A Context-based Numeral Reading Technique for Text to Speech Systems

This paper presents a novel technique for context based numeral reading in Indian language text to speech systems. The model uses a set of rules to determine the context of the numeral pronunciation and is being integrated with the waveform concatenation technique to produce speech out of the input text in Indian languages. For this purpose, the three Indian languages Odia, Hindi and Bengali are considered. To analyze the performance of the proposed technique, a set of experiments are performed considering different context of numeral pronunciations and the results are compared with existing syllable-based technique. The results obtained from different experiments shows the effectiveness of the proposed technique in producing intelligible speech out of the entered text utterances compared to the existing technique even with very less storage and execution time

Healthy–unhealthy tensions duality model:Managing conflict and the exploration–exploitation paradox in creative firms

We examine how senior managers in creative firms navigate the paradoxical tensions of exploration and exploitation—balancing artistic excellence with commercial viability—while managing conflict arising from these contradictions. Drawing on paradox theory and Mary Parker Follett's concept of constructive and non-constructive conflict, we conducted in-depth interviews with 37 senior managers from various creative firms. Our analysis reveals four key managerial mechanisms—integration, compromise, obliging and dominance—that managers employ to address conflict generated by paradoxical tensions. Our findings highlight that integration fosters constructive conflict and generates healthy tensions, characterised by moderate tension and synergy between exploration and exploitation. In contrast, compromise results in temporary resolutions, leading to non-constructive conflict and little tension, while obliging and dominance lead to non-constructive conflict and unhealthy tensions. Based on our findings, we develop a duality model illustrating the interplay between managerial interventions, conflict outcomes and tension dynamics. We contribute to paradox theory by explaining the connections between (non)constructive conflict and (un)healthy tensions and the pivotal role of managerial interventions. We provide practical insights for leaders in creative and other industries, emphasising the importance of integration to achieve a balance between competing demands

IMPROVING EXTRACTIVE TEXT SUMMARIZATION VIA EFFICIENT COATI ALGORITHM FOR SINGLE DOCUMENT

In the digital era, the rapid expansion of online information demands efficient automated text summarization techniques to extract key insights from large documents. This study introduces a novel single-document extractive summarization approach that utilizes Term Frequency-Inverse Topic Frequency (TF-ITF) for feature extraction and the Coati Optimization Algorithm (COA) for optimal sentence selection. COA enhances summarization performance by balancing precision and recall through an adaptive fitness function, improving the quality of extracted summaries. The proposed model is evaluated on DUC 2002, 2003, and 2005 datasets using ROUGE, BLEU, precision, recall, and F1-score metrics. Comparative analysis against state-of-the-art optimization algorithms, including PSO, CSO, GWO, BCO, QABC, MCSO, and GLO, demonstrates that COA outperforms existing techniques, achieving higher recall and F1 scores while maintaining competitive precision. These findings establish COA as an effective optimization technique for enhancing automated text summarization

Study of causes and facility based lags in a tertiary care hospital contributing to maternal mortality

Background: Maternal death is a tragic situation as these deaths occur during or after a natural process like pregnancy. By addressing the three levels of delays i.e., delay in seeking care, delay in reaching care and delay in receiving care; it can be prevented to a fair extent.Methods: All maternal deaths occurred in SCB Medical College and Hospital, Cuttack between September 2015 to September 2016 included in the study, Antepartum and postpartum events were documented as per the proforma. Opinions of respective faculties regarding diagnosis, treatment, possible preventable factors and any delays and lapses at our set up were obtained.Results: There were 10060 live births and 121 maternal deaths, giving the hospital based incidence of maternal mortality as 12.02 per 1000 live births. 42.98%, 6.61% and 50.41% of death were due to Level I, Level II and level III delays respectively. The delays due to unavailability of appropriate facilities in our institution are highlighted. Lack of ICU facility accounted 37.19% deaths. Unavailability of blood, a delay in surgery, delayed multispecialty referral and required investigation follow it. 91.7%. deaths were preventable.Conclusions: Hypertension, Obstetric hemorrhage, liver and kidney diseases were mainly responsible for maternal mortality. Facility based maternal death review system help in finding out the constraints in the existing system. It brings a sense of responsibility in all stake holders involved in delivery of MCH care. It is feasible and cost effective strategy to reach Millennium Development target 5 in extended time frame

Smart Contract Assisted Blockchain based PKI System

The proposed smart contract can prevent seven cyber attacks, such as Denial of Service (DoS), Man in the Middle Attack (MITM), Distributed Denial of Service (DDoS), 51\%, Injection attacks, Routing Attack, and Eclipse attack. The Delegated Proof of Stake (DPoS) consensus algorithm used in this model reduces the number of validators for each transaction which makes it suitable for lightweight applications. The timing complexity of key/certificate validation and signature/certificate revocation processes do not depend on the number of transactions. The comparisons of various timing parameters with existing solutions show that the proposed PKI is competitively better.Comment: manuscrip

Noncognitive microfoundations : understanding dynamic capabilities as idiosyncratically refined sensitivities and predispositions

Can use published PDF in AURA. Check policy and update on publication. Acknowledgements We would like to thank former associate editor Mike Pfarrer and three anonymous reviewers for their exceptional comments and encouragement.Peer reviewedPostprin

Impact of Environmental Regulations on the manufacturing Sector of India

The growing concerns over the depleting environment and the growing pollution levels have raised concerns over the preservation of the environment. Industrialization and the growth of the manufacturing sector have had an impact on the environment. The utilization of natural resources has grown over the years, and most of the industrial developments in the past few year have been due to unplanned urbanization in India. The environment is a major concern globally and the pressure is on the manufacturing sector to reduce wastage and increase utilization to reduce its effect on the environment. The technological changes have bought about major reformations in the manufacturing sector and companies globally are developing new and innovative processes and techniques to comply with the regulations. Over the past few years the environmental regulations globally have got stricter and hence companies now have no choice by comply by the regulations. However there are a lot of uncertainties that can effect a firms decision to comply with the regulations. International competition has also has forced companies to comply with the regulations as it helps create a green image. In this study I have tried to analyze the impact environmental regulations can have on a firm's performance. The importance of compliance to the regulations is growing, and the companies seem to understand the importance of environmentally sustainable practices to comply with the regulations. None the less very few companies have efficient environmental management practices in place. The growing need and importance of complying with the environmental regulations could influence many more firms in India to comply with the regulations

Improving Kui digit recognition through machine learning and data augmentation techniques

Speech digit recognition research is growing decisively, and a bulk of digit recognition algorithms are used in European and a few Asian languages. Kui is a low-resourced tribal language locally used in several states of India. Despite its significance, there is not much research on Kui's speech. This research aims to present an in-depth analysis of novel Kui digit recognition using predefined machine learning (ML) techniques. For this purpose, we first gathered spoken numbers i.e. from 0 to 9 of eight different speakers containing a total of 200 words. Secondly, we choose the numbers: ଶୂନ (zero), ଏକ (one), ଦୁଇ (two), ତିନି(three), ସାରି(four), ପାସ (five), ସଅ (six), ସାତ (seven), ଆଟ (eight), ନଅ (nine). Meanwhile, we build nine different ML models to recognize Kui digits that take the Mel-frequency cepstral coefficients (MFCCs) method to extract the relevant features for model predictions. Finally, we compared the performance of ML models for both augmented and non-augmented Kui data. The result shows that the SVM+Augmentation method for Kui digit recognition combined obtained the highest accuracy of 83% than other methods. Moreover, the difficulties and potential prospects for Kui digit recognition are also highlighted in this work

Study on thyroid function test in pregnancy in a tertiary care hospital

Thyroid disorder is a very common endocrine problem encountered by pregnant women. Maternal thyroid dysfunction is associated with adverse outcome both in mother and fetus. The aim of the study: to find out the prevalence of various thyroid disorders in pregnant women attending antenatal clinic. Materials and methods. This prospective cross-sectional study was carried out in the Department of Obstetrics and Gynecology, F.M. Medical College & Hospital, Balasore, Odisha from June 2020 to May 2021. 220 women with uncomplicated singleton pregnancy were included. Serum Thyroid-stimulating hormone (TSH), free T4 (FT4) and free T3 (FT3) were estimated by using electro-chemiluminescence immunoassay technique. Results. Out of 220 pregnant women screened for thyroid dysfunction, 68 were found to have thyroid disorders. 27.3 % of pregnant women had subclinical hypothyroidism, 1.4 % had overt hypothyroidism, 1.8 % had subclinical hyperthyroidism and 0.5 % had overt hyperthyroidism. Prevalence of subclinical hypothyroidism was 6.36 % when the upper reference limit of TSH level taken as 4 mIU/L. Prevalence of thyroid disorder among pregnant women in the age groups 18–25 years, 26–30 years and 31–40 years were 28.9 %, 32.1 % and 38.9 % respectively. There were 35.5 %, 28 % and 26 % pregnant women with thyroid disorders in the first, second and third trimester respectively. Prevalence of both subclinical and overt hypothyroidism were more in multigravida compared to primigravida. Conclusion. Our study revealed high prevalence of thyroid disorders in pregnant women and maternal subclinical hypothyroidism was the most common pattern

A novel machine learning based hybrid approach for breast cancer relapse prediction

The second leading cause of death for women is breast cancer, which is growing. Some cancer cells may remain in the body, so relapse is possible even if treatment begins soon after diagnosis. Since there are now many machine learning (ML) approaches to recurrence prediction in breast cancer, it is important to compare and contrast them to find the most effective one. Datasets with many features often lead to incorrect predictions because of this. In this study, correlation-based feature selection (CFS) and the flower pollination algorithm (FPA) are used to improve the quality of the wisconsin prognostic breast cancer (WPBC) and University Medical Centre, Institute of Oncology (UMCIO) breast cancer relapse datasets respectively. Data imputation, scaling, pre-process raw data. The second stage uses CFS to select discriminative features based on important feature correlations. The FPA chose the optimum attribute combination for the most precise answer. We tested the approach using 10-fold cross-validation stratification. Various trials show 84.85% and 83.92% accuracy on the WPBC and UMCIO breast cancer relapse datasets, respectively. The hybrid method performed well in feature selection, increasing the accuracy of the relapse classification for breast cancer