Bacterial Pigments as Antimicrobial Agents
In this chapter, we discuss various bacterial derived secondary metabolites pigments which has antimicrobial properties. Though these metabolites were identified more than several decades ago, attention into their bioactivities has emerged in the last few decades. Their increasing acceptance is an outcome of their cost-effectiveness, biodegradability, noncarcinogenic property, and eco-friendly characteristics. This chapter has made an attempt to take an in-depth observation into the current bacterial derived pigments and their bioactivity against various microorganisms. 2024 selection and editorial matter, Mohammed Kuddus, Poonam Singh, Raveendran Sindhu and Rachana Singh; individual chapters, the contributors.
Madhavan A.; Arun K.B.; Reshmy R.; Abhinand K.; Menon A.M.; Nair B.G.; Sindhu R.; Kuriakose L.L.; Awasthi M.K.; Pandey A.; Binod P.
Microbial Pigments: Applications in Food and Beverage Industry, pp. 150-157.
https://doi.org/10.1201/9781003353980-9 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184528915&doi=10.1201%2f9781003353980-9&partnerID=40&md5=2dab4684e5fcabd3f9ae9ab04265c584
Madhavan A., School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, Kollam, India; Arun K.B., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Reshmy R., Department of Science and Humanities, Providence College of Engineering, Kerala, Chengannur, India; Abhinand K., School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, Kollam, India; Menon A.M., School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, Kollam, India; Nair B.G., School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, Kollam, India; Sindhu R., Department of Food Technology, T K M Institute of Technology, Kerala, Kollam, India; Kuriakose L.L., Department of Food Technology, T K M Institute of Technology, Kerala, Kollam, India; Awasthi M.K., College of Natural Resources and Environment, Northwest A & F University, Shaanxi, Yangling, China; Pandey A., Center for Innovation and Translational Research, CSIR-Indian Institute of Toxicology Research, Lucknow, India, Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Uttarkhand, Dehradun, India, Centre for Energy and Environmental Sustainability, Uttar Pradesh, Lucknow, India; Binod P., Microbial Processes and Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Kerala, Trivandrum, India
Eradication of Global Hunger at UN Initiative: Holacracy Process Enriched byHuman Will and Virtue
Holacracy; Hunger; Poverty; Sustainable Development Goals (SDGs); UN (United Nations)
The researchers have directed their attention to the UNs 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs), with a specific focus on two critical objectives: hunger and poverty alleviation. While the UN has been vocal about eradicating hunger and poverty, the researchers believe that a fundamental shift in human perspective is needed. They propose a novel approach rooted in holacracy to revolutionize food production, distribution, and management. At the core of their proposal lies the ancient Indian principle, Vasudhaiva Kutumbakam, which translates to The World Is One Family. While it may seem utopian, the researchers see it as a reachable goal through holacracy. Their hypothesis centres on producing food for all and collectively utilizing it, transcending national boundaries and individual interests. The researchers advocate for a transformation in the way the UN operates by embracing holacracy as a practical social technology rather than a mere concept. Holacratic organizations, they argue, have the potential to remove barriers obstructing progress. The implementation of their vision begins with the UN functioning as a global nerve centre for data, with its 193 member nations acting as equal and interdependent contributors. This Centre would display the worldwide food landscape and foster a moral and ethical awakening, emphasizing the shared responsibility for all humanity. Real-time data on food availability, supply chains, and consumption would be accessible on a public website. Holacracy, they contend, should inspire individuals to prioritize love for humanity as a panacea. Power circles interconnect to collaboratively address issues. The UN could serve as a catalyst for this transformation. The knowledge nerve centre would provide critical data on arable land, water resources, and supply chain infrastructure to facilitate problem-solving at various levels. Timely responses and actions would be driven by the principles of holacracy and advanced digital technologies, addressing concerns hindering the achievement of UN goals. This data-driven approach, coupled with actionable plans, aims to eliminate food shortages and subsequently combat poverty and hunger worldwide. In conclusion, the researchers envision a future where holacracy and a shared sense of responsibility propel humanity towards ending hunger and poverty, with the UN playing a pivotal role as a catalyst for change and a provider of essential data and guidance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Green Energy and Technology, Vol-Part F2272, pp. 477-494.
Springer Science and Business Media Deutschland GmbH
Nair R., School of Arts and Humanities, Christ University, Bangalore, India; Joy J., School of Business and Management, Christ University, Bangalore, India
Reshaping the Education Sector of Manipur Through Blockchain
Blockchain; Education; Manipur; Sustainable future; Technology
The use of technology in education has been over a century, yet blockchain is in its nascent stage in education. Over the years, technology has enhanced the teaching-learning method, and blockchain can improve even in the administrative section of education. The states of North East, India, in general, lag behind the rest of Indian states in almost all sectors, and the lack of transparency in the administrative sector significantly contributed to it. If blockchain is incorporated into the education department at the administrative level, it could pave the way for a faster, more transparent, and smoother administration. Given the harsh reality that transportation is hard and expensive, a standardised blockchain can alleviate the need to be physically present for any academic-related activity. The attempt of this study would be to show how blockchain can be beneficially used even at the institutional level, where unabated printing could be reduced and adopting to e-paper be maximised. Besides the educational institutions, the administrative sector in education could profitably use them in offices, thereby avoiding red tape for the common people. The chapter points out how blockchain can be a trailblazer in reshaping the education sector in Manipur. Educational institutions must take the lead towards a sustainable future, and blockchain can aid in bringing some visible change in the educational sector. This chapter uses an interdisciplinary approach to substantiate the importance and need for blockchain in the context of Manipur to change for a sustainable future. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Kaje B.K.; Gangmei N.; Jacob H.D.; Shimray N.A.
Signals and Communication Technology, Vol-Part F2283, pp. 167-179.
Kaje B.K., Christ University, Bangalore, India; Gangmei N., Christ University, Bangalore, India; Jacob H.D., OPJS University, Rajasthan, Churu, India; Shimray N.A., OPJS University, Rajasthan, Churu, India
EFFECTIVENESS OF COGNITIVE BEHAVIOURAL THERAPY FOR ADULTS WITH DEPRESSION AND ANXIETY DURING COVID-19: A Systematic Review of Randomised Controlled Trials
Introduction: The COVID-19 pandemic has forced the administration of Cognitive Behavioural Therapy (CBT) either face-to-face or online. This systematic review aims to assess the effectiveness of CBT and Internet-Delivered CBT (iCBT) in treating depression and anxiety disorders during the COVID-19 outbreak. Methods: Three independent reviewers searched the Web of Science, PubMed, Cochrane Library, and Clinical Trial Databases using specific search phrases. PubMed searches included Cognitive Behavioural Therapy/Intervention and COVID-19 and 2019 Coronavirus Disease or 2019-nCoV, internet-administered/internet-based cognitive behavioural therapy, CBT, cognitive behavioural treatment. Two independent reviewers evaluated the risk of bias at the study level, with disagreements settled through discussion with other research team members. The study findings were reported as per the PRISMA guidelines. Results: Thirty-one studies met the inclusion criteria, and 17 were randomised controlled trials. The studies demonstrated that CBT and iCBT effectively treated depression and anxiety disorders during the COVID-19 pandemic. However, a hybrid CBT modality was more beneficial from a long-term perspective. Conclusion: The findings suggest that CBT and iCBT effectively treat depression and anxiety disorders during the COVID-19 pandemic. However, further research is needed to establish these interventions long-term effectiveness and identify the optimal mode of delivery for different populations. 2024 selection and editorial matter, Dr Rajesh Verma, Dr Uzaina, Dr Tushar Singh, Dr Gyanesh Kumar Tiwari, and Prof Leister Sam Sudheer Manickam.
Joshi G.; Joshi C.; Tushir B.; Srivastava A.
Exploring the Psycho-Social Impact of Covid-19: Global Perspectives on Behaviour, Interventions and Future Directions, pp. 59-88.
Joshi G., Christ University, Delhi, India; Joshi C., Jamia Millia Islamia University, Delhi, India, 21K School, Karnataka, Bangalore, India; Tushir B., Christ University, India; Srivastava A., O.P. Jindal Global University, India
Beyond Teacher Quality: Understanding the Moderating Role of Infrastructure in Student Learning Outcomes in Secondary Education
Bihar and Kerala comparison; Moderating effect of infrastructure; School infrastructure; Student outcome; Teacher quality
Education is an essential resource for individuals and societies, and it plays a significant role in shaping the future of any nation. Depriving a generation of young children of their basic right to quality education can easily be regarded as the highest form of injustice in a society. Bihar, which was once the epitome of education and knowledge across the world, is now counted among the states with the lowest literacy rates and the poorest educational infrastructure. While a list of reasons can be enumerated behind this downfall, including historic and social reasons, it is prudent to act on those that we can effectively alter and improve upon, such as infrastructure and teaching quality. The quality of education provided to students is influenced by various factors, such as infrastructure, teacher quality, and student-teacher relationships. This study explores the moderating effect of infrastructure on the relationship between teacher quality and student outcome in secondary education in Bihar, mapping an intriguing contrast with Kerala, the state with the highest literacy rate in India. With the help of a simple moderation analysis and drawing on the resource dependency theory, our findings indicate that the moderation effect of infrastructure on student outcome is stronger in Bihar than in Kerala. This study highlights the urgent need to prioritise consolidating and enhancing the quality of education in schools in Bihar rather than adding up a number of concrete blocks. 2024 Patliputra School of Economics.
Development with Justice: Te Bihar Experience, pp. 57-69.
Singh A., Christ University, Bangalore, India; Rama S., Indian Institute of Management, Bodh Gaya, India
Transforming Industry 5.0: Real Time Monitoring and Decision Making with IIOT
This chapter explores the transformative potential of Industry 5.0 by leveraging real-time monitoring and decision-making capabilities through the use of IIoT dashboards. It extends in examining how IIoT dashboards enable organizations to gain real-time insights into their operations, facilitating data-driven decision-making and improving overall efficiency. By embracing IIoT dashboards, businesses can effectively transform Industry 5.0, unlocking new levels of productivity, agility, and competitiveness. In this chapter, important challenges such as data integration, data security, scalability, and user experience are identified. It highlights key considerations for implementing IIoT dashboards and offers practical methods for successful adoption of this technology. Remarkable achievements in implementing this technology include applications such as crude oil production with IIoT and edge computing, as well as IIoT-enabled smart agriculture dashboards. Adopting IIoT dashboards may involve initial costs, but they offer long-term benefits and cost-effectiveness, particularly in the era of Industry 5.0 transformation. 2024 selection and editorial matter, C Kishor Kumar Reddy, P R Anisha, Samiya Khan, Marlia Mohd Hanafiah, Lavanya Pamulaparty and R Madana Mohana.
Sustainability in Industry 5.0: Theory and Applications, pp. 76-106.
Arputharaj J.V., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Pal S.K., Department of Biological Sciences, Skyline University, Kano, Nigeria
Machine Learning in Cyber Threats Intelligent System
Cybercriminals disrupt services, exfiltrate sensitive data, and exploit victim machines and networks to perform malicious activities against organizations. A malicious adversary seeks to steal, destroy, or compromise business assets that have a specific financial, reputational, or intellectual value. As a result, organizations are complementing their perimeter defenses with threat intelligence platforms to address these security challenges and eliminate security blind spots for their systems. Any type of information useful for identifying, assessing, monitoring, and responding to cyber threats is considered cyber threat intelligence. Organizations can benefit from increased visibility into cyber threats and policy violations. An organizations threat intelligence allows them to prevent or mitigate various types of cyberattacks. The use of machine learning and artificial intelligence is a key component of cybersecurity conflict, which together allows attackers and defenders to function at new speeds and scales. In spear-phishing attacks, relatively frivolous machine learning algorithms have been used to overwhelming effect as adversarial artificial intelligence. This chapter discusses the various cyber threats, cyber security attack types, publicly available datasets for research work, and machine learning techniques in cyber-physical systems. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.
Artificial Intelligence for Cyber Defense and Smart Policing, pp. 1-20.
https://doi.org/10.1201/9781003251781-1 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190232809&doi=10.1201%2f9781003251781-1&partnerID=40&md5=ec3bada096b848bc8f7a6e2ff5b650c8
Jaisingh W., Presidency University, Bengaluru, India; Nanjundan P., Department of Data Science, Christ University, Pune, Lavasa, India; George J.P., Department of Data Science, Christ University Delhi NCR Campus, India
The Women Leadership: A Catalytic Role of Digital Divide Through Digital Ecosystem
Digitalization; Leadership; Organization; Technology
The digitalization of the macro environment of an organization and digital upskilling and digital capital formation in the micro level of human capital paves women an opportunity to ladder up in the organization in various job roles leading to women leadership. The sociodemographic, psychological, socioeconomic, and cultural factors to the digital divide predominantly determine digital capital formation. Every attempt of women to surpass the digital divide obstacle to digital capital formation enables women capital to leadership characteristics. The study proposes a conceptual framework by extricating the past scholarly works on digital divide, digital capital, technology leadership, and women leadership. The preferences and choices of women leading to leadership skills through technology by encapsulating digital capital formation are meritorious in the research inquiry. The individual factors and organization factors are taken to the moderating variables in the association of digital capital to the women leadership. The study finds the need of ICT and digital upskilling among the women professionals in industry and catalytic role of digital capital formation by surpassing the digital divide. The empirical study on the concept formulation is highly recommendable for the future study. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Thomas J.V.; Mallika Sankar M.; Varghese J.P.; Kumar A.
Technical and Vocational Education and Training, Vol-39, pp. 513-524.
Thomas J.V., Christ (Deemed to be University), Bengaluru, India; Mallika Sankar M., Christ (Deemed to be University), Bengaluru, India; Varghese J.P., Christ (Deemed to be University), Bengaluru, India; Kumar A., Kristu Jayanti College Autonomous, Bengaluru, India
Voices of the Future: Generation Zs Views on AIs Ethical and Social Impact
Data security; Ethics; GenZ; Perception; Regulatory frameworks; Social impact
As artificial intelligence (AI) becomes increasingly integral to modern society, its profound implications are coming to the forefront of discussions. This research paper investigates the perspective of Generation Z on the multifaceted societal and ethical impacts of AI. Gen Z is the first generation to fully embrace AI across all facets of life. Therefore, understanding their attitudes, concerns, and expectations towards AI is imperative for cultivating a responsible, adaptable, and ethically conscious society in the AI-driven era. This study addresses a significant research gap by exploring Gen Zs perceptions of the challenges associated with AI, such as issues related to privacy, data security, transparency, bias, public fear and more. It also examines the impact of AI on employment dynamics, specifically on job displacement and the necessity for reskilling in the face of AI-driven automation. The paper adopts a global perspective, acknowledging the variations in perception influenced by cultural, economic, and historical factors. Leveraging a sample size of approximately 200250 respondents aged 1825years, the research aims to provide a comprehensive view of Gen Zs viewpoints on AIs ethical and societal ramifications. Findings emphasize the need for transparent and accountable AI systems, as Gen Z is uncomfortable with the ambiguity in AI algorithms. Concerns about privacy and data security highlight the necessity for robust safeguards. They also advocate for strategies to address job displacement and ensure harmonious coexistence between humans and AI. In education, Gen Z sees AI as transformative, endorsing personalized learning. They stress the importance of regulatory frameworks to combat AI bias. They recognize AIs potential to enhance human connections and combat social isolation. The studys findings contribute to policy discussions, educational strategies, and business practices, offering insights into how to harness AIs benefits while mitigating its potential pitfalls. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Gupta A.; Pranathy R.S.; Binny M.; Chellasamy A.; Nagarathinam A.; Pachiyappan S.; Bhagat S.
Studies in Systems, Decision and Control, Vol-223, pp. 367-386.
Gupta A., School of Business and Management, BBAH, CHRIST(Deemed to be University), Bengaluru, India; Pranathy R.S., School of Business and Management, BBAH, CHRIST(Deemed to be University), Bengaluru, India; Binny M., School of Business and Management, BBAH, CHRIST(Deemed to be University), Bengaluru, India; Chellasamy A., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India; Nagarathinam A., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India; Pachiyappan S., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India; Bhagat S., School of Business and Management, CHRIST(Deemed to be University), Bengaluru, India
Green Data Centers: A Review of Current Trends and Practices
Artificial intelligence; COVID-19; Ethics; Health care; Neural networks
A green data center is a facility that makes use of eco-friendly techniques and technologies to lessen its carbon footprint and environmental impact. A data center can consume as much electricity as a small city and contains thousands of servers. These server farms require an enormous amount of processing power to operate, which presents numerous difficulties, including high energy costs, greenhouse gas emissions, backups, and recovery. This paper clarifies the various green data center best practices, including energy efficiency, cooling systems, renewable energy, sustainable building techniques, and carbon footprint. The need for green data centers in todays internet, commercial, financial, and business applications is also covered in the paper. The reality and myths of green data centers are alsoexamined. The paper delves into the metrics for each characteristic used to gauge how green and effective data centers are. The discussion has concluded with case studies of companies that have implemented green data centers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Nagarathinam A.; Chellasamy A.; Antonysamy K.; Saravanan V.; Gopalakrishnan M.
Studies in Systems, Decision and Control, Vol-223, pp. 251-264.
Nagarathinam A., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Chellasamy A., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Antonysamy K., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Saravanan V., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Gopalakrishnan M., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India
Application of AI-Based Learning in Automated Applications and Soft Computing Mechanisms Applicable in Industries
The term artificial intelligence is used to describe a method through which computers may teach themselves new skills and develop themselves, without the help of humans or any predetermined instructions. Machines are fed data and trained to look for patterns; these patterns are then used as templates for further learning. They get the agency to choose their own actions and alter their habits accordingly. The term soft computing refers to a group of computational techniques that draw inspiration from both AI and natural selection. Solutions to difficult real-world situations that have no simple computer solution are provided, and they are both practical and cost-effective. Soft computing is an area of study in mathematics and computer science that has been around since the early 1990s. The idea for this project sprang from the fact that people can think of solutions that are close to the ones in the actual world. It is via the use of approximations that the science of soft computing is able to solve difficult computational challenges. Industrial automation is used by a diverse variety of industries and companies to improve the effectiveness of their processes by leveraging a number of technology developments. Many routine tasks are being changed by industrial applications. Industrial automation that reduces breakdowns and repairs quickly might help a business save money. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors.
Kumar B.M.; Talukdar V.; Khan H.; Talukdar S.B.; Koujalagi A.; Kumar R.G.; Gupta A.
Robotics and Automation in Industry 4.0: Smart Industries and Intelligent Technologies, Vol-45689, pp. 110-131.
Kumar B.M., Department of MCA, Dayananda Sagar College of Engineering, Bengaluru, India; Talukdar V., Kaziranga University, Jorhat, India; Khan H., Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai, India; Talukdar S.B., School of Computer Science and Engineering, VIT Bhopal, Bhopal, India; Koujalagi A., Department of Computer Science and Engineering, Godavari Institute of Engineering and Technology (Autonomous), Rajamahendravaram, India; Kumar R.G., Department of Computer Science and Engineering CHRIST, (Deemed to be University), School of Engineering and Technology, Kengeri Campus, Bangalore, India; Gupta A., Department of Computer Science and Engineering, Vaish College of Engineering, Rohtak, India
AI in Forensics A Data Analytics Perspective
Artificial intelligence (AI) is rapidly becoming the most significant science in all areas of life, and forensic science is one of the fields benefiting from it. Forensics can be defined as a study of crime via the use of scientific methods and techniques. Around the globe, governments invest a large amount of money in developing forensics techniques to prove criminal activities and track criminals effectively. It is now becoming a practice to involve artificial intelligence in supporting the forensic application. It involves a smart and intelligent examination of massive volumes of very complicated data. As a result, AI is becoming an excellent solution for addressing many of the complicated issues that now exist in forensics. For example, AI proves more effective in skeleton-based human identification compared to the traditional skull/skeleton superimposition method. AI can be used to pool meta-data generated from multiple sources connected to forensic science and do a meta-analysis on it to simplify complex data. AI finds patterns and uses them to identify/recognize/predict something that is required in crime tracking or criminal/victim recognition. Complex analytics and probabilistic reasoning are used to recognize patterns. Among the most crucial things to forensic science is the identification of specific sorts of patterns in enormous amounts of data. This could include image pattern recognition, in which the program attempts to distinguish between distinct components of an image or a person. Other types of pattern recognition, such as finding patterns in text, may also exist. Artificial intelligence aids in the more accurate recognition of such patterns in complex data. This chapter introduces the reader to several aspects of artificial intelligence that can be used in forensics. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.
Artificial Intelligence for Cyber Defense and Smart Policing, pp. 41-60.
Jacob L., Department of Data Science, Christ University, Pune, Lavasa, India; Thomas K.T., Department of Data Science, Christ University, Pune, Lavasa, India; Savithri M., Department of Data Science, Christ University, Pune, Lavasa, India
Big Data Paradigm in Cybercrime Investigation
Big Data is a field that provides a wide range of ways for analyzing and retrieving data as well as hidden patterns of complex and large data collections. As cybercrime and the danger of data theft increase, there is a greater demand for a more robust algorithm for cyber security. Big Data concepts and monitoring are extremely useful in discovering patterns of illegal activity on the internet and informing the appropriate authorities. This chapter investigates privacy and security in the context of Big Data, proposing a paradigm for Big Data privacy and security. It also investigates a classification of Big Data-driven privacy and security of each algorithm. In this section, we first define Big Data in the contexts of police, criminology, and criminal psychology. The chapter will look at how it might be used to analyze concerns that these paradigms confront carefully. We provide a conceptual approach for assisting criminal investigations, as well as a variety of application situations in which Big Data may bring fresh insights into detecting facts regarding illegal incidents. Finally, this chapter will explore the implications, limits, and effects of Big Data monitoring in cybercrime investigations. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.
Harchandani R.; Bansal P.; Jain S.; Sondhi J.K.; Jacob L.
Artificial Intelligence for Cyber Defense and Smart Policing, pp. 91-109.
https://doi.org/10.1201/9781003251781-7 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190227294&doi=10.1201%2f9781003251781-7&partnerID=40&md5=fb9d42bde369e439551e1b7adacd915d
Harchandani R., Department of Data Science, Christ University, Pune, Lavasa, India; Bansal P., Department of Data Science, Christ University, Pune, Lavasa, India; Jain S., Department of Data Science, Christ University, Pune, Lavasa, India; Sondhi J.K., Department of Data Science, Christ University, Pune, Lavasa, India; Jacob L., Department of Data Science, Christ University, Pune, Lavasa, India
Internet of Things-Based Smart Agriculture Advisory System
Computation simulation; Multidimensional data; Smart agricultural system; Smart agriculture; Smart IoT; Computational intelligence
The Internet era provides a lot of automation tools for data analysis, and it is the need of the hour to develop new analytical tools to manage the big data. For task automation, machine learning and expert systems are of primary importance to study the behavior of computer thinking to involve computers in sensible work, known as computational intelligence. The data involves varied formats such as structured, unstructured, as well as semi-structured, and it is an automation tool that uses computational intelligence to extract valid and potential information from the sources. The specific purpose of this proposed work is to meet out computing demands which highly rely on computational intelligence. Computational intelligenceinvolves the design and deployment of an analytical tool for multidimensional data analytics. The proposed integrated framework focuses on multidimensional data analytics, for crop and plant data, especially plants that contain medicinal values and components. This research works main aim is to create a secured data tool for agriculture crop data management through big data (crops and plants) analytics. The data security is enhanced through applied cryptography, and the final phase prediction on crops is done by various machine and deep learning algorithms. The specific objective of this research work is to help farmers in making informed decisions for the enhancement of cultivation and information. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Jeyabalu M.; Ghodi A.S.; Balasubramanian S.; Chinnayan B.; Jayapal J.
Signals and Communication Technology, Vol-Part F2461, pp. 159-177.
Jeyabalu M., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore Yeshwanthpur Campus, India; Ghodi A.S., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore Yeshwanthpur Campus, India; Balasubramanian S., Department of Information Technology, University of Technology and Applied Sciences, AL Mussanah, Oman; Chinnayan B., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore Yeshwanthpur Campus, India; Jayapal J., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore Yeshwanthpur Campus, India
Deep Learning Decision Support Model for Police Investigation
A police investigation is an exciting task with many complicated processes that may or may not succeed. However, it is the sole duty of a police officer to understand the crime scene, reconstruct the event and predict the criminal with accuracy. There are various methods for interrogations, predictions, and confirmation after identifying a person as a criminal or upon concluding their actions as a criminal act. However, we can see massive growth in crime rates every day. This massive growth rate makes conventional prediction or analysis very strenuous. In such times we can use or take the help of deep learning and machine learning methods for crime analysis and suspect prediction by identifying the data points in a set. This prediction methodology is known as intelligence analysis which simulates the dataset to draw a connection or pattern collectively from millions of data points to identify the instigator and linkman. This chapter will summarize the uses of deep learning and artificial intelligence in a decision support model for police investigation. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.
Devan A.M.; Raghul V.; Dhasmana U.; Rath A.; Jacob L.
Artificial Intelligence for Cyber Defense and Smart Policing, pp. 76-90.
Devan A.M., Department of Data Science, Christ University, Pune, Lavasa, India; Raghul V., Department of Data Science, Christ University, Pune, Lavasa, India; Dhasmana U., Department of Data Science, Christ University, Pune, Lavasa, India; Rath A., Department of Data Science, Christ University, Pune, Lavasa, India; Jacob L., Department of Data Science, Christ University, Pune, Lavasa, India
Computer-based Intelligence and Security
There is a massive increase in the incidence of cyberattacks day by day in the modern enterprise environment. Although humans are behind this task due to the rapid growth in the incidence human intervention is unable to control this. Therefore, something more than human intervention is required to have a check over it. With cyberattacks evolving at a rapid pace and with the increase in the use of devices in todays world, Artificial Intelligence (AI) and Machine Learning (ML) can help to have a check over cybercrime incidences, automate the process of detection of threat, and handle these in a better way as compared to the conventional methods used for controlling cybercrime and cyberattack. AI and ML has shown good results in data information security as these technologies are capable of analyzing a large and wide variety of data and can track threats related to cyberattacks that may cause phishing attacks. As these technologies are capable of learning and improving from past experiences, they can even predict and tell the new variety of attacks that may occur in the coming days. This chapter describes the use of AI in controlling cyberattacks and cybercrime and the expert views on this matter. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.
Tanwar S.; Vijayalakshmi S.; Durgadevi P.; Girija R.
Artificial Intelligence for Cyber Defense and Smart Policing, pp. 160-171.
Tanwar S., Manipal University, Jaipur, India; Vijayalakshmi S., Department of Data Science, Christ University, Pune, Lavasa, India; Durgadevi P., GITAM University (Deemed to be University), Bengaluru, India; Girija R., Manav Rachna University, Faridabad, India
Beyond Humour: How Memes Shape Brand Associations and Drive Purchase Choices
Consumer purchase; Meme branding; Meme marketing
Memes are the perfect marketing tools a brand can use while promoting their products or services. In this ever-changing consumer preferences memes are the convenient marketing tools that a consumer pays attention, the usage of memes has become a completely modern approach for brands to seek the attention of consumers. The study examines the impact of internet meme that spreads through social media which catches the consumer attention and improves the intention of purchasing products and also learn about the brands. A structured questionnaire and convenience sampling technique are designed to collect data from frequent internet users who are active in social media from Gen-z and have at least a little knowledge on meme marketing, and responses yielded were 353. This paper gives a general study of meme marketing and if the consumer brand relatability and purchase decisions are affected by meme marketing. The findings state that there is a relationship between branding memes and consumer brand relatability and using the memes in social handles affect the consumer behaviour however there is a discomfort among consumers when brands solely use memes for marketing purposes. Also the study found that there is no significance between Gender and meme motivation into buying products. Thus the study contributes to understand the consumer behaviour, purchase intention and likeliness towards the brands. In addition, the authors contribute to the finding the significance of meme in daily life of a consumer and what type of memes would pursue consumers more towards the brand. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Surya P.M.; Chellasamy A.; Nagarathinam A.; Pachiyappan S.; Deepika S.R.
Studies in Systems, Decision and Control, Vol-223, pp. 341-352.
Surya P.M., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Chellasamy A., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Nagarathinam A., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Pachiyappan S., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India; Deepika S.R., School of Business and Management, CHRIST (Deemed to be University), Bengaluru, India
Phrases that scarcely existed a decade ago are now a part of our day-to-day lifestyle, as criminals use malicious new technologies to commit cyber attacks against businesses, individuals, and governments. These crimes cause serious harm and impose real threats to victims worldwide either physically or virtually. There are no borders in cyberspace. Attacks can come from any place and at any time. Cybercrime can take many forms, but they all have a digital platform/environment in common. It can be done with both good and bad intentions. But, nowadays, the most common types of cybercrime activities such as phishing scams, identity theft, Internet frauds, online intellectual property or patent infringements, online harassment, and cyber stalking are sadly very widespread in todays associated world. Cyber bullying and online harassment activities spread casually in social media posts and comments or through direct messages and also via emails. The main motive of these messages is to threaten either an individual or a group. Such kinds of cybercrime activities are extremely damaging to the victims mental health. Government agencies working to investigate cybercrimes have reported multiple records of victims developing mental illnesses and even ending up committing suicide. On the other hand we have phishing scams, one of the widespread crime activities. Organizations have detected an increase in the ratio of phishing emails to professional emails from unknown or anonymous service providers appending fake attachments and invoices. These files and attachments may contain malicious payloads to scam people and to create a backdoor in that system, so the attacker can gain access to the system anytime and from anywhere without the victims knowledge. This has been considered as one of the major advantages for the attacker. Cybercrimes have not restricted to only these forms of criminal activities. A wide variety of new attacks have been created and have spread all over the world through commonly used platforms such as social media sites, blogs, and news portals. We are living in a digital world where all our activities are being monitored by someone, somewhere - even keystrokes are being monitored using keyloggers. Nothing seems to be secret and protected unless you are tech savvy. National agencies are keeping a close watch on all individual online activities to prevent illegal activities from happening. No longer the delete option is possible in this digital world; rather, only migration of data from one location to another or from a local server to a cloud server is possible. In our day-to-day lives, several new viruses and attack mechanisms are triggered by attackers by following very new tactics with the help of more complex algorithms. So, its time to advance our knowledge on protecting our valuable assets by spending time in learning and following proper online practices. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.
Artificial Intelligence for Cyber Defense and Smart Policing, pp. 21-31.
Gunavathi R., Department of Data Science, Christ University, Pune, Lavasa, India; Bharathi K.M., CSUITE TECH LABS, Tamil Nadu, Chennai, India
Is ESG the Key to Stimulate Financial Performance? An Empirical Investigation
ESG; Financial performance; Nifty 100 ESG index; Nifty 100 index; P/E ratio; ROA; ROCE; ROE
Environmental, Social, and Governance (ESG) principle is a critical framework for businesses and non-business entities. Recently, investors increasingly concentrate on the ethical impact of their investments in addition to financial rewards. The present study outlines links between a companys ESG practices and its financial performance. By means of performance comparison between the Nifty 100 ESG and Nifty 100 Indices within the Indian context, it issuggested that investing in ESG-adopting companies can lead to better financial performance. The study uses statistical analysis to compare the performance of both indices between 2018 and 2022. The analysis includes financial ratios, such as P/E ratio, ROA, ROE, and ROCE. The findings reveal a relatively modest connection between ESG and P/E ratio. The stronger negative correlations between ESG and key financial metrics (ROA, ROE, and ROCE), signifies a more robust trade-off between ESG focus and financial performance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Studies in Systems, Decision and Control, Vol-223, pp. 297-306.
Cherian S., Christ (Deemed to Be University), Bangalore, India; Seranmadevi R., Christ (Deemed to Be University), Bangalore, India
The name Big Data for Security and Intelligence is a method of analysis that focuses on huge data (ranging from petabytes to zettabytes) that includes all sources (such as log files, IP addresses, and emails). Various companies use big data technology for security and intelligence in order to identify suspicious tasks, threats, and security tasks. They are able to use this information to combat cyber-attacks. One of the limitations of big data security is the inability to cover both current and past data in order to be able to uncover identified threats, anomalies, and fraud to keep the n/wsafe from attacks. A number of organizations are addressing rising problems like APTs, attacks, and fraud by focusing on them. More is better than less! The easier it will be to determine. Nevertheless, organizations which utilize big data techniques make sure that privacy and security issues have been resolved before putting their data to use. Because there are so many different types of data stored in so many different systems, the infrastructure needed to analyze big data should be able to handle and support more advanced analytics like statistics and data mining. The one side of the coin is the collection and storing of lots of information; the other side is protecting massive amounts of information from uncertified access, which is very difficult. Big data is commonly used extensively in the improvement of security and the facilitation of law enforcement. Big data analytics are used by the US National Security Agency (NSA) to foil terrorist plots, while other agencies use big data to identify and handle cyber-attacks. Credit card companies use big data analytics tools to detect fraud transactions, while police departments use big data methods to track down criminals and forecast illegal activity. Big data is being used in amazing ways in todays information world, but security and privacy are the primary concerns when it comes to protecting massive amounts of data. Real-time data collection, standardization, and analysis used to analyze and enhance a companys overall security is referred to as Security Intelligence. The security intelligence nature entails the formation of software assets and personnel with the goal of uncovering actionable and useful insights that help the organization mitigate threats and reduce risks. To identify security incidents and the behaviors of attackers, todays analysts use machine learning and big data analysis. They also use this cutting-edge technology to automate identification and security events analysis and to extract security intelligence from event logs generated on a network. This chapter will discuss how Big Data analytics can help out in the world of security intelligence, what the appropriate infrastructure needs to be in order to make it useful, how it is more efficient than more traditional approaches, and what it would look like if we built an analytic engine specifically for security intelligence. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors.
Vijayalakshmi S.; Savita; Durgadevi P.; Shariff A.S.M.
Artificial Intelligence for Cyber Defense and Smart Policing, pp. 61-75.
Vijayalakshmi S., Department of Data Science, Christ University, Pune, Lavasa, India; Savita, School of Engineering & Technology, Maharishi University of Information Technology, Noida, India; Durgadevi P., GITAM University (Deemed to be University), Bengaluru, India; Shariff A.S.M., Galgotias College of Engineering and Technology, India