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Early stage detection of osteoarthritis of the joints (hip and knee) using machine learning
This study explores the developing relationship between health care and technology, with a special emphasis on the use of machine learning (ML) algorithms to detect early stage osteoarthritis (OA) in the hip and knee joints. OA, a substantial worldwide health problem, requires improved diagnosis techniques. In this analysis, we illuminate the limitations of traditional methods, emphasizing the inherent subjectivity of clinical assessments and the delay in detection using routine imaging techniques. The research investigates the potential of ML to bring about significant changes. It focuses on combining various algorithms with extensive datasets and highlights the need to select relevant features and prepare the data to improve the accuracy of the models. The use of ML is closely connected to ethical issues, which include the protection of data privacy and the capacity to comprehend the models used. To bridge the gap between theory and practice, the chapter presents concrete examples of ML's practical use in detecting OA, opening possibilities for customized therapy and enhanced patient results. The chapter also highlights potential areas for future study, emphasizing the urgent requirement for additional progress in ML-based early detection techniques to alleviate the worldwide impact of OA. 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Early strength of concrete amended with waste foundry sand - A potential for early open to traffic (EOT) pavements
The most predominant and widely practiced methods for waste disposal are Landfill, Incineration, and composting. There is a scarcity of land for waste disposal and because of increasing land cost, recycling and utilization of industrial by-products and waste materials has become an attractive proposition to waste disposal. There are several types of industrial by-products and waste materials. The utilization of such materials in concrete not only decreases the overall cost of construction but also helps in reducing disposal concerns. One such industrial by-product is waste foundry sand (WFS). The annual production is about 3 million tons from different industries in India. In the metal casting process, foundry industries dispose of huge quantities of waste sand into landfills, causing a harmful impact on the environment. The silica-based spent foundry sands from iron, steel, and aluminum foundries are evaluated in the risk assessment. This paper mainly focuses on achieving concrete for EOT (Early Open to Traffic) rigid pavements with WFS along with the use of accelerator and super-plasticizer. Effects of WFS on concrete properties such as compressive strength and split tensile strength are presented. Two types of mix proportions were investigated in this study. FDOT (Florida Department of transportation) and IRC (Indian Road Congress) recommendations were adopted for mix proportions using 5% & 10% of WFS replaced partially for M-Sand. 1-day compressive strength for FDOT mix with 10% WFS was 30MPa & for IRC mix with 10%, WFS was 20?MPa. The 3-days strength for mixtures with 10% WFS was 45MPa & 47MPa for FDOT & IRC mix proportions, respectively. Though the strength decreased with the inclusion of WFS, the 1-day and 3-days strength achieved for mixtures with 10% WFS surpassed the minimum strength requirements as per the slab replacement guidelines. Normally the pavement will be open to traffic after three to four days of laying asphalt, this method of using foundry sand enables the pavements to be open to traffic inless than a day. 2023 Author(s). -
Early Warning System for Engine Failure Detection in Aircraft Engines Using Machine Learning
Aviation has a problem with engine defects which are a major concern. Unforeseen causes might render them expensive on the ground and hazardous in the air. We present a system that signals when an aircraft engine is about to fail. Our AdvancedModelTrainer checks a collection of models - Random Forest, XGBoost, Gradient Boosting, LightGBM, Ridge, Lasso, ElasticNet, and a simple neural network - through a dataset of 10,000 engine cycles along with 25 engineered features. Hyperparameter tuning and Remaining Useful Life (RUL) metrics help to select the top two (Gradient Boosting and XGBoost, RMSE 39.99, R2=0.7715). A complete MLOps structure keeps an eye on the drift, initiates the retraining process, and sets up dashboards that are user-friendly for the mechanics. The system has detected on 1,433 new engines, 1,126 were classified as Safe, 106 as Warning, and 201 as Critical, which is indicating the coverage of 93.44The dataset used was completely anonymized in order to safeguard sensitive operational data and to not conflict with the aviation data privacy regulations. 2025 IEEE. -
Early-Stage Cervical Cancer Detection via Ensemble Learning and Image Feature Integration
Cervical cancer ranks as the fourth most common malignancy worldwide and poses a significant threat, particularly in resource-constrained regions. Automated diagnostic approaches, leveraging colposcope image analysis, hold great promise in curbing the impact of this disease. In this study, we introduce an ensemble of machine learning and deep learning models, including DenseNet 121, ResNet 50, and XGBoost to classify the cervical intraepithelial neoplasia. A novel feature integration is proposed which ensembles the results of the individual models in five fold validation process. Our methodology is deployed on a dataset sourced from the International Agency for Cancer Research. The results from the proposed framework have shown to be accurate, robust and dependable. This method can be utilized for achieving automatic identification of cervical cancer in early stages so it can be treated appropriately. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Earthquake and flood resilience through spatial Planning in the complex urban system
Urban Communities are exposed to different disaster risks. The paper aims at understanding the interrelation of spatial planning and the resilience of the urban communities for earthquakes and floods. Various spatial planning components were used to evaluate the community resilience to earthquake and flood in the city of Pune of Maharashtra state in India. It has been identified that spatial planning contributes to a greater extent in determining community resilience. Spatial planning results in differential resilience among communities. In the study area, economically weaker households are found to be more vulnerable to disaster risk due to their spatial locations and limited accessibility to share the resources. These factors are found to be contributing to reduced resilience in the city. 2022 The Authors -
EASM: An efficient AttnSleep model for sleep Apnea detection from EEG signals
This paper addresses the crucial task of automatic sleep stage classification to assist sleep experts in diagnosing sleep disorders such as sleep apnea and insomnia. The proposed solution presents a novel attention-based deep learning model called, Efficient Attention-sleep Model (EASM), designed specifically for sleep apnea detection using EEG signals. EASM incorporates a streamlined architecture that includes a modified Muti-Resolution Convolutional Neural Network (MRCNN), Adaptive Feature Recalibration (AFR), and a simplified Temporal Context Encoder (TCE) module to reduce complexity. To mitigate overfitting, ridge regression is utilized, which incorporates a penalty term to enhance model generalization. Furthermore, the proposed EASM utilizes a class-balanced focal loss function to address data imbalance issues. The effectiveness of EASM is evaluated on two publicly available datasets, SLEEP EDF-20 and SLEEP EDF-78. Comparative analysis of EASM against state-of-the-art models demonstrates its superior performance in terms of accuracy, training time, and model complexity. Notably, the proposed model achieves a 50% reduction in training time and a 55.7% decrease in complexity compared to the Attnsleep model. The EASM achieves a classification accuracy of 85.8% with minimum loss when compared to the Attnsleep model. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
EASM: An efficient AttnSleep model for sleep Apnea detection from EEG signals
This paper addresses the crucial task of automatic sleep stage classification to assist sleep experts in diagnosing sleep disorders such as sleep apnea and insomnia. The proposed solution presents a novel attention-based deep learning model called, Efficient Attention-sleep Model (EASM), designed specifically for sleep apnea detection using EEG signals. EASM incorporates a streamlined architecture that includes a modified Muti-Resolution Convolutional Neural Network (MRCNN), Adaptive Feature Recalibration (AFR), and a simplified Temporal Context Encoder (TCE) module to reduce complexity. To mitigate overfitting, ridge regression is utilized, which incorporates a penalty term to enhance model generalization. Furthermore, the proposed EASM utilizes a class-balanced focal loss function to address data imbalance issues. The effectiveness of EASM is evaluated on two publicly available datasets, SLEEP EDF-20 and SLEEP EDF-78. Comparative analysis of EASM against state-of-the-art models demonstrates its superior performance in terms of accuracy, training time, and model complexity. Notably, the proposed model achieves a 50% reduction in training time and a 55.7% decrease in complexity compared to the Attnsleep model. The EASM achieves a classification accuracy of 85.8% with minimum loss when compared to the Attnsleep model. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Ebcqi: Enhanced bcqi downlink scheduling algorithm for voip in mobile networks
Long Term Evolution (LTE) is a currently growing technology. It gives high speed data with several useful applications. Voice over Internet Protocol (VoIP) is one of the top most applications in that LTE. Scheduling is the main issue in LTE. This paper proposing an updating version of Best Channel Quality Indicator (BCQI) downlink scheduling algorithm. The proposed algorithm assigns the highest priority to VoIP users followed by video traffic and then other remaining traffics in next priority order. The simulation reports give the better results of increased average throughput in all users, as well as the spectral efficiency development is also increased. Here, in the proposed algorithm, the percentage of packet loss is also consistent with the existing BCQI algorithm. And, it totally emits positive results in both rural and urban area environments with different mobility. Number of user access is also high when compared with BCQI algorithm. IJSTR 2019. -
EC(H) onarrating stories: Ecological thought and metanarrativity in folktales
This paper studies the ecological discourse constructed in folktales, looking at the relationship between folktales and the human-nature-culture paradigm. By closely examining select folktales collected by folklorist A. K. Ramanujan, this paper looks at the metanarrativity of tales and argues from a narratological perspective that folktales deploy nature metaphors to establish a close relationship between nature, women and culture. This, it is argued, is made possible only in the conservation of stories for, in conserving a story, the message of conserving cultures and their artefacts (an ecological metaphor) is spread. The story is conserved; however, not in hoarding it but quite contrarily in transmitting and letting it go. The paper also critically examines how female subjects, through the use of nature metaphors and symbols of fertility and femininity speak of their consciousness in these 'woman-centred tales' in a space characterized by the absence of the Phallic Other but inevitably speak the patriarchal language of feminine inscriptions. Using folkloric research of A. K. Ramanujan as well as ecocritical frameworks, this paper looks at the narratological dimensions of folklore to understand metanarration as a crucial aspect of folklore and ecological conservation. Therefore the lessons of conservation lie not only in the content of the folktales but also in their very telling. The ecological aspects in and of the tale must necessarily be echoed multiple times to enable the tale's transmission, and in effect, their conservation. 2014 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (Dharmaram Vidya Kshetram, Bangalore). -
Ecc-based secure group communication in energy-efficient unequal clustered wsn (Eeuc-ecc)
With an advent of the Internet of things (IoT), wireless sensor networks (WSNs) are gaining popularity in application areas like smart cities, body area sensor networks, industrial process control, and habitat and environment monitoring. Since these networks are exposed to various attacks like node compromise attack, DoS attacks, etc., the need for secured communication is evident. We present an updated survey on various secure group communication (SGC) schemes and evaluate their performance in terms of space and computational complexity. We also propose a novel technique for secure and scalable group communication that performs better compared with existing approaches. Springer Nature Singapore Pte Ltd. 2020. -
Eccentric completion of a graph
The eccentric graph Ge of a graph G is a derived graph with the vertex set same as that of G and two vertices in Ge are adjacent if one of them is the eccentric vertex of the other. In this paper, the concepts of iterated eccentric graphs and eccentric completion of a graph are introduced and discussed. 2022 The authors. -
Eccentric Graph of Join of Graphs
The eccentric graph Ge corresponding to a graph G is a derived graph with the same vertex set of G and two vertices in Ge are neighbours if one of them is the eccentric vertex of the other. Motivated by the studies on derived graphs and graph operations, in this article, the eccentric graph of the join of two graphs is analysed based on the variations in the radius. The notion of eccentric join of two graphs with at least one of them having radius 1, is introduced. The eccentric graph of eccentric join of graphs is also examined. Finally, the concept of r-eccentric join of graphs is also introduced. This study is analytical in nature, which involves deductive and logical reasoning. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Eccentricity splitting graph of a graph
Let G = (V, E) be any connected graph with (Figure presented.) for all uj, uk ? Si if e(uj) = e(uk)(1 ? i ? t) with each | Si |? 2 and (Figure presented.). The eccentricity splitting graph of a graph denoted by ES(G) is obtained by taking a copy of G and adding vertices w 1, w 2, , wt such that wi is adjacent only to the vertices of Si for 1 ? i ? t. We initiate the study on eccentricity splitting graph ES(G) and examine its structural properties. We also analyze diameter, girth and chromatic number of eccentricity splitting graphs of certain classes of graphs. 2021 Taru Publications. -
Ecclesiology, piety, and presbyterian and independent polemics during the early years of the english revolution
Religious controversy swept across England during the revolutionary decades of the 1640s and 1650s. Historians have studied the attendant ecclesiological debates meticulously. The piety as practiced by the puritans has also been carefully examined. Yet generally, these two subjects of ecclesiology and piety have been kept as separate compartments of analysis. The plethora of tracts that rolled off the press during the initial years of the 1640s, nevertheless, shows that many contemporary polemicists were keen to tie the two themes together. The Presbyterian and Independent polemicists were no exception. As this article seeks to demonstrate, a common feature of their publications was the belief that their preferred ecclesiastical polity best served the purpose of promoting individual piety and creating a godly society. Thus the Presbyterian and Independent conflict waged not only over issues of ecclesiology proper such as categories of church offices and of governing councils or composition of church membership to which historians have directed their attention hitherto, but also over questions of how ecclesiology affected piety. Such conflict was a reflection of the commitment of Presbyterians and Independents to their respective vision of reformation for the country. More broadly, this article shows a facet of religious controversy that ultimately led to the disintegration of the godly community and weakened the base of support for the Commonwealth and the Protectorate. American Society of Church History 2015. -
Echoes of Conflict: Unveiling the Interconnected Tapestry of Russia-Ukraine Warfare, Oil Price Ballet, and the Asian Stock Symphony
The purpose of this research is to look into the impact of the Russia-Ukraine war on the relationship between oil prices and the Asian stock market. While earlier studies have investigated the impact of oil prices on stock markets, there has been little research into the impact of crude oil prices on the Asian stock market in the context of the Russia-Ukraine war. For this purpose, the data is collected from NSE and Bloomberg database the study's findings imply that the Russia-Ukraine war has had a major impact on the relationship between crude oil prices and stock market indices in numerous Asia-Pacific countries. The study suffers from a few limitations such as it only examines the relationship between crude oil prices and stock market indices but there are other macroeconomic factors, such as interest rates, inflation, and political instabil ity which also affect the market. 2024, ASERS Publishing House. All rights reserved. -
Echoes of Empire: Portuguese Cultural Imperialism in Goa and Mangalore from the 15th to 18th Centuries
The Portuguese colonization in Goa and its indirect religious influence in Mangalore from the 15th to the 18th century left behind a complex legacy of social, cultural, economic, political, and religious changes. Situated within postcolonial and neocolonial studies, the paper explores the mechanisms of Portuguese cultural dominance in Goa coerced religious conversion, linguistic imposition, architectural transformation, communication, and educational control contrasted with more indirect cultural and religious influence in Mangalore, and, as a result, the impact of cultural imperialism and cultural transformation. The study contextualises the enduring effects of these colonial processes by using the theoretical frameworks of Anal Quijano concept of Coloniality of Power, Johan Galtungs Centre-Periphery Model, Edward Saids Orientalism, and Herbert Schillers Communication Imperialism. The paper highlights local resistance and cultural hybridization, and reveals a complex negotiation between imposition and adaptation. The study emphasizes the legacy of Portuguese imperialism within a broader perspective of global power structures and how it has shaped the modern neocolonial frameworks. The findings contribute to discussions on cultural imperialism by illustrating how historical hegemonic practices persist through language policies, architectural preservation, and religious traditions. The paper also touches upon the regions postcolonial identity formation through Goas Lusophone heritage and Mangalores distinct religious evolution. This analysis demonstrates how past mechanisms of control continue to influence the contemporary global and regional dynamics, reinforcing cultural hegemony through modern neocolonialism. 2024 selection and editorial matter, Dr. L. Santhosh Kumar, Ms. Minu A., Dr. Barnashree Khasnobis, Dr. Preetha M. and Dr. Merrin R. S.; individual chapters, the contributors. -
Eco Friendly Nitration of Toluene using Modified Zirconia
Bulletin of Chemical Reaction Engineering & Catalysis Vol. 7, No.3, pp.205-214 ISSN No. 1978-2993 -
Eco friendly nitration of toluene using modified zirconia
Nitration of toluene has been studied in the liquid phase over a series of modified zirconia catalysts. Zirconia, zirconia- ceria (Zr0.98Ce0.02)O2, sulfated zirconia and sulfated zirconia- ceria were synthesised by co precipitation method and were characterised by X-ray diffraction, BET surface area, Infra red spectroscopy analysis (FTIR), Thermogravimetric analysis (TGA), Scanning Electron Microscopy (SEM), and Energy Dispersive X ray analysis (EDAX). The acidity of the prepared catalysts was determined by FTIR pyridine adsorption study. X-ray diffraction studies reveal that the catalysts prepared mainly consist of tetragonal phase with the crystallite size in the nano range and the tetragonal phase of zirconia is stabilized by the addition of ceria. The modified zirconia samples have higher surface area and exhibits uniform pore size distribution aggregated by zirconia nanoparticles. The onset of sulfate decomposition was observed around 723 K for sulfated samples. The catalytic performance was determined for the liquid phase nitration of toluene to ortho-, meta- and para- nitro toluene. The effect of reaction temperature, concentration of nitric acid, catalyst reusability and reaction time was also investigated. 2013 BCREC UNDIP. -
Eco-conscious consumers green real estate decisions in India: the role of social commerce
Purpose: The primary purpose of this paper is to examine the role of perceived trust, information quality, positive word of mouth and societal norms toward real estate purchase intention. The study also examines how pro-environmental self-identity mediates the relationship between positive word of mouth and real estate purchase intent, as well as between societal norms and real estate purchase intention. This research aims to delve into these intricate dynamics through a multidimensional lens. Design/methodology/approach: The research employs existing scholarly works and measurable variables evaluated through a five-point Likert scale, hypothesis testing and mediation analysis to examine the proposed framework. A structured survey comprising six sections was administered, yielding 385 valid responses. The data analysis process included the use of confirmatory factor analysis and structural equation modelling techniques. Findings: The analysis indicates that pro-environmental self-identity has the most significant influence on real estate purchase intention, closely followed by positive word of mouth. Incorporating eco-friendly themes in marketing campaigns significantly boosts purchase intentions. However, perceived trust does not significantly impact purchase intentions. Other factors, such as information quality and societal norms, also play significant roles, underscoring the importance of understanding the complex dynamics shaping consumer decisions in the real estate market. Research limitations/implications: This research exclusively targets responses from young consumers in specific regions of India. Future studies should aim for a more extensive geographic scope, encompassing a diverse global population for a broader understanding of the subject. Originality/value: Based on previous literature, this study is the first to identify the elements influencing the inclination to buy environmentally friendly real estate through social commerce. 2025, Emerald Publishing Limited. -
Eco-conscious photocatalytic degradation of organic textile dyes using green synthesized silver nanoparticles: a safe and green approach toward sustainability
Green synthesized nanoparticles from Strobilanthes barbatus leaf extracts are environmentally safe and feasible for enduring wastewater treatment, especially for organic textile dye degradation. The synthesized Strobilanthes barbatusmediated silver/silver-oxide nanoparticles (SB-Ag/AgO NPs) showed maximum absorbance at 428nm. The SB-Ag/AgO NPs were generally spherical with an average diameter of 37.59nm (FESEM and TEM analysis). The importance of functional groups in the production of SB-Ag/AgO NPs was recorded by FTIR investigations. In the degradation and rate of degradation for textile dyes, after 320min, SB-Ag/AgO NPs displayed 96.60% (5.31 10?1 L mg?1min?1) and 87.50% (1.179 10?1 L mg?1min?1) degradation of Reactive Blue 220 (RB-220) and Reactive Blue 222A (RB-222A), respectively. When compared to dye effluents, SB-Ag/AgO NPs-treated dye solutions revealed a considerable decrease in inhibitory efficiency during phytotoxicity evaluation on test organisms, Vigna radiata and Artemia salina. The biosynthesized SB-Ag/AgO NPs could serve as a feasible photocatalyst for the treatment of organic textile dyes in organic substancepolluted water ecosystems. SB-Ag/AgO NPs can serve as efficient, cost-effective and environmentally friendly sources for dye degradation. The current research offers a safe and environmentally friendly strategy for sustaining the environment. 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.