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IoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and Diagnosis
Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome these restrictions, we present a hybrid framework combining CNN and ResNet that merges deep learning-based feature extraction with real-time data collecting from IoT devices. The proposed approach utilises CNNs for preliminary feature extraction, ResNet for hierarchical learning with residual connections, and IoT for real-time patient monitoring and automatic notifications. The dataset undergoes preprocessing through normalisation, augmentation, and histogram equalisation to improve image quality and learning efficacy. The model is trained with cross-entropy loss and the Adam optimiser, guaranteeing stability and excellent performance. The evaluation results indicate a substantial enhancement compared to baseline models, with an accuracy of 97, an F1-score of 95.3, and a recall rate of 96.4%, exceeding traditional deep learning (90 accuracy) and CNN-based models (80% accuracy). The suggested model similarly minimises mistakes, with RMSE and MSE values declining to 1.2 and 1.6, respectively, signifying reduced misclassification rates. The inclusion of IoT facilitates instantaneous data transmission with little latency, hence improving clinical decision-making and minimising diagnostic delays. This advanced system facilitates automated and precise breast cancer detection, providing an innovative method for early diagnosis, optimised treatment planning, and improved patient outcomes, while ensuring data privacy and security through encryption and commitment to healthcare regulations. 2026 Yamini Kalva, R. Ganesh Babu, Sindhu V, S. Gokul Pran, Garaga Srilakshmi, Kavitha C T, Sathish Kumar Shanmugam and V. Bhoopathy. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
IoT-Powered Health Monitoring System for Protecting Vital Organs Through Cloud-Based Diagnosis
The main objective of this research was the development and evaluation of an IoT- and machine learning-based health monitoring system capable of protecting patients vital organs through cloud diagnosis. This could be achieved by connecting a set of sensors, including temperature, pressure, heart rate, and oxygen sensors, to the patient and allowing them to communicate with the cloud to transmit real-time data via IoT technologies. The data could be further analyzed and predicted using cloud-based machine learning algorithms. This study investigated the performance of different machine learning models, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Naive Bayes (NB), and Negative Decision Trees (DT), for the purpose of patients health prediction based on the sensor data. After experimentation and evaluation, we found that the ANN model demonstrated the best predictive ability, with an accuracy level of 99.45%. The SVM, NB, and DT models also demonstrated good performance, with the accuracies of 96.5%, 94.34%, and 91.2%, respectively. Therefore, this research demonstrated that IoT and machine learning technologies could be successfully employed in healthcare for remote patient monitoring and timely prediction. The created system allows for real-time monitoring, which enables early prediction, potentially leading to improved patient outcomes, cost savings, and higher efficiency of provided care. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
IoT-Powered Innovations in Renewable Energy Generation and Electric Drive
This review explores the growing impact of the Internet of Things (IoT) on the energy sector, particularly in the context of renewable energy generation and electric drive systems. IoT technology has rapidly expanded into various sectors, including energy, smart cities, and industrial automation, revolutionizing monitoring, control, and management processes. In this paper, we examine the existing literature on IoT applications in energy systems, with a focus on smart grids. We also delve into the core IoT technologies, such as cloud computing and data analysis platforms, that underpin these innovations. Additionally, we address challenges associated with IoT implementation in the energy sector, notably privacy and security concerns, and suggest potential solutions, such as blockchain technology. Our findings provide valuable insights for energy policy-makers, economists, and managers, offering a comprehensive overview of how IoT can optimize energy systems. Furthermore, we highlight IoT's expanding role in renewable energy and electric drive applications, enhancing performance monitoring, management, and energy savings while also advancing research and education in engineering. The Authors, published by EDP Sciences, 2024. -
IoVST: Internet of vehicles and smart traffic - Architecture, applications, and challenges
The internet of things (IoT) is the network of sensors, devices, processors, and software, enabling connection, communication, and data transfer between devices. IoT is able to collect and analyze large amounts of data which can then be used to automate daily tasks in various fields. IoT holds the potential to revolutionise and create many opportunities in multiple industries like smart cities, smart transport, etc. Autonomous vehicles are smart vehicles that are able to navigate and move around on their own on a well-planned road. 2023, IGI Global. -
IPR in Stem Cell Research, Therapy, and Regenerative Medicine
According to the World Trade Organization, intellectual property rights are rights given to persons over the creations of their minds. They usually give the creator an exclusive right over the use of his or her creation for a certain period. There is a critical need for fresh developments in the existing medical diagnostic techniques, therapy, pharmaceutical medications, and research, in a world where such a sizable number of people are afflicted with various ailments, some of which are fatal and still incurable. Pharmaceutical companies are developing novel and cutting-edge ways to treat diseases at an increasing rate. The major pharmaceutical corporations in the world, including Pfizer, Miltenyi, Biotec, AstraZeneca, and Mesoblast Limited are pursuing research in the area of stem cell and regenerative medicine. Regenerative medicine, stem cell research, and therapy are currently regarded as groundbreaking developments in the medical sciences. Understanding their intellectual property rights and the legal means through which these businesses can safeguard their discoveries becomes crucial. This paper will analyze the meaning of stem cell and regenerative medicines, the eligibility of IPR in Stem cell research under the Indian Patents Act, of 1970 and the morality and public issues related to the same. 2024 Taylor & Francis. -
IPWM Based IBMSC DC-AC Converter Using Solar Power for Wide Voltage Conversion System; [Convertisseur DC-AC IBMSC bassur l'IPWM et utilisant l'ergie solaire pour un syste de conversion large tension]
This article proposes isolated bidirectional micro dc-ac single phase controlled (IBMSC) converter based on in-phase-voltage pulsewidth modulation (IPWM). This resonant IPWM converter, ratio of voltage conversion can be controlled from 0 to ?. So, this converter is highly referred for huge range voltage conversion. However, voltage conversion ratio determines power transfer direction and duty ratio. Power flow direction and duty cycle value can be varying smoothly, so it is suitable for dc-ac bidirectional power conversion application. Inverter mode and also rectifier mode are possible from bidirectional operation, which is controlled by a unified current controller. The proposed solution can achieve smooth switching grid operation with high efficiency. Working principle, design procedure, control strategy, and characteristics of the proposed converter are implemented with a prototype model of power rating 500 W with a voltage range of 20-50 V to test the ability of withstanding. Performance, feasibility, and effectiveness of the proposed converter are tested with this hardware test-bench model. 2022 IEEE. -
IRIS Data Classification using Genetic Algorithm Tuned Random Forest Classification
Optimising hyper-parameters in Random Forest is a time-consuming undertaking for several academics as well as professionals. To acquire greater performance hyper-parameters, specialists should explicitly customize a series of hyper-parameter settings. The best outcomes from this manual setting are then modelled and implemented in a random forest algorithm. Several datasets, on the other side, need various prototypes or hyper-parameter combinations, which may be time-consuming. To solve this, we offered various machine learning models and classifiers for correctly optimising hyper-parameters. Both genetic algorithm-based random forest and randomised CV random forest were assessed on performance measures such as sensitivity, accuracy, specificity, and F1-score. Finally, when compared to randomised CV random forest, our suggested model genetic algorithm-based random forest delivers more incredible accuracy. 2022 IEEE. -
Iron pulsing, a cost effective and affordable seed invigoration technique for iron bio-fortification and nutritional enrichment of rice grains
Rice being a major staple food for millions of people, it has been one of the major targets for bio-fortification and iron bio-fortification in rice has been in prime focus to address global micronutrient malnutrition. Commonly practiced methods for obtaining Fe biofortified rice includes soil amendments and foliar spray with iron salts, breeding and development of transgenic rice varieties with Fe-enriched grain are associated with impediments like high cost, labor intensiveness, sub-optimal outcome and approval for commercialization respectively. Iron pulsing technique has reportedly enhanced the carbon and nitrogen assimilation in rice seedlings, which has been translated in yield. Based on the previous findings, in the present study, we have undermined the efficacy of iron pulsing, in improving the iron content and nutritional status of rice kernel obtained from pulsed plants. The present study documents that kernel of seeds obtained from iron pulsed plants have a higher amounts of iron, carbohydrate, protein, lipid, vitamins, nutrient and anti-oxidants than that of non-treated ones. The iron localization studies revealed that iron was mostly present in the endosperm and embryo. Besides, the ferritin expression levels also validated the fact that, the treated grains have accumulated more iron. Thus, iron-pulsing can serve as a novel and propitious sustainable agricultural innovation for iron bio-fortification and improvisation of the overall nutritional value of the rice grains that is affordable, user and consumer friendly in years to come. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Iron-pulsing, a novel seed invigoration technique to enhance crop yield in rice: A journey from lab to field aiming towards sustainable agriculture
Bulk fertilizer application is one of the easiest means of improving yield of crops however it comes with several environmental impediments and consumer health menace. In the wake of this situation, sustainable agricultural practices stand as pertinent agronomic tool to increase yield and ensure sufficient food supply from farm to fork. In the present study, efficacy of iron-pulsing in improving the rice yield has been elucidated. This technique involves seed treatment with different concentrations (2.5, 5 and 10 mM) of iron salts (FeCl3 and FeSO4) during germination. FeCl3 or FeSO4 was used to treat the sets and depending on the concentration of the salts, the sets were named as C2.5, C5, C10 and S2.5, S5, S10 (where C and S stands for FeCl3 and FeSO4 respectively and the numbers succeeding them denotes the concentration of salt in mM). Our investigation identified 72 h of treatment as ideal duration for iron-pulsing. At this time point, the seedling emergence attributes and activities of ?-amylase and protease increased. The relative water uptake of the seeds also increased through upregulation of aquaporin expression. The treatment efficiently maintained the ROS balance with the aid of antioxidant enzymes and increased the iron content within the treated seeds. After transplantation in field, photosynthetic rate and chlorophyll content enhanced in the treated plants. Finally, the post-harvest agro-morphological traits (represented through panicle morphology, 1000 seed weight, harvest index) and yield showed significant improvement with treatment. Sets C5 and S5 showed optimum efficiency in terms of yield improvement. To our best knowledge, this study is the first report deciphering the efficacy of iron-pulsing as a safe, cost effective and promising technique to escalate the yield of rice crops without incurring an environmental cost. Thus, iron-pulsing is expected to serve as a potential tool to address global food security in years to come. 2021 Elsevier B.V. -
Irreducible tensor approach to study ? + d ? d + ? 0
The study of photoproduction of mesons plays an important role in understanding the properties of strong interactions. Pion photoproduction on deuterons has been studied theoretically for several decades. At the VEPP - 3 storage rings, tensor analysing powers in ? + d ? d + ?0 have recently been measured. In light of these advances, we suggest adopting an irreducible tensor technique to explore the reaction ? + d ? d + ?0 at close to threshold energies. Our method, which is model-independent, works well for predictions regarding spin observables. By describing the differential cross section in terms of multipole amplitudes, the angular dependence of the cross section will be studied. 2023 Author(s). -
IRRELEVANCE OF ITEM NUMBERS IN BOLLYWOOD MOVIES TODAY- AFFECTING THE PORTRAYAL OF ITEM GIRLS
The research paper was aimed to look into the portrayal of women in media especially those who do item numbers. The paper also looked into the matter that how due to the lack of relevance of item numbers in movies today, the portrayal is negative. Whether this in turn has led to a negative stereotypical representation of women in general was also a concern of the study. The researcher focussed on this matter as she is strongly against any kind of stereotypical representations. As a media student she wanted to inform people about the rights and wrongs in the society and how this leads to framing of stereotypes which is often regarded derogatory. The research was done using both primary and secondary sources. Primary data collection included questionnaire method to general audience of sample size of 100 and a comparative analysis will be done. An extensive study was done of secondary sources too including books, journals, movies, short videos, internet and newspapers. The study revealed that item numbers have definietely lost its relevance in the movies and that has led to the negative portrayal of item girls. There were other reasons also found have an impact on the audiences?? mind which in turn influences his thinking towards the item girls, this was found by comprehending the study with Cultivation theory by Gerbner. -
Irreversibility analysis of radiative heat transport of Williamson material over a lubricated surface with viscous heating and internal heat source
Thecurrent research explores the importance of surface lubrication and convective boundary conditions in the flow of non-Newtonian Williamson material. Rosseland radiative heat flux and viscous heating are also considered. The phenomenon of the generation or absorption of internal heat is studied. The conservation laws of momentum, mass, and energy are used to model the problem with suitable boundary conditions. With the help of appropriate transformations and the finite difference method, highly nonlinear equations of governance are solved. The influence of key parameters on Bejan number, velocity, entropy production, temperature profiles are analyzed by parametric analysis. It was found that the entropy generation rate improves due to the presence of the Rosseland radiative heat flux and the convective boundary on the lubricated surface. The sliding condition on the lubricated surface has lengthened the structure of the velocity boundary layer, while this trend is opposite to the thermal field. The dissipation due to the viscous forces of the Williamson material improves the production of entropy. 2021 Wiley Periodicals LLC -
Irreversibility analysis of the MHD Williamson fluid flow through a microchannel with thermal radiation
The heat transport and non-Newtonian fluid (Williamson fluid) flow through a micro-channel are considered to analyze the entropy generation minimization using the thermodynamic second law. The energy equations have been modeled with the addition of joule heating, heat source, and thermal radiation. The use of suitable dimensionless transformation helps to convert the modeled flow equations into non-dimensional coupled ODEs. The numerical simulations are done via the Finite Element Method. The current outcomes are constructed to examine the behavior of various flow parameters and presented via graphs. It is found that the rise of heat source and Reynolds number Re decays/boosts the entropy rate Ns and the Bejan number Be profile near the left/right plate, and reverse behavior is noticed for the thermal radiation parameter. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Irrigation water policies for sustainable groundwater management in irrigated northwestern plains of India
Increasing global water shortage emphasizes the need for demand-side water management policies, especially in the agriculture sector, being the largest consumer of freshwater. Such policies are relevant in India, where groundwater depletion may have severe implications at various socio-economic levels. In this study, using mathe-matical modelling, we assess the feasibility of two alter-native irrigation water pricing policies (i) uniform wa-ter pricing policy and (ii) differentiated water pricing policy, wherein farmers growing less water-requiring crops (<4488 m3/ha) get an incentive for saving water, while those growing water-intensive crops pay for it. Us-ing a case study of Punjab, the breadbasket and one of the fastest groundwater-depleting states in India, alter-native cropping patterns are also suggested. The findings reveal that the current rate of groundwater withdrawal could not sustain agricultural intensification in the state. Although optimization of resource allocation has the pote-ntial to save water by 8%, this alone is unlikely to break the ricewheat mono-cropping pattern in Punjab. The analysis of two different volumetric irrigation water pricing policies shows that differentiated water pricing would be more effective in halting groundwater deple-tion in the state. However, adequate investment in irri-gation water supply infrastructure, mainly for installing water meters, is required to implement the policy. 2022, Current Science. All Rights Reserved. -
Is asteroid 33 Polyhymnia a dark matter (DM) degenerate object?
Polyhymnia (33 Polyhymnia) is a main belt asteroid in our solar system with a diameter around 54km. The density of asteroid 33 Polyhymnia, located in the main asteroid belt, is calculated to be 75g/cc. Researchers have speculated the possibility that Polyhymnia could be composed of high-density superheavy elements near atomic number 164. Here, we propose that Polyhymnia could be an asteroid composed of degenerate dark matter (DM) and there could be many such asteroids in our solar system. (This is following our earlier work suggesting that Planet Nine could be such an object.) The Author(s), under exclusive licence to SocietItaliana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Is Bitcoin a Safe Haven for Indian Investors? A GARCH Volatility Analysis
This paper attempts to understand the dynamic interrelationships and financial asset capabilities of Bitcoin by analysing several aspects of its volatility vis-a-vis other asset classes. This study aims to analyse the volatility dynamics of the returns of Bitcoin. An asymmetric GARCH model (EGARCH) is used to investigate whether Bitcoin may be useful in risk management and ideal for risk-averse investors in anticipation of negative shocks to the market (leverage effect). This paper also examines Bitcoin as an investment and hedge alternative to gold as well as NSE NIFTY using a multivariate DCC GARCH model. DCC GARCH models are also used to check whether correlation (co-movement) between the markets is time-varying, examine returns and volatility spillovers between markets and the effect of the outbreak of COVID-19 in India on the investigated markets. The results show that given the supply of Bitcoin is fixed, low returns realisation is equivalent to excess supply over demand wherein investors are selling off Bitcoin during bad times. The positive co-movement between Bitcoin and gold during the COVID-19 outbreak shows that investors perceived Bitcoin as a relatively safe investment. However, overall analysis shows that Bitcoin was not considered a safe hedge and an investment option by Indian investors during the study period. 2022 by the authors. -
Is carbon neutrality a reality for India?
India, the third-largest carbon dioxide emitter in the world, aims to achieve zero emissions by 2070. India is committed to its Panchamrit and has launched various initiatives such as green bonds, carbon credits, carbon market, investing in green hydrogen, etc. However, given the present scenario with respect to the dependency on coal-based power generation and lack of green financing, the present article assesses the different solutions and their practicality in achieving carbon neutrality. (2024), (Indian Academy of Sciences). All rights reserved. -
Is ChatGPT Enhancing Youths Learning, Engagement and Satisfaction?
Integration of artificial intelligence (AI) in educational practices necessitates the understanding of the influence of tools such as ChatGPT. Self-determination Theory (SDT) has been used to examine the impact of ChatGPT usage by students for the improvement of perceived learning, engagement and satisfaction. The moderating role of students AI literacy between ChatGPT and the antecedents of intrinsic motivation, autonomy, competence and relatedness. The data was collected through questionnaire from 481 students and structural equation modeling was used to analyze the data. The findings of the study shows that ChatGPT usage impacts students perceived autonomy, competence, and relatedness, enhancing intrinsic motivation. Also, there is a moderation of AI literacy between ChatGPT usage and these psychological needs. This study extends SDT to student interactions with ChatGPT and underscores the pivotal role of AI literacy. The findings contribute to the discourse on AI and education, offering valuable perspectives on students use of ChatGPT and its effect on their academic experience. 2024 International Association for Computer Information Systems. -
Is ChatGPT Enhancing Youths Learning, Engagement and Satisfaction?
Integration of artificial intelligence (AI) in educational practices necessitates the understanding of the influence of tools such as ChatGPT. Self-determination Theory (SDT) has been used to examine the impact of ChatGPT usage by students for the improvement of perceived learning, engagement and satisfaction. The moderating role of students AI literacy between ChatGPT and the antecedents of intrinsic motivation, autonomy, competence and relatedness. The data was collected through questionnaire from 481 students and structural equation modeling was used to analyze the data. The findings of the study shows that ChatGPT usage impacts students perceived autonomy, competence, and relatedness, enhancing intrinsic motivation. Also, there is a moderation of AI literacy between ChatGPT usage and these psychological needs. This study extends SDT to student interactions with ChatGPT and underscores the pivotal role of AI literacy. The findings contribute to the discourse on AI and education, offering valuable perspectives on students use of ChatGPT and its effect on their academic experience. 2024 International Association for Computer Information Systems. -
Is connection the key? The mediating role of psychological safety in the relationship between relatedness to employee engagement
This study examines the influence of Relatedness Needs (RL) on Employee Engagement (EE) in Bengaluru's Information Technology (IT) Industry, with the mediating role of psychological safety (PS). As the information technology industry experiences continuous innovation and is associated with a high-pressure work environment, aligning the organizational needs with the employee's needs is critical to ensure organizational success. Employees with higher RL needs satisfaction will exhibit positive commitment and higher engagement, contributing to the long-term productivity and success of the organisation. This study examines the extent to which PS, indicating a safe environment promoting transparent communication, sharing ideas and engaging in collaborative decision-making without the fear of negative consequences, mediates the relationship between RL and EE. To test the study's hypothesis, AMOS, Smart-PLS, and structural equation modeling were used to analyse data collected from 304 employees working across companies in Bengaluru's Information Technology (IT) industry. Our findings suggest that having a stronger RL boosts EE through the mediating role of PS characterised by trustworthiness, a sense of safety and fairness at the workplace. The results suggest that fostering higher RL and ensuring a strong PS is vital for sustained EE and reducing turnover intention. This study offers valuable insights into the Information technology (IT) companies intending to boost workforce engagement in a highly pressured work environment. 2025 The Authors