Modeling of breakdown voltage of solid insulating material using artificial neural network

The voids or cavities within the solid insulating material during manufacturing are potential sources of electrical trees which can lead to continuous degradation and breakdown of insulating material due to Partial Discharge (PD). To determine the suitability of use and acquire the data for the dimensioning of electrical insulation systems breakdown voltage of insulator should be determined. A major field of Artificial Neural Networks (ANN)) application is function estimation due to its some useful properties, such as, non-linearity and adaptively especially when the equation describing the function is unknown. In this project, the breakdown voltage due to PD in cavities for five insulating materials under AC conditions has been predicted as a function of different input parameters namely the thickness of the insulating sample ‘t,’ the thickness of the void ‘t1’ diameter of the void ‘d’ and relative permittivity of materials by using the ANN model. The requisite training data are obtained from experimental studies performed on a Cylinder-Plane electrode. The voids are artificially created with different measures. Detailed studies have been carried out to determine the ANN model parameters which give the best results. On completion of training, it is found that the ANN model is capable of predicting the breakdown voltage Vb = f (t, t1, d, ) very efficiently and with a small value of Mean Absolute Error. The system has been predicted using MATLAB

Risk factors for ectopic pregnancy: an institutional study in a tertiary care hospital

Background: Ectopic pregnancy is the leading cause of maternal death during the 1st trimester of pregnancy, accounting for approximately 10% of all pregnancy related deaths. A better understanding of ectopic pregnancy risk can help prevent its occurrence. The present study was designed to evaluate the ectopic pregnancy risk factors and their strength of association with ectopic pregnancy at a tertiary care hospital.Methods: It was a prospective study with 104 cases of ectopic pregnancy and 125 controls conducted in the Department of Obstetrics and Gynecology, SCB Medical College, Cuttack for a period of 1 year. Detailed history suggestive of risks factor for ectopic pregnancy, menstrual and obstetrics history was taken. General, systemic, abdominal and vaginal examination was done. Diagnosis of ectopic pregnancy was confirmed by clinical examination, urine pregnancy test, ultrasonography and culdocentesis and only confirmed cases were included in the study group. Healthy pregnant women were taken as control group.Results: The study revealed that the risk of ectopic pregnancy was associated with the traditional risk factors including previous EP [Adjusted odds ratio (AOR) = 9.98, 95% CI: 0.89-11.1%], previous infertility (AOR= 7.29, 95% CI:2.53-21.0) and previous history of sterilization (AOR=12.47,95% CI: 3.50 - 44.4) and previous history of abortion (AOR= 3.10, 95% CI: 1.53-6.30). Age comparison between cases and controls revealed that the ODDS of having ectopic pregnancy was 4 times in the age group 30 to 35 years as compared to uterine pregnancy and this difference was statistically significant (P value = 0.007).Conclusions: Risk factors such as previous ectopic pregnancy, induction of ovulation, intra uterine device usage, abortion as well as increased maternal age along with recent diagnostic tools aid in early detection of ectopic pregnancy in women resulting in proper and timely treatment

Genetic and Multilocation Evaluation of High Yielding Provenances of Bhimal (\u3cem\u3eGrewia optiva\u3c/em\u3e) on Farmers’ Fields in North Western Himalayas

Agroforestry is the inclusion of woody perennial within farming systems, has been practiced as a traditional land use and livelihood option since time immemorial (FSI 2013). It is being practiced on agricultural lands for fuel wood and fodder (Khybri et al., 1992), as well as medicinal and fruit trees (Bijalwan, 2011; Rathore et al., 2014) enabling food security (Narain 1998), non timber forest products, timber and shelter etc. A number of different (185) agroforestry systems are popular among farmers in different agro-climatic regions (Solanki, 2006). Grewia optiva Drummond (Bhimal) is an important agroforestry tree species primarily grown for green fodder in the north west Himalayas (Khybri et al., 1992; Dhyani, 2009). It is distributed throughout the sub-Himalayan tract upto an altitude of 1800m. Therefore, the present study was envisaged to monitor the performance of three best provenances of Bhimal (Mehta et al., 2011) on farmers’ fields at four locations comprising middle hill elevations and valley zones and their effect on field crops

Fungal systematics and evolution : FUSE 7

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Not AvailableCarissa carandas Linn. is a large dichotomously branched evergreen shrub. It has several medicinal and nutritional properties. An experiment was conducted considering two types, viz., pinkish-green and pinkish-white to compare the phytochemical changes in perspective of antioxidant activity during storage. In fresh fruits, the maximum ascorbic acid content (50.98 mg/100 g) was recorded in pinkish green fruits as compared to pinkish-white (36.86 mg/100 g). Similarly, the scavenging activity of methanol extract of pinkish-green fruits was found significantly higher (89.57%) as compared to pinkish-white fruits (86.27%) in fresh samples. However, the minimum loss in phenol content (11.36%) was recorded in pinkish-white type during storage upto 8 days. Therefore, karonda fruits may be considered as an important phyto-chemical source for making different traditional medicines.Not Availabl

A Multilevel Image Thresholding Using Particle Swarm Optimization

Abstract — Image Thresholding is one simplest method of image segmentation, which partitions the image into several objects on the basis of one or more threshold values. Threshold values are the values chosen from the intensity values of the image. In this paper, 8-bit unsigned gray scale images are taken as sample where the intensity values ranges from 0 to 255. Here Kapur's entropy criterion method is used which i a function of threshold values and is optimized by the advanced swarm based optimization technique named as particle swarm optimization (PSO). Particle swarm optimization is a nature-inspired methodology which mimics the food searching technique of birds. In this paper PSO takes Kapur's entropy criterion method as fitness function and gives the optimized threshold values to segment the image. This method gives the better result using small swarm size and few number of iterations comparing to the traditional image thresholding technique.

Fuzzy Approach to Detect and Reduce Impulse Noise in RGB Color Image

Abstract- This paper mainly focuses on image enhancement technique using soft computing approach like fuzzy sets. Image enhancement primarily covers noise detection and reduction from digital color image. To overcome the color disorder on edge and texture pixel, here each color component of a pixel is correlated to the other two corresponding color components of the same pixel. Here filtering is applied to only the corrupted pixels found by the fuzzy approach to improve the complexity and to avoid the color disorder at edges. An experimental result shows that the proposed method in this paper provides significant improvement as compared to the other non-fuzzy and fuzzy filters. Index terms- Image processing, impulse noise, RGB Color, fuzzy logic, fuzzy rule based system, membership function. I

Asymptomatic papules over central and pericentral areas of the face

We report the case of a 24-year-old college girl, presenting with numerous acneiform papular eruptions over the central part of the face