Make every mother and child count: a retrospective analysis of maternal mortality at medical college tertiary care hospital, Tamilnadu, India

Background: Maternal mortality is a human development indicator. Maternal deaths have serious implication on the family, society and nation. This study is aimed to study the determinants, common causes and recommendations for the prevention of possible causes of maternal mortality.Methods: A retrospective observational study of all maternal deaths for one year period from August 2014 to July 2015 was done in the Department of Obstetrics and Gynaecology, Raja Mirasudhar Hospital, Thanjavur Medical College, Thanjavur, Tamilnadu, India.Results: Over the study period there were 29 maternal deaths out of 14898 deliveries with 14220 live births amounting to a maternal mortality ratio of 204 per 100000 live births. Hypertensive disorders complicating pregnancy were the leading causes of maternal mortality amounting to 40%, while others were haemorrhage - 31%, anaemia with failure 17.2%, heart disease complicating pregnancy 6.4%, sepsis 3.2% and other causes 3.2%. Out of 29 maternal deaths 64.3% were in the age group 21-30 years and 75.7% belonged to lower socio economic status.Conclusions: The Maternal mortality ratio in our study was 204 per 100000live births. Of these the Maternal Mortality Ratio due to intramural deaths was 70 per 100000 live births and Maternal Mortality Ratio due to extra mural deaths (late referral) was 134per100000live births. Hypertensive disorders complicating pregnancy (40%) and its complications mainly HELLP (72.7%) and eclampsia (37.3%) were the most common cause of maternal deaths. Facility based maternal death review and State based maternal death review has contributed a lot in the analysis of the factors causing and compounding maternal mortality and reduction of maternal mortality and its ratio in Tamilnadu

Detecting Inception of Hydrodynamic Cavitation Noise of Ships using Quadratic Phase Coupling Index as an Indicator

There is ever increasing interest in underwater noise control onboard ships as part of concerted efforts to reduce ship’s radiated noise. Reduction of radiated noise is considered important as it will affect the performance of hydro-acoustic systems such as sonars, echo sounders, towed systems, etc. Out of three major sources of noise onboard ships, viz., machinery, propeller, and hydrodynamic noise, propeller noise is considered a major source beyond certain speed at which propellers cavitate produces cavitation noise. The inception speed of propeller cavitation is generally accompanied by sudden increase in radiated noise level of 8-15 dB when measured using a hydrophone placed on the seabed. This paper attempts to establish the concept of quadratic phase coupling index as an indicator to detect inception of cavitation of ship propellers. This concept was tested on actual ship radiated noise data measured at sea for evaluating its effectiveness.Defence Science Journal, Vol. 65, No. 1, January 2015, pp.53-62, DOI:http://dx.doi.org/10.14429/dsj.65.788

A Novel Approach for Multi Variant Classification of Medical Data in Short Text

457-462Data Mining Techniques has attained its momentum in several areas, and its efficient performance in decision support has outperformed and made it a reliable choice. The medical world is one such empirical domain in which a perfect decision at right time would turn out to be a lifesaver. Medical data figures out to be majorly multi-dimensional, where relevant feature extraction is a challenging factor. Several classification approaches like SVM, Decision Trees, and Naive Based are considered to handle these profound challenges. One such challenge discussed in our paper emphasizing on Medical decision support system with Machine Learning (ML) Methodology considering diseases and treatments with their semantic relations in the document of Pub med abstracts. The proposed Multi variant classification framework aims at reducing data into attributes using PCA Transformation infusion with an efficient classification Algorithm - CNB. Our computed results are comparatively successful in attaining ultimate outcomes concerning performance metrics like Accuracy, Precision, Recall, and Time. The strength of our work lies in presenting an efficient approach for elevating enhanced decisions in Health care

A NOVEL APPROACH FOR MULTI VARIANT CLASSIFICATION OF MEDICAL DATA IN SHORT TEXT

Data Mining Techniques has attained its momentum in several areas, and its efficient performance in decision support has outperformed and made it a reliable choice. The medical world is one such empirical domain in which a perfect decision at right time would turn out to be a lifesaver. Medical data figures out to be majorly multi-dimensional, where relevant feature extraction is a challenging factor. Several classification approaches like SVM, Decision Trees, and Naive Based are considered to handle these profound challenges. One such challenge discussed in our paper emphasizing on Medical decision support system with Machine Learning Methodology considering diseases and treatments with their semantic relations in the document of Pub med abstracts. The proposed Multi variant classification framework aims at reducing data into attributes using PCA Transformation infusion with an efficient classification Algorithm - CNB. Our computed results are comparatively successful in attaining ultimate outcomes concerning performance metrics like Accuracy, Precision, Recall, and Time. The strength of our work lies in presenting an efficient approach for elevating enhanced decisions in Health care

The generalized dice similarity measures for multiple attribute decision making with hesitant fuzzy linguistic information

In this paper, we shall present some novel Dice similarity measures of hesitant fuzzy linguistic term sets and the generalized Dice similarity measures of hesitant fuzzy linguistic term sets and indicate that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute decision making models with hesitant fuzzy linguistic term sets. Finally, a practical example concerning the evaluation of the quality of movies is given to illustrate the applicability and advantage of the proposed generalized Dice similarity measure

Make every mother and child count: a retrospective analysis of maternal mortality at medical college tertiary care hospital, Tamilnadu, India

Background: Maternal mortality is a human development indicator. Maternal deaths have serious implication on the family, society and nation. This study is aimed to study the determinants, common causes and recommendations for the prevention of possible causes of maternal mortality.Methods: A retrospective observational study of all maternal deaths for one year period from August 2014 to July 2015 was done in the Department of Obstetrics and Gynaecology, Raja Mirasudhar Hospital, Thanjavur Medical College, Thanjavur, Tamilnadu, India.Results: Over the study period there were 29 maternal deaths out of 14898 deliveries with 14220 live births amounting to a maternal mortality ratio of 204 per 100000 live births. Hypertensive disorders complicating pregnancy were the leading causes of maternal mortality amounting to 40%, while others were haemorrhage - 31%, anaemia with failure 17.2%, heart disease complicating pregnancy 6.4%, sepsis 3.2% and other causes 3.2%. Out of 29 maternal deaths 64.3% were in the age group 21-30 years and 75.7% belonged to lower socio economic status.Conclusions: The Maternal mortality ratio in our study was 204 per 100000live births. Of these the Maternal Mortality Ratio due to intramural deaths was 70 per 100000 live births and Maternal Mortality Ratio due to extra mural deaths (late referral) was 134per100000live births. Hypertensive disorders complicating pregnancy (40%) and its complications mainly HELLP (72.7%) and eclampsia (37.3%) were the most common cause of maternal deaths. Facility based maternal death review and State based maternal death review has contributed a lot in the analysis of the factors causing and compounding maternal mortality and reduction of maternal mortality and its ratio in Tamilnadu

EC-STCRA: Energy Conserved – Supervised Termite Colony based Role Assignment scheme for Wireless Sensor Networks

AbstractConserving energy and ensuring security are the main challenges of Wireless sensor Networks (WSNs). Energy at the sensors must be preserved to increase the lifetime of the network. Clustering helps in reducing the number of transmissions between the Cluster Head (CH) and the Base Station (BS). In this paper, an Energy Conserved - Supervised Termite Colony based Role Assignment (EC-STCRA) scheme is proposed to conserve energy. The network is trained to provide better performance by incorporating efficient clustering, routing and security schemes. The CHs are randomly selected, and the soldier and the worker nodes are appointed based on their location and Residual Energy (RE). Efficient paths to the BS are found by selecting the worker nodes with high RE. The soldiers protect the network from attacks like Denial of Service (DoS), flooding and spoofing by maintaining an Active List (AL) of reliable nodes along with a Warning List (WL) and a Dead List (DL) of malicious nodes. EC-STCRA outperforms the existing Genetic algorithm (GA) and Ant Colony Optimization (ACO) based clustering and routing schemes in terms of Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), throughput, delay, Residual Energy (RE) and network lifetime

Correlation between maxillary central incisor crown form and maxillary dental arch form: A Model-Based morphometric, cross-sectional study

The crown form of maxillary central incisor tooth is one of the vital phenomenon for a person's esthetics. Its crown form has been compared with other anatomical parameters such as arch form and facial form. Three different classes of tooth forms which relate to square, tapered, and ovoid forms are identified. The aim of this study was to morphometrically evaluate the correlation between maxillary dental arch form and the maxillary central incisor crown form. Dentate cast models of fifty male and fifty female normal occlusion controls in the age group of 18–23 years were analyzed. The mesiodistal (MD) dimensions of the maxillary central incisors were measured at incisal (MD_I) and at gingival (MD_G) levels. The transverse widths of maxillary casts were measured at the first molar and at the first premolar levels. The measured data were statistically analyzed using the SPSS software. The MD dimensions of maxillary central incisor were significantly greater in males than females. The ratio between the two MD dimensions also varied significantly among genders. The intermolar width (IMW) and inter first premolar width (IPmW) between males and females were highly significant (P < 0.05), whereas the ratio between these two parameters in males and females was not significant (P = 0.43). Eighty-eight percentage of the participants were found to have an ovoid type of maxillary arch, while only 45% of them had the ovoid form of maxillary central incisors. The MD_I and the IMW were found to be in the ratio of 1:5.5 in both genders. The MD_G and the IPmW were in the ratio of 1:4.7 in males and 1:4.5 in females. There was a weak positive correlation between MD_I and IMW (r2 = 0.146) and between MD_G and IPmW (r2 = 0.05). No significant concordance between the maxillary central incisor crown form and the maxillary arch form was found in this study