976 research outputs found

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

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    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

    Impact of Environmental Regulations on the manufacturing Sector of India

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    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

    Smart Contract Assisted Blockchain based PKI System

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    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

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

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    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

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

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    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

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

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    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

    Fetal kidney length as a parameter for determination of gestational age from 20th week to term in healthy women with uncomplicated pregnancy

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    Background: Accurate assessment of gestational age is pivotal to give quality maternity care. Ultrasonographic fetal biometry is the most widespread method used to establish GA. Sonographic biometric parameters commonly used are Crown rump Length (CRL), Biparietal diameter (BPD), Head circumference (HC), Abdominal circumference (AC) and Femur length (FL). Fetal Kidney Length (FKL) is one of nontraditional parameter and more accurate method of GA estimation than BPD, FL, HC and AC after 24th week of gestation. This study evaluates role of FKL in estimation of GA and compared its accuracy with other established biometric indices.  Methods: Present study is a cross sectional study and includes healthy women who were certain of their LMP with prior regular menstrual cycles with uncomplicated pregnancy between 20 weeks of gestation to term. Maximum length of anyone single fetal kidney is measured from upper pole to lower pole at least thrice and mean of the measurements was taken. The data has been analyzed in SPSS-21 version and Microsoft word, excel have been used to generate graphs, tables etc.Results: Linear regression equation showed kidney length could predict gestational age with an accuracy ±9.048 days and predictability when combined with other biometric indices was ±8.299 days.Conclusions: The study shows good correlation between gestational age derived from FKL and gestational age from established biometric indices like BPD, HC, AC, and FL.FKL can be combined with the other four biometric indices to give a fair estimation of gestational age

    Congestion Managed Multicast Routing in Wireless Mesh Network

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    To provide broad band connectivity to the mobile users and to build a self-structured network, where it is not possible to have wired network, “Wireless Mesh Networks” are the most vital suitable technology. Routing in Wireless Mesh Networks is a multi-objective nonlinear optimization problem with some constraints. We explore multicast routing for least-cost, delay-sensitive and congestion-sensitive in optimizing the routing in Wireless mesh networks (WMNs). In this work different parameters are associated like edge cost, edge delay and edge congestion. The aim is to create a tree traversing which the set of target nodes are spanned, so as to make the cost and congestion to be minimum with a bounded delay over the path between every pair of source and destination. Since searching optimal routing satisfying multi constraints concurrently is an NP complete problem, we have presented a competent estimated algorithm certified with experimental results, which shows that the performance of presented algorithm is nearly optimum

    A Stochastic Game Framework for Efficient Energy Management in Microgrid Networks

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    We consider the problem of energy management in microgrid networks. A microgrid is capable of generating a limited amount of energy from a renewable resource and is responsible for handling the demands of its dedicated customers. Owing to the variable nature of renewable generation and the demands of the customers, it becomes imperative that each microgrid optimally manages its energy. This involves intelligently scheduling the demands at the customer side, selling (when there is a surplus) and buying (when there is a deficit) the power from its neighboring microgrids depending on its current and future needs. Typically, the transaction of power among the microgrids happens at a pre-decided price by the central grid. In this work, we formulate the problems of demand and battery scheduling, energy trading and dynamic pricing (where we allow the microgrids to decide the price of the transaction depending on their current configuration of demand and renewable energy) in the framework of stochastic games. Subsequently, we propose a novel approach that makes use of independent learners Deep Q-learning algorithm to solve this problem. Through extensive empirical evaluation, we show that our proposed framework is more beneficial to the majority of the microgrids and we provide a detailed analysis of the results
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