiologists can identify irregularities. To identify and diagnose numerous illnesses and anomalies, medical photographs are sources of important information. Various techniques help radiographers to examine the internal system, and these techniques have generated a significant amount of attention across several fields of research. Each of these approaches holds a great deal of relevance in many healthcare sectors. Using artificial intelligence techniques, this article aims to present a study that highlights current developments in the detection and classification of breast cancer. The categorization of breast cancer using many medical imaging modalities is discussed in this article. It initially offers a summary of the various machine learning methodologies, followed by a summary of the various deep learning algorithms used in the detection and characterization of metastatic breast tumors. To give an insight into the field, we also give a quick summary of the various imaging techniques. The chapter concludes by summarizing the upcoming developments and difficulties in the diagnosis and classification of breast cancer. 2024 Elsevier Inc. All rights reserved. -
Mediating Effect of Digital Literacy Between Attitude Towards AI and Job Insecurity Among HR Professionals
As businesses continue to incorporate technologies that use AI into a variety of business processes, the connection between employee attitudes towards AI and job insecurity has attracted some attention. However, a critical aspect that has not been covered in the existing literature is the potential mediating role of digital literacy in shaping this relationship. This study investigates the interplay between attitudes towards AI, job insecurity, and digital literacy among HR employees through an online survey. Utilizing established scales, including Attitudes Towards AI (ATAI), Job Insecurity, and Digital Literacy, significant results reveal a substantial mediated relationship. Finding also states a significant impact of attitudes towards AI on job insecurity. Acceptance AI attitude indirectly reduce job insecurity through heightened digital literacy. Also, the pivotal role of digital literacy as a mediator, emphasizing its importance in alleviating job insecurity concerns amidst AI integration. These findings offer practical insights for organizations seeking to foster employee confidence in AI-rich workplaces. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Impact of chitosan and chitosan-based nanoparticles on genetic transformation: an overview
Currently, the primary challenge to modern agricultural science is to meet the global demand for products and ensure food security for the growing population. No doubt the conventional plant breeding techniques and use of agrochemicals to obtain greater crop productivity and variety have been established to fight against biotic and abiotic stress in plants for better yield of agricultural products. The scientific community is exploring better techniques that can satisfy the need of mankind without affecting the ecosystem. Genetic engineering in plants is a recent advancement in the field of plant biotechnology and is more precise and can quickly obtain the desired trait in plants. This technology majorly focuses on improving the crop yield and quality by expressing desirable genes that are responsible for desirable traits such as tolerance to extreme conditions, herbicide, pest resistance, and enhanced secondary metabolite production, which is of medical importance. Nanomaterial-mediated genetic transformation is one reliable and efficient means of crop improvement for sustainable development in agricultural science. This technology has revolutionized modern agriculture as they are used as an effective delivery system to plants. Chitosan-based nanoparticles find their best application as nano-carrier due to their intrinsic properties such as cationic, biocompatible, high loading capacity, and good penetration potential with good release kinetics. Thus chitosan nanoparticles are used to deliver different types of genetic materials such as DNA, RNA, miRNA, siRNA, pDNA, CRISPR/Cas9 single guide RNA for plant transformation. This chapter provides an overview of chitosan nanoparticles as a delivery system and with a focus on their application as a safe genetic delivery system in plants. 2022 Elsevier Inc. All rights reserved. -
Phytochemistry and Pharmacological Activities of Coriandrum sativum L.
Coriandrum sativum L. is a pharmaceutically significant herb that is used for culinary purposes and in herbal formulations. It is an annual herb from the family Apiaceae (Umbelliferae) with unique taxonomic characters. Generally called Dhania or kutumbari, it is cultivated worldwide for its distinct flavors and medicinal properties. Coriander is a rich reservoir of nutrients and significant biochemicals. The phenomenal healing properties of coriander can be attributed to the phytochemicals present in essential oils produced in various parts of the plants, such as leaves, flowers, fruit, and seed. The essential oils are rich in biochemicals like Linalool, (E)-2-decenal, 2-Decenoic acid, camphor, etc. These biomolecules altogether contribute to many pharmacological activities like analgesic, anticancer, anticonvulsant, antidiabetic, anthelmintic, antihypertensive, antimicrobial, anti-mutagenic, antioxidant, anxiolytic, diuretic, hypnotic activity. There are many scientifically proven reports to suggest its importance for usage. The present chapter summarizes the nutrition, biochemicals, and the scientifically proven pharmacological activities of Coriandrum sativum L as well as its cultivation and processing. 2022 by Nova Science Publishers, Inc. -
An Area-Efficient Unique 4:1 Multiplexer Using Nano-electronic-Based Architecture
Quantum dot cellular automata computing methodology is a new way to develop systems with less power consumption. Nanotechnology-based computing technology has enabled the QCA principles to be more relevant with respect to the critical limitations of current VLSI-based design. In this paper, a novel 4:1 multiplexer design based on the QCA concept is presented. As compared to the previous designs of a multiplexer, this novel design is area efficient and power efficient. A five-input majority voter is used for the design of the multiplexer. The 4:1 multiplexer is constructed by making use of three 2:1 multiplexer. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
The role of personal harmony and organisational citizenship behaviour in enhancing job satisfaction of teachers working in Indian higher educational institutions during the COVID-19 catastrophe in the VUCA world
Purpose: The COVID-19 pandemic has been a good example of a Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) world. Higher educational institutions (HEIs) have faced a massive hit because the jobs in this industry have become unexpected. Considering the most valuable assets 'Teachers' crunched in the VUCA crisis, the study intends to determine if personal harmony (PH) and organisational citizenship behaviour (OCB) would enhance teachersjob satisfaction (JS). Design/methodology/approach: Data are collected from the teachers of Indian HEIs and teachers who have experienced the impact of the COVID-19 catastrophe (VUCA). Considering the pandemic restrictions, data have been collected through an online survey (N = 364). Practical Implications: PH is an individual's internal quality and attribute that cannot be developed on force or situational need. Even in an uncertain situation, teachers have tried their best to contribute through professional service. Hence, people who possess PH contribute their best even though unsatisfied with their jobs. Originality/value: This study has focused on finding the relationship between two different variables, PH and OCB (which has not been explored in Asian countries, majorly in India, where it has a vast cultural diversity and structure influencing the educational policies) that hinders the factors influencing JS, where these two variables are highly influenced by hygiene factors such as values, culture, ethical standards, personal belief, leadership styles, and fair treatment showcased by the organisations/institutions. 2024 The authors. Published under exclusive licence by Emerald Publishing Limited. All rights reserved. -
BERT-Based Secure and Smart Management System for Processing Software Development Requirements from Security Perspective
Software requirements management is the first and essential stage for software development practices, from all perspectives, including the security of software systems. Work here focuses on enabling software requirements managers with all the information to help build streamlined software requirements. The focus is on ensuring security which is addressed in the requirements management phase rather than leaving it late in the software development phases. The approach is proposed to combine useful knowledge sources like customer conversation, industry best practices, and knowledge hidden within the software development processes. The financial domain and agile models of development are considered as the focus area for the study. Bidirectional encoder representation from transformers (BERT) is used in the proposed architecture to utilize its language understanding capabilities. Knowledge graph capabilities are explored to bind together the knowledge around industry sources for security practices and vulnerabilities. These information sources are being used to ensure that the requirements management team is updated with critical information. The architecture proposed is validated in light of the financial domain that is scoped for this proposal. Transfer learning is also explored to manage and reduce the need for expensive learning expected by these machine learning and deep learning models. This work will pave the way to integrate software requirements management practices with the data science practices leveraging the information available in the software development ecosystem for better requirements management. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Application of machine intelligence-based knowledge graphs for software engineering
This chapter focuses on knowledge graphs application in software engineering. It starts with a general exploration of artificial intelligence for software engineering and then funnels down to the area where knowledge graphs can be a good fit. The focus is to put together work done in this area and call out key learning and future aspirations. The knowledge management system's architecture, specific application of the knowledge graph in software engineering like automation of test case creation and aspiring to build a continuous learning system are explored. Understanding the semantics of the knowledge, developing an intelligent development environment, defect prediction with network analysis, and clustering of the graph data are exciting explorations. 2021, IGI Global. -
Computational statistics of data science for secured software engineering
The chapter focuses on exploring the work done for applying data science for software engineering, focusing on secured software systems development. With requirements management being the first stage of the life cycle, all the approaches that can help security mindset right at the beginning are explored. By exploring the work done in this area, various key themes of security and its data sources are explored, which will mark the setup of base for advanced exploration of the better approaches to make software systems mature. Based on the assessments of some of the work done in this area, possible prospects are explored. This exploration also helps to emphasize the key challenges that are causing trouble for the software development community. The work also explores the possible collaboration across machine learning, deep learning, and natural language processing approaches. The work helps to throw light on critical dimensions of software development where security plays a key role. 2021, IGI Global. -
Community-based educational intervention on emotion regulation, self-esteem, and behavioural problems among school children
Recently, there has been a trend where higher education institutions are designing and implementing community-based educational interventions for underprivileged children in the community. It is important to understand whether these interventions are useful to the children in improving their psychosocial development. In this chapter, the author discusses the learnings from an explanatory sequential mixed methods study which aimed at assessing the impact of community educational intervention provided by a higher educational institution on self-esteem, emotional regulation and bbehavioralproblems among adolescents in rural Karnataka. The study included 250 adolescents who were beneficiaries of community educational intervention and another 250 who were non-beneficiaries. Besides this, the chapter also highlights the qualitative results grounded in the focus group discussions to understand the stakeholder's perspective on community educational interventions. Finally, the author demonstrates the processes and mechanisms of change and presents a critical discussion from the quantitative and qualitative data analytic lens. The author anticipates that community educational interventions provided by higher educational institutions are extremely impactful. Several critical factors of stakeholders, institutional, and rural communities might bring change and sustainability in benefits among rural adolescents. 2024 Nova Science Publishers, Inc. -
Revolutionizing the financial landscape: A review on human-centric AI thinking in emerging markets
The emergence of Industry 4.0 has transformed the financial landscape by integrating unconventional technologies and artificial intelligence (AI) into consumer interactions. This chapter explores the evolving paradigm of human-centric AI-thinking in the context of emerging customer interactions in making financial decisions. The review analyses the opportunities and the challenges that arise from the integration of AI tools and human-centric approaches in addressing the diverse needs and behaviours of consumers within emerging financial markets. More specifically, the review critically examines the utilization of AI-driven technologies, such as predictive analytics, natural language processing (NLP), and machine learning algorithms, in customising the financial services to cater the emerging-market consumers. Moreover, the current study explicates how AI enables personalized customer interactions, risk assessments, and ethical decision making and financial inclusion strategies while considering the socioeconomic and cultural landscapes. The study has focussed on addressing the concerns related to data privacy, risk assessment, and transparency towards AI-powered financial solutions with ethical standards. Through an exhaustive analysis of current trends, and empirical evidence from the existing literature, this review highlights the inevitability of human-centric AI-thinking approach towards financial services decision making. It emphasizes the importance of congruent AIdriven financial solutions in the context of banking where the determinants such as empathy, financial literacy, ethical considerations, and human values plays a significant role in finding the financial services in emerging markets. This research explores the challenges and prospects and has made commendations to all the major stakeholders such as industry stakeholders, policymakers, practitioners, customers, and service providers to create a dynamic financial landscape of Industry 4.0 in AI technologies that embrace a human-centric ethos to meet the evolving needs of consumers within emerging financial ecosystems. 2024, IGI Global. All rights reserved. -
Impact of Blockchain Technology in the Healthcare Systems
The healthcare industry is one of the most important industries in the world which is in dire need of a restructuring process because of its poor and outdated techniques of data management. Healthcare system has adopted a centralized environment and deals with a lot of intermediaries which makes it prone to issues of single point of failure, lack of traceability of transactions, and privacy issues such as data leakage. Blockchain is a relatively new technology which is able to tackle the obsolete methods and practices existing in the healthcare industry. In this chapter, we analyzed the applications of blockchains in the healthcare industry which can solve the issues prevalent in the healthcare industry. The aim of this chapter is to reveal the potential benefits that comes from using blockchain technology in the healthcare industry and identify the various challenges that this technology has. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Bibliometric analysis of the impact of blockchain technology on the tourism industry
The tourism sector is one of the world's fastest-expanding industries. Because of the benefits, it provides to individuals and organizations, the tourism sector has attracted a lot of attention throughout the years. But because of its poor and obsolete data management techniques, this industry is in desperate need of reform. Blockchain technology is one method for managing and exploring data relevant to the tourism industry. This study used bibliometric methods to analyze the impact of blockchain technology on the tourism sector from 2017 to 2022. The publications were extracted from the dimensions database, and the VOS viewer software was used to visualize research patterns. The findings provided valuable information on the publication year, authors, author's country, author's organizational affiliations, publishing journals, etc. Based on the findings of this analysis, researchers may be able to design their studies better and add more insights into their empirical studies. 2024 Srinesh Thakur, Anvita Electronics, 16-11-762, Vijetha Golden Empire, Hyderabad. -
Graphene quantum dots: Promising catalysts for electrocatalytic water splitting
In recent times, graphene quantum dots have attracted attention from both academia and industry due to their low cost, non-toxicity, abundance, inertness, stability, photoluminescence, and ease of functionalization. Graphene quantum dots are doped with heteroatoms and modified structurally with metals/metal oxides to form composites that find immense application in catalysis. Electrocatalytic water splitting is an energy efficient route for oxygen evolution, hydrogen evolution, and oxygen reduction reactions. Graphene quantum dots based composites have been extensively employed for electrocatalytic water splitting applications, with remarkable results. This chapter focuses on electrocatalytic applications of modified graphene quantum dots in water splitting. 2024 Nova Science Publishers, Inc. All rights reserved. -
Rational Designing of Ni-Ag/C Bimetallic Nanoparticles
Bimetallic nanoparticles have been found to show improved properties due to the synergistic effect between the incorporated metals as a result of electronic charge transfer between them. The importance of using bimetallic particles lies in the high selectivity that they offer. Ni being a reactive metal, was doped with Ag, a highly selective host. In this study, Ni-Ag bimetallic nanoparticles supported on carbon have been synthesized by co-impregnation by using nickel (II) nitrate and silver nitrate as precursors. The catalyst is characterized using XRD, FTIR, DLS, Zeta potential, EDX, SEM, and TEM. The scope of this synthesized catalyst can be extended to several reactions like CO2 reduction reaction, hydrogenation, and industrially important organic reactions. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Fluorescent carbon nanoparticles for catalytic and photocatalytic applications
In the present times, catalysis is ubiquitous in chemical processes. Catalysts range from macromolecules consisting of enzymes to nanoparticles, including metals/metal oxides and composite materials. Due to their harmlessness, biocompatibility, high stability, versatility, and ease of functionalization, carbon nanomaterials (CNMs) which are fluorescent in nature, are used extensively for catalytic applications. Several studies regarding the catalytic applications of CNMs have been reported. These applications range from homogeneous to heterogeneous catalysis, where CNMs are used as supports for metal/metal oxide nanoparticles. Extensive studies on nanocomposites, doping strategies, and their utility in catalysis have been carried out. Carbon-based electrocatalysts find applications in both storage and conservation of energy. The exceptional properties of these materials make them an apt choice for various environment-friendly organic transformations. Photocatalysis is another area in which CNMs have excelled. Photoluminescence, photostability, and electron transfer properties of CNMs make them potent candidates for several photoinduced reactions. Various CNMs, namely graphene, carbon dots, nanotubes, graphitic carbon nitride, fullerenes, and graphdiyne, find applications in medicine, catalysis, sensing, bioimaging, supercapacitors, and many more. This chapter focuses on the catalytic and photocatalytic applications of CNMs. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
AI vs. traditional portfolio management: A study on Indian investors
This research chapter investigates the dynamics between artificial intelligence (AI) and traditional portfolio management strategies, specifically focusing on the attitudes and preferences of investors in the Indian market. The study aims to elucidate the comparative performance, risk-adjusted returns, and behavioral aspects associated with AI-driven portfolio management as opposed to traditional methods. Utilizing a methodology tailored to the unique characteristics of the Indian investment landscape, this research engages investors with varying degrees of experience in the stock market. Through a meticulous collection of data during October and November 2023, employing convenience sampling, the authors explore the factors influencing investor perceptions and decisions in adopting AI-based portfolio management strategies. These findings contribute to the existing discourse by shedding light on the role of trust, subjective norms, perceived usefulness, perceived ease of use, and attitudes as critical variables shaping the adoption of AI in portfolio management. 2024, IGI Global. All rights reserved. -
Intelligent Optimized Delay Algorithm for Improved Quality of Service in Healthcare Social Internet of Things
Internet of Things (IoT) interconnects billions of devices by establishing a network that adheres to International Organization of Standardization (ISO) standards. These devices communicate with each other by sharing data regulated by the application. This is performed to accomplish a task or service that the application demands. The social or human-like behaviors are adapted in the IoT environment forming the Social IoT (SIoT). The SIoT integrates social networks in IoT-connected devices, making them unique and identifiable. Recent advancements in networking, intelligent network management, battery management, remote sensing, sensors, and other related technologies convinced users and designers to adopt IoT even for large-scale applications where the data involved is enormous. Leveraging the advancements in medical IoT, which focuses on healthcare to patients, can improve its service by removing redundant manual processes, long wait times, and providing other automated services. The advancements in real-time healthcare IoT devices and wearables make a strong case for implementing SIoT in the healthcare domain. SIoT in the healthcare domain has the potential to benefit users on a large scale. This chapter comprehends the challenges and solutions of using SIoT in medical and healthcare solutions from a networking quality of service (QoS) perspective. In addition, this chapter compares the intelligent algorithm, which can be used to improve the QoS of SIoT. Achieving higher QoS is necessary for healthcare services, especially while handling data from emergency and intensive care units. These data cannot tolerate errors and delays. Intelligent network management has become unavoidable in the health and medical services to achieve a higher degree of QoS system, which indirectly decreases data transfer time. The data from the sensor devices sent across the network leads to data loss and delay in data transmission due to congestion in the network and gateway devices. The optimized algorithms incorporated with the delay-based algorithm improves the QoS predominantly and reduces the delay in data transfer. Similarly, the particle swarm optimization algorithm allocates resources over the network and dynamically makes the network adapt to increased and reduced data flow, which reduces the delay and improves the QoS. Intelligent optimized delay algorithm (IODA) is proposed to improve the network performance by reducing the delay and using available bandwidth for data transfer in SIoT. 2023 selection and editorial matter, Gururaj H L, Pramod H B, and Gowtham M; individual chapters, the contributors.