Time filter

Source Type

Malik F.R.,Riphah International University | Malik B.B.,Shaheed Benazir Bhutto Women University | Irfan M.,Riphah International University
Journal of Postgraduate Medical Institute | Year: 2015

Objective: To compare the frequency of postnatal depression in women following Normal Vaginal Delivery and Caesarian Section Methodology: A comparative study was conducted in Departments of Obstetrics and Gynecology of Lady Reading Hospital, Khyber Teaching Hospital and Hayatabad Medical Complex, Peshawar from November 2009 to January 2010. A total of 100 women; 50 cases of Normal Vaginal Delivery and 50 cases of Caesarian Sections were included in the study through purposive, non-probability sampling technique. A semi-structured demographic proforma and Edinburg Post-Natal Depression Scale (EPNDS) were used for data collection by interviewing the cases between 1st and 8th post partum weeks. All findings were recorded in SPSS and excel sheets. Chi square test was applied as the test of significance and P- value of less than 0.05 was considered significant. Results: The mean age of the sample was 29.68+ 6.8 years (Range 15-52 years). In women that underwent Caesarean Section (n=50), 29 (58%) were found as having depressive illness while in the group of women that gave birth through Normal Vaginal delivery (n=50), 12 (24%) were having depression (p- value < 0.001). Conclusion: The study concluded that postnatal depression is significantly more common in the females undergoing caesarian sections as compared to the normal vaginal deliveries. © 2015, J post med inst. All Rights Reserved. Source

Khan S.,University of Dammam | Azam H.,Khyber Medical College | Salahuddin N.,Shaheed Benazir Bhutto Women University
Macedonian Journal of Medical Sciences | Year: 2015

BACKGROUND: End Stage Renal Failure (ESRD) is the last stage of the chronic renal failure in which kidneys become completely fail to function. AIM: The basic aim of this study was to discover the important risk factors of ESRD and to construct a model for prediction of the ESRD patients in various hospitals of Peshawar, Pakistan. MATERIAL AND METHODS: The data were collected from the patients of renal diseases from three major hospitals of Peshawar. Brown method was used to obtain initial model, then backward elimination logistic regression analysis was performed to find the significant variables (risk factors). The response variable (ESRD) in this study is binary; therefore, logistic regression analysis is used to identify the significant variables. A Statistical Package GLIM and SPSS were used for fitting the model and for finding the significant variables. RESULTS: The backward elimination procedure selects predictor variables diabetic, hypertension, glomerulonephritis and heredity, for males. Thus, these variables are the main causes of ESRD. For females, the predictor variables selected are hypertension & (Diabetic*Hypertension), which means that hypertension and hypertensive diabetic are significant causes of ESRD. CONCLUSION: Our main conclusion from this analysis is that diabetic, hypertension and glomerulonephritis are the significant risk factors of ESRD. © 2015 Salahuddin Khan, Tariq Hussain, Hashimuddin Azam, Najma Salahuddin. Source

Fida M.-R.,Shaheed Benazir Bhutto Women University | Ali M.,Institute of Management Sciences
2013 IEEE 11th Malaysia International Conference on Communications, MICC 2013 | Year: 2013

Frequent change in the topology of a disrupted social network is a barrier in using traditional routing protocols. One way to deal with this problem is to collect mobility profiles of nodes and to utilize them for future routing decisions. The solution however lacks scalability since it is difficult for nodes to keep updated information of the whole network. The paper thus devises a scalable scheme that exploits the limited social circles of the mobile device owners; i.e. it breaks network into social communities and employs a fine-grained heuristic routing scheme for intra-community communication. Moreover the paper specifies a simple method for identification of bridging nodes to transfer message to destination lying outside the community. The idea paper is expected to bring a near to optimal routing solution for disrupted social networks. © 2013 IEEE. Source

Gul A.,University of Essex | Gul A.,Shaheed Benazir Bhutto Women University | Perperoglou A.,University of Essex | Khan Z.,University of Essex | And 5 more authors.
Advances in Data Analysis and Classification | Year: 2016

Combining multiple classifiers, known as ensemble methods, can give substantial improvement in prediction performance of learning algorithms especially in the presence of non-informative features in the data sets. We propose an ensemble of subset of kNN classifiers, ESkNN, for classification task in two steps. Firstly, we choose classifiers based upon their individual performance using the out-of-sample accuracy. The selected classifiers are then combined sequentially starting from the best model and assessed for collective performance on a validation data set. We use bench mark data sets with their original and some added non-informative features for the evaluation of our method. The results are compared with usual kNN, bagged kNN, random kNN, multiple feature subset method, random forest and support vector machines. Our experimental comparisons on benchmark classification problems and simulated data sets reveal that the proposed ensemble gives better classification performance than the usual kNN and its ensembles, and performs comparable to random forest and support vector machines. © 2016 The Author(s) Source

Sheng Q.,Harbin Engineering University | Khalid S.S.,Chinese Academy of Agricultural Sciences | Xiong Z.,Chinese Academy of Agricultural Sciences | Sahib G.,Shaheed Benazir Bhutto Women University | Zhang L.,Harbin Engineering University
Journal of Marine Science and Application | Year: 2013

In this paper, hydrodynamic analysis of vertical axis tidal turbine (both fixed pitch & variable pitch) is numerically analyzed. Two-dimensional numerical modeling & simulation of the unsteady flow through the blades of the turbine is performed using ANSYS CFX, hereafter CFX, which is based on a Reynolds-Averaged Navier-Stokes (RANS) model. A transient simulation is done for fixed pitch and variable pitch vertical axis tidal turbine using a Shear Stress Transport turbulence (SST) scheme. Main hydrodynamic parameters like torque T, combined moment C M, coefficients of performance C P and coefficient of torque C T, etc. are investigated. The modeling and meshing of turbine rotor is performed in ICEM-CFD. Moreover, the difference in meshing schemes between fixed pitch and variable pitch is also mentioned. Mesh motion option is employed for variable pitch turbine. This article is one part of the ongoing research on turbine design and developments. The numerical simulation results are validated with well reputed analytical results performed by Edinburgh Design Ltd. The article concludes with a parametric study of turbine performance, comparison between fixed and variable pitch operation for a four-bladed turbine. It is found that for variable pitch we get maximum C P and peak power at smaller revolution per minute N and tip sped ratio λ. © 2013 Harbin Engineering University and Springer-Verlag Berlin Heidelberg. Source

Discover hidden collaborations