Planned early birth versus expectant management for prelabour rupture of membranes at term

Objective: To compare the feto-maternal outcome of planned early birth versus expectant management (waiting) among patients with prelabor rupture of membrane at term (37 weeks or more) at LUMHS. Methodology: This randomized control trial was conducted at gynae and OBS department of Liqaut University of Medical and health Sciences from March 2015 to February 2016. Woman with uncomplicated PROM without signs of active labour, having single alive fetus with cephalic presentation and gestational age of 37 weeks to 42 weeks were included. Patients were equally divided in two groups as; Group-I (Planned early birth) patients received induction in form of prostaglandin E2 vaginal pessary maximum of two vaginal tablets were used 6 hours apart. Group-II (Expectant management) patients waited for spontaneous onset of labour with maternal and fetal monitoring if labour did not begin within 24/hour than induction started with oxytocin infusion or prostaglandin E2 vaginal passery to deliver the patient. Data was collected via study proforma and was analyzed by SPSS version 20. Results: Total 06 women were incorporated and most of the patients were between age group of 18 to 34 years in both groups (group A and group B) as 83.3% AND 80.0% respectively. C-section was done in 1 patient of group A and 6 patients of group B. C-section+puerperal sepsis were noted in 3 patients of group A and one patient of group B. Chorioamnionitis was noted in one case of group A and one case of group B. Chorioamnionitis with c-section was found in 1 patient of group A and two patients of group B. Peripartum sepsis was in 3 patients of group A and one patient of group B. However no maternal mortality and ICU admission were seen all the patients were normally discharges. Feto-maternal outcome was statistically insignificant in both groups (p=>0.05). Conclusion: Planned management (induction by prostaglandin E2 vaginal pessary) slightly decreases the risk of chorioamnionitis and caesarean section. Meanwhile both management options may not be very different and both methods can be successfully employed for the management of term PROM

Blood image analysis to detect malaria using filtering image edges and classification

Malaria is a most dangerous mosquito borne disease and its infection spread through the infected mosquito. It especially affects the pregnant females and Children less than 5 years age. Malarial species commonly occur in five different shapes, Therefore, to avoid this crucial disease the contemporary researchers have proposed image analysis based solutions to mitigate this death causing disease. In this work, we propose diagnosis algorithm for malaria which is implemented for testing and evaluation in Matlab. We use Filtering and classification along with median filter and SVM classifier. Our proposed method identifies the infected cells from rest of blood images. The Median filtering smoothing technique is used to remove the noise. The feature vectors have been proposed to find out the abnormalities in blood cells. Feature vectors include (Form factor, measurement of roundness, shape, count total number of red cells and parasites). Primary aim of this research is to diagnose malaria by finding out infected cells. However, many techniques and algorithm have been implemented in this field using image processing but accuracy is not up to the point. Our proposed algorithm got more efficient results along with high accuracy as compared to NCC and Fuzzy classifier used by the researchers recently

Blood image analysis to detect malaria using filtering image edges and classification

Malaria is a most dangerous mosquito borne disease and its infection spread through the infected mosquito. It especially affects the pregnant females and Children less than 5 years age. Malarial species commonly occur in five different shapes, Therefore, to avoid this crucial disease the contemporary researchers have proposed image analysis based solutions to mitigate this death causing disease. In this work, we propose diagnosis algorithm for malaria which is implemented for testing and evaluation in Matlab. We use Filtering and classification along with median filter and SVM classifier. Our proposed method identifies the infected cells from rest of blood images. The Median filtering smoothing technique is used to remove the noise. The feature vectors have been proposed to find out the abnormalities in blood cells. Feature vectors include (Form factor, measurement of roundness, shape, count total number of red cells and parasites). Primary aim of this research is to diagnose malaria by finding out infected cells. However, many techniques and algorithm have been implemented in this field using image processing but accuracy is not up to the point. Our proposed algorithm got more efficient results along with high accuracy as compared to NCC and Fuzzy classifier used by the researchers recently

Synthetic Grey Water Treatment Through FeCl3-Activated Carbon Obtained from Cotton Stalks and River Sand

The research objective was to reclaim greywater through simple, easily available, and cost-effective methods. For this purpose, an activated charcoal was prepared from biomass (cotton stalk) through the pyrolysis process and sand collected from river Indus. Both materials were subjected to separate columns and applied as filters. Whereas, the efficiency of both materials as filter media was analyzed on the synthetic grey water (SGW). The formulation of synthetic greywater was a complicated process because the selection of ingredients and their amount should not exceed from the real grey water. So, for the presence of fecal contamination, a small amount (10 ml L-1) of settled sewage was added to the distilled water, while to mimic the organic load, several chemical products of technical grade were also added. The physicochemical and microbiological characteristics of this SGW were tested before and after treatment. The results show that both mediums (AC and river sand) were very effective in the greywater treatment. The removal efficiency for BOD and COD was up to 91.2%, and 70% respectively. Similarly, the removal measure for turbidity was 91.3%. While the pH showed that the synthetic grey water was alkaline in nature with a value of 10 because the washing detergents used during the preparation of SGW, but after passing through both filter columns, pH was observed in between 7 and 8 units. Furthermore, the removal value examined after passing SGW from both columns for total coliforms was 46.87 CFU/100 ml from1500 CFU/100 ml

Utilization of Sawdust in Concrete Masonry Blocks: A Review

SDC (Sawdust Concrete) was developed in 19th century. It has been well recognized due to its lightweight and cost-effectiveness. Presently, developed countries have created opportunities to use wood waste in the concrete construction to reduce the environmental burden. Although SDC has received little consideration as a lightweight masonry block in building works but it has been intensively investigated in many countries for decades. The aim of this review is to summarize the last five years (2012-2016) research work related to utilization of sawdust in concrete masonry. However, it is important to explore existing ideas and approaches developed by previous researchers as a reference and guidance for the future research. There are lots of opportunities to develop lightweight concrete especially throughutilizing sawdust as a fine aggregate replacement material in concrete. However, this review paper is focusing on utilization of sawdust, as to reduce environmental impacts poses by the waste products of furniture industry and a by-product of wood industry. As a conclusion, this review paper summary the existing important ideas and useful information for the fellow researchers, as to enhance the utilization of sawdust to produce lightweight masonry units. It is recommended that considerable research is required on the sawdust cement blocks, which can deliver more confidence on their utilization as a green building construction material

Influence of Ground Coal Bottom Ash on the Properties of Concrete

The coal based thermal power plant in Malaysia produces annually around 1.7 million tons of coal bottom ash (CBA) as a discarded material which poses great environmental problems. Hence, the objective of this study is to utilize ground CBA as a supplementary cementing material in concrete. The oven dried original CBA was grinded for 20hours to achieve required fineness. The mixture of concrete was prepared with CBA proportion of 10, 20 and 30% by weight of cement. For the evaluation of density, water absorption, compressive and tensile strength of concrete, 48 specimens were cast. The workability of fresh mix concrete was also evaluated, and it was found to be decreased as the quantity of CBA increased in the mixture. However, the compressive and splitting tensile strength of concrete was also reduced with the addition of ground CBA but with 10% replacement has attended the targeted compressive strength at the age of 28days. Besides that, it was also observed that the influence of CBA on concrete is obvious in density as well as in water absorption. The density of concrete gradually decreased due to addition of ground CBA, concrete containing 10% ground CBA was likely to be similar to that of control mix and the opposite performance was noticed in water absorption. Hence, experimental findings of this study indicated potentiality of ground CBA as supplementary cementing material in concrete construction which will reduces the environmental concern

Probabilistic and Hybrid Model Checking Deployments for Wireless Sensor Networks

In the early stages of system development, model checking is a good practice for examining the WSNs (Wireless Sensor Networks). Model checking involves verifying a system\'s properties based on the system\'s finite state model. For varying applications like computers and wireless communication prior to expensive simulations, model checking has become a vital requirement in order to investigate the performance and reliability. In this paper for the first time, we are presenting probabilistic and hybrid model checking tools which are being implemented to analyse and verify the WSN applications and their examples. Here we are categorizing the model checking tools and presenting how they have been used for the investigation of various behaviours of WSN solutions. Consequently, this paper helps readers/researchers to choose the appropriate model checking tool and to get benefited in shape of validating their solutions. The paper has also highlighted the problems of existing model checking tools within WSN domain

Image Quality Assessment for Performance Evaluation of Focus Measure Operators

This paper presents the performance evaluation of eight focus measure operators namely Image CURV (Curvature), GRAE (Gradient Energy), HISE (Histogram Entropy), LAPM (Modified Laplacian), LAPV (Variance of Laplacian), LAPD (Diagonal Laplacian), LAP3 (Laplacian in 3D Window) and WAVS (Sum of Wavelet Coefficients). Statistical matrics such as MSE (Mean Squared Error), PNSR (Peak Signal to Noise Ratio), SC (Structural Content), NCC (Normalized Cross Correlation), MD (Maximum Difference) and NAE (Normalized Absolute Error) are used to evaluate stated focus measures in this research. . FR (Full Reference) method of the image quality assessment is utilized in this paper. Results indicate that LAPD method is comparatively better than other seven focus operators at typical imaging condition

Analysis of Booth Multiplier based Conventional and Short Word Length FIR Filter

The optimized implantation of digital filters has remained one of the challenging tasks, for FPGA (Field- Programmable Gate Array) based system designers, due to the involvement of very complex circuitry for multiplication. The multiplier consumes more recourse and hence results in less speed, being not the single step arithmetic operation. One way to carry out these implementations effectively is; to reduce the word length that will increase throughput in view of that. Since decays, SDM (Sigma-Delta Modulation) is used to convert the word length from multi-bit to single bit recurrently. This work is an extension of current trends of using SDM, in the design of Digital FIR (Finite Impulse Response) Filter, which is the most attractive component of DSP (Digital Signal Processor) In this work, we have presented single-bit ternary (0,+1,-1) and multi-bit FIR filter design, using the Booth multiplier technique, on small commercially used FPGA family, provided by Altera. Also, the performance analysis of designed filter with SWL (Short Word Length) using SDM and the conventional one (Multi-bit FIR Filter using general booth multiplier) is carried out. The results indicate that with consuming the resources one third of the conventional design, the sigma delta modulation based multiplier results six times more efficient in terms of achieved frequency, hence sum up the reason of using the sigma delta modulation in about all DSP applications