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RF-ShCNN: A combination of two deep models for tumor detection in brain using MRI
The tumor in the brain is the reason for jagged cell enlargement in the brain. Magnetic resonance imaging (MRI) is a common scheme to identify tumor existence in the brain. With these MRIs, the medical practitioner can examine and detect the abnormal growth of tissues and corroborate if the brain is influenced by a tumor or not. Due to the appearance of artificial intelligence models, the discovery of brain tumor is performed by adapting different models which thereby help in making decisions and selecting the most suitable diagnosis for patients. The main motivation of this work is to reduce the death rate. If they are not adequately treated, the survival rate of the patient decreases. The correct diagnoses help patients receive accurate treatments and survive for a long time. This paper develops a hybrid model, namely the Residual fused Shepherd convolution neural network (RF-ShCNN) for discovering tumor in the brain considering MRI. Thus, the Adaptive wiener filtering is adapted to filter image-commencing noise. Thereafter, Conditional Random Fields-Recurrent Neural Networks (CRF-RNN) are adapted for segmentation followed by the mining of essential features. Lastly, the features employed in RF-ShCNN for making effective brain tumor detection by means of MRI. Thus, the RF-ShCNN is built by unifying the deep residual network and Shepherd convolution neural network. The hybridization is done by adding a regression layer wherein the regression is fused with Fractional calculus (FC) to make effective detection. The RF-ShCNN provided better accuracy of 94%, sensitivity of 95% and specificity of 94.9%. 2023 -
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Rewriting Epic as a Discourse of the Marginalized: A Study of Mahasweta Devis Select Fiction
The present dissertation engages itself with an analytical study of five short stories by Mahasweta Devi, where she has rewritten episodes from the grand narrative The Mahabharata. Her stories The Five Women, Kunti and Nishadin, Souvali, Draupadi and Bhishmas thirst have been chosen for being studied in order to show how Devi counter narrates the grand epic by looking at the religious battle of Kurukshetra and the canonical epic characters from the subaltern perspective and thus creates a discourse of the marginalised. The critical framework of the study is based on a postcolonial and subaltern study of the texts as the principal characters and Devis themes are anti-canonical and anti- hegemonic. Through Devis feminist rewriting of the ancient text the subaltern sections of the society, who have been marginally represented in the canonical text, have been given a chance to speak. A readers understanding of the epic undergoes a change by going through the rewritten stories which is Devis main intention behind rewriting The Mahabharata. Through her writing she challenges the age old notions and long established truths in the epic for which it has been granted an epic stature. Thus she makes an attempt to lend a voice to the voiceless by this narrative technique and fulfils her social commitment as a journalist and activist writer. -
Reward Based Garbage Monitoring and Collection System Using Sensors
Most of the time in our surroundings we come across the overfilled garbage bins near the lakes. When the bins are full, people just throw the waste here and there, which eventually goes into the lakes and pollutes the water bodies. This is because of improper dumping of garbage that is practiced in our society. With the increase in population, this problem is taking really bad shape. The prime need is to maintain a clean and healthy environment with proper disposal of waste. This paper presents a small effort to reduce this garbage problem. An Android app has been created which keeps on checking whether the dustbin is full. Also, the people will be rewarded for throwing waste into the dustbins. A QR code has been attached to the dustbin which will be scanned for rewarding the people. The dustbins use an IR sensor that detects the receiver of waste in bins. Major part of this proposed system includes the proper working of mobile application and proximity sensors. Arduino is used to maintain the proper connection with sensors and application and that is done by Bluetooth sensor. The main objective of this proposed system is to lure people to put waste into the dustbin along with the contribution towards smart city vision. This paper also gives a brief overview of the technologies and work done so far in this field. 2024 River Publishers. -
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. -
Revolutionizing Road Traffic Management and Enforcement: Harnessing AI, ML, and Geospatial Techniques
This study investigates the synergistic application of Artificial Intelligence (AI), Machine Learning (ML), and Geospatial Technologies in optimizing traffic management systems. Through a mixed-methods research design, it evaluates the potential of these technologies to enhance urban traffic flow and reduce congestion. The research emphasizes the critical importance of data quality, ethical considerations, and the selection of appropriate technological solutions based on specific urban traffic scenarios. Findings highlight the significant role of integrated AI and geospatial analyses in improving traffic predictions and operational efficiency. Future work will focus on developing more sophisticated models that ensure privacy, equity, and adaptability to new transportation trends. 2024 IEEE. -
Revolutionizing packaging sustainability through advanced materials and technologies
Consumer engagement is identified as a catalyst for positive environmental impact in the context of sustainable packaging. It probes into three fundamental aspects collectively contributing to forming a conscientious community: packaging transparency and labelling, consumer education, and packaging as a narrative medium. Education promotes advocacy for sustainability, transparent labelling enables individuals to make informed decisions, and packaging narratives establish emotional connections. Collectively, they facilitate a transition towards conscientious consumption. The potential for improved environmental impact of packaging is further enhanced by the collaborative efforts of consumers and brands, which can shape corporate strategies and contribute to preserving the planet. 2024, IGI Global. All rights reserved. -
Revolutionizing lifelong learning AI, virtual, and augmented reality in education
The purpose of this chapter is to investigate the revolutionary effects that artificial intelligence (AI), virtual reality (VR), and augmented reality (AR) have had on the educational environment, specifically with regard to the revolutionization of lifelong learning. It investigates the ways in which the incorporation of cuttingedge technology is changing conventional instructional approaches, therefore providing students with individualized and immersive educational experiences. The conversation focuses on the inclusive and dynamic character of education that is made possible by artificial intelligence, virtual reality, and augmented reality, while also addressing problems such as the limitations of technology and ethical implications. It is emphasized that in order to fully realize the potential of modern technologies in the field of education, it is necessary for educators, legislators, and technologists to work together. This abstract offers a succinct overview of the ways in which artificial intelligence, virtual reality, and augmented reality are profoundly changing paradigms of lifelong learning. 2024, IGI Global. All rights reserved. -
Revolutionizing legal services with blockchain and artificial intelligence
[No abstract available] -
Revolutionizing Healthcare with IoT: Connecting the Dots for Better Patient Outcomes
Healthcare enhances ones physical and emotional well-being via the detection, treatment, and eventual cure of disease, illness, injuries, and other debilitating conditions. The importance of information systems has increased everywhere, particularly in the healthcare sector. Information technology has long benefitted the health business, from electronic health records to cloud-based platforms. Information systems are becoming increasingly important in advancing healthcare and healthcare administration. The pandemic brought virtual space and services to all sectors of the economy, especially healthcare, which was predominantly supported through face-to-face services earlier, but due to the requirement of social distancing, hospitals started offering services in virtual mode. Also, evolution in the information system and the Internet has paved the way for the Healthcare Internet of Things (HIoT). The Healthcare Internet of Things (HIoT) is the interconnection of intelligent objects or devices that enables the development of new healthcare services and applications. HIoT can take many forms, namely medical devices, public health services, innovative technology, medication refills, and remote monitoring. This healthcare data is a new treasure for healthcare stakeholders to improve patients health and experiences while creating revenue opportunities and improving healthcare operations. Thus, HIoT is redefining healthcare by ensuring better care, improved treatment outcomes, and reduced patient costs, as well as better processes and workflows, improved performance, and patient experience for healthcare providers. HIoT devices can also be useful for asset management tasks like controlling inventory at the pharmacy, checking refrigerator temperatures, and controlling humidity and temperature in the environment. Having said the advantages, one cannot deny the challenges it has brought to safety, security, privacy, and scalability aspects. Hence, this chapter will explore the evolution of IoT in healthcare, its elements, applications, and challenges. 2024 selection and editorial matter, Alex Khang. -
Revolutionizing healthcare telemedicine's global technological integration
The pursuit of universal and high-quality healthcare services is a fundamental obligation of any responsible state, yet India faces persistent challenges in achieving this goal despite governmental efforts and policies. Notably, the 65th World Health Assembly emphasized universal health coverage (UHC) as pivotal for global public health advancement. Addressing this, a 2010 high-level expert group identified impediments in UHC implementation, highlighting issues such as health financing, infrastructure, skilled human resources, and access to medicines. This study focuses on exploring telemedicine's potential to mitigate these challenges and become instrumental in realizing universal health coverage in India. It aims to scrutinize government plans, critically assess policies on telemedicine implementation, and propose effective integration models, particularly in rural areas, to facilitate UHC. Additionally, the research aims to examine the role of AI, ML, deep learning, and neutral networks within telemedicine, envisaging their contribution to augmenting telemedicine's efficacy towards achieving universal health coverage in India. 2024, IGI Global. All rights reserved. -
Revolutionizing Biodegradable and Sustainable Materials: Exploring the Synergy of Polylactic Acid Blends with Sea Shells
This study explores the mechanical properties of a novel composite material, blending polylactic acid (PLA) with sea shells, through a comprehensive tensile test analysis. The tensile test results offer valuable insights into the materials behavior under axial loading, shedding light on its strength, stiffness, and deformation characteristics. The results suggest that the incorporation of sea shells decrease the tensile strength of 14.55% and increase the modulus of 27.44% for 15 wt% SSP (sea shell powder) into PLA, emphasizing the reinforcing potential of the mineral-rich sea shell particles. However, a potential trade-off between decreased strength and reduced ductility is noted, highlighting the need for a delicate balance in material composition. The study underscores the importance of uniform sea shell particle distribution within the PLA matrix for consistent mechanical performance. These results offer a basis for additional PLA-sea shell blend optimization, directing future efforts to balance strength, flexibility, and other critical attributes for a range of applications, including biomedical devices and sustainable packaging. This investigation opens the door to more sustainable and mechanically strong materials in the field of additive manufacturing by demonstrating the positive synergy between nature-inspired materials and cutting-edge testing techniques. 2024 The Authors. -
Revolutionizing Arrhythmia Classification: Unleashing the Power of Machine Learning and Data Amplification for Precision Healthcare
This paper presents a comprehensive exploration of arrhythmia classification using machine learning techniques applied to electrocardiogram (ECG) signals. The study delves into the development and evaluation of diverse models, including K-Nearest Neighbors, Logistic Regression, Decision Tree Classifier, Linear and Kernelized Support Vector Machines, and Random Forest. The models undergo rigorous analysis, emphasizing precision and recall due to the categorical nature of the dependent variable. To enhance model robustness and address class imbalances, Principal Component Analysis (PCA) and Random Oversampling are employed. The results highlight the effectiveness of the Kernelized SVM with PCA, achieving a remarkable accuracy of 99.52%. Additionally, the paper discusses the positive impact of feature reduction and oversampling on model performance. The study concludes with insights into the significance of PCA and Random Oversampling in refining arrhythmia classification models, offering potential avenues for future research in healthcare analytics. 2024 IEEE. -
Revolutionising Tumour Diagnosis: How Clinical Application of Artificial Intelligence and Machine Learning Enhances Accuracy and Efficiency
This research paper examines the transformative influence of Artificial Intelligence (AI) and Machine Learning (ML) on tumour diagnosis within clinical settings. The advent of AI and ML technologies has revolutionised the field of oncology, offering the unprecedented potential for more accurate, timely, and personalised cancer detection. By leveraging vast datasets of medical images, genomic information, and patient records, these intelligent systems enable the early identification of tumours, classification of cancer types, and prediction of patient outcomes with remarkable precision. This paper delves into the mechanisms through which AI and ML algorithms analyse complex data, highlighting their ability to detect subtle patterns and anomalies that may escape human perception. Moreover, we examine the successful integration of these technologies into clinical workflows, their potential to reduce diagnostic errors, and the implications for patient care and outcomes. As AI and ML continue to emerge, the synergy between technology and clinical expertise promises to enhance tumour diagnosis, ultimately contributing to more effective and personalised cancer treatments. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Revolution of the Indian Agricultural Landscape using Machine Learning and Big Data Techniques: A Systematic Review
The world of Big Data has been rapidly expanding into the domains of Engineering and Machine Learning. The biggest challenge in the Big Data landscape is the incompetence of processing vast amounts of data in a time-efficient manner. The agriculture domain has so long only relied on traditional method for yield prediction. This can be bettered by using novel Machine Learning techniques and innovative thinking. The study provides the review of most of the techniques already implemented in the ML, Big Data and Agriculture domain- traditional and modern- while focusing on highlighting the difference in accuracy between the traditional methods and the more advanced methods. 2022 IEEE. -
Revocable and Secure Multi-Authority Attribute-Encryption Scheme
Security is an important factor as nowadays many systems generates and process huge amount of data. This also leads many of us to rely on a third-party service provider for storing sensitive and confidential data. Providing outsourcing means the data owner will encrypt and store the data in a third-party storage system. In this paper, we are proving solutions for two main problems. The first issue is what if the attribute authority itself can access the data because the attributes and secret keys are known by attribute. This issue is called the key escrow problem. For solving it we are proposing a multi-authority system with Elliptic Curve Cryptography. The second issue that we addressed in this paper is the revocation problem, which means when someone leaves the system should be prohibited from accessing subsequent data this is called forward security and as a second case when someone joins the system should be prevented from accessing previous shared date this is called backward security. In this paper, we address both forward and backward security. For solving this problem we are using the concept of the Lagrange interpolation technique for generating and verifying secret keys. Based on this technique secret key will be dynamically altered and used for encryption and due to this can achieve greater security. 2023, Ismail Saritas. All rights reserved. -
Revitalizing language acquisition journey: A multidisciplinary approach to combat burnout
This chapter presents an all-encompassing strategy for combating digital fatigue in second language acquisition (SLA). It examines digital exhaustion's symptoms, causes, and psychological effects, emphasizing the need for healthy digital practices. Excessive use of technology, such as language applications and social media, can exacerbate exhaustion and necessitate self-care and stress management. Learners should prioritize their well-being by engaging in self-reflection, relaxation, and non-language activities, including mindfulness and meditation. Instructors are essential for fostering supportive environments incorporating feedback and a development mindset. Peer participation fosters community and reduces fatigue. This comprehensive strategy engages learners, instructors, parents, and peers to ensure a successful SLA journey in the digital age, with well-being at its core. 2023, IGI Global. -
Revitalizing education: A roadmap for school transformation
Educational equity, school transformation, and policy and practice alignment are crucial in the evolution of educational systems. It requires an all-encompassing comprehension that transcends historical contexts, technological impacts, and conceptual frameworks to address students' varied requirements and eliminate inequalities. Acknowledging educational equity as a moral imperative underscores the ethical obligation of stakeholders. School transformation necessitates the presence of forward-thinking administrators, the active involvement of stakeholders, and a comprehensive reassessment. A cohesive approach to equity requires the utilization of robust frameworks, ongoing professional development, and continuous assessment to align policy and practice. Overcoming obstacles requires confronting opposition, capitalizing on technological advancements, deriving lessons from past failures, and establishing the foundation for a future characterized by greater inclusivity. 2024, IGI Global. All rights reserved. -
Revisiting the trade opennessunemployment nexus: anapplication of the novel JKS panel causality test with static anddynamic panel models
Purpose: This paper documents a robust empirical regularity: higher trade openness is associated with a lower unemployment rate. This paper also examines whether or not the effects of trade liberalisation depend on countries' income levels. Further, the dynamic causation between trade openness and unemployment is also examined. Design/methodology/approach: In order to obtain insight into the opennessunemployment nexus, following empirical methods were utilised - static panel models, dynamic panel models and a novel panel Granger causality approach proposed by Juodis etal. (2021). Findings: Results suggest that openness negatively affects unemployment; the extent to which trade liberalisation affects unemployment depends on the income level of each country. The Juodis, Karavias, and Sarafidis (JKS) test confirmed that the past values of trade openness, inflation, foreign direct investment and gross domestic product per capita contain information that helps to predict unemployment in a more robust manner. To simply put, opening upto trade may eventually become a requirement for creating more job opportunities, but this alone may not be enough. The extent to which nations benefit from trade liberalisation is largely dependent on the overall economic conditions and their capability to move up the income scale. Originality/value: A major difference between this study and those performed previously is that this study does not only examine the impact of trade openness on unemployment, but also investigates whether the unemployment effect of liberalisation is affected by countries' income levels an issue that has received little attention in the past. Additionally, the unique panel non-causality approach put forth by Juodis etal. (2021) is used in the first instance to look into the causal link between trade openness and unemployment. This method has advantages in that the method enables capturing Granger-causality in homogeneous or heterogeneous panels amongst multiple variables. 2023, Emerald Publishing Limited.