The adoption of static resource allocation parameter named Transmission Opportunity (TXOP) limit has been assigned for specific heterogeneous traffic flows in IEEE802.11e Enhanced Distributed Channel Access (EDCA) protocol. TXOP limit facilitates same categories multiple packets transmission until the allocated time expired. Due to the variation of traffic load in Wireless Campus Network (WCN), the fixed bandwidth reservation parameter is not sufficient to guarantee QoS for Interactive Multimedia (IMM) traffic flows. While the traffic load is very low, although, there is no same categories of traffic to transfer but others category of traffics have to wait until the current TXOP limit is expired. Thus, wastes the channel bandwidth over the network. In contrast, during high traffic load, fixed duration of time is not adequate to guarantee QoS because the packets loss occurs. Many researchers adjust the TXOP parameter dynamically to ensure QoS but still have some unresolved problem with it. This paper aims to employ Proposed Dynamic TXOP (PDTXOP) mechanism based on the current calculated queue size and pre-setting thresholds. A mathematical estimation of PDTXOP scheme has been developed to calculate the dynamic TXOP limit for different current high priority traffic queues in MAC layer. The evaluation of the PDTXOP has been done using Qualnet 5.1 simulator and measured the performance of the network using different performance metrics (jitter, end-to-end delay, throughput and packet delivery ratio). The simulation results demonstrate that the proposed scheme agrees to improve significantly about 40.99%, 36.36%, 14.80% and 17.91% respectively QoS performance of the IMM traffics.

The health landscape of most of the world today is an amalgamation of disparities, contrasts, complexities, and opportunities reflecting the vast multitude of spatial ‘uniqueness’ that exists around the globe. One of the features of medical geography that has made it so useful in health research is statistical spatial analysis, which enables the quantification and qualification of health events in comparison to a hypothetical distribution. This field is even more useful for developing countries where large number of population is vulnerable to infectious disease as malaria in relation to the environment. The main objective of this research work was to study the spatial distribution patterns of the common water related disease i.e. malaria in Rawalpindi district using spatial statistical techniques to identify the hot spots and the possible risk factor for those hot spots. The data regarding the disease patients from 2010 – 2012 was collected from the District Health Office Rawalpindi. Spatial statistical analyses were done in ArcGIS version 10. Demographic data was collected from the House of Statistics, Islamabad. Satellite images for landuse classification were purchased from SUPARCO and processed in ERDAS Imagine. Water samples were also collected from the study area for bacteriological testing to identify the presence or absence of any microbial contamination. Total number of samples collected was 450. The results of this study indicated that malaria incidence varies according to geographical location, with eco-climatic condition and showing significant positive spatial autocorrelation (global Moran’s I test statistics). Hotspots or location of clusters were identified using Getis-Ord Gi* statistic. Significant clustering of malaria incidence occurs in rural central part of the study area including Gujar Khan, Kaller Syedan and some part of Kahuta and Rawalpindi tehsil. Ordinary Least Square (OLS) regression analysis was conducted in ArcGIS to analyze the relationship of risk factors with the disease cases. Relationship of different land cover with the disease cases indicated that malaria was more related with the agriculture, low vegetation and water bodies land cover class. Temporal variation of disease cases of malaria showed significant positive association with the meteorological variables including average monthly rainfall and temperature. The results of the study suggested that water supply and sewage system and solid waste collection system needs a serious attention to prevent any outbreak in the study area. This dissertation highlights the usefulness of geography in the epidemiological studies. Need of the hour for the health research is to develop more projects that make the health professionals and geographers to work together in their research so that both analysis and interpretation can be taken to higher academic levels. This cooperation will no doubt continue to solidify the role that geography plays in health research, and lead to more effective and efficient disease control and prevention strategies with direct consequences for global human health.

Missing data are likely to be a bigger problem for the behavioral scientist as the data gathering techniques continue to improve. In addition, as “Big Data” is encountered in a variety of different fields, such as medicine or management, analysis of parts of the data sets rather than the entire data set may be required for computational speed. This article used an artificial data design to test the adequacy of the multidimensional scaling procedure EXSCAL (EXtended Individual Differences SCALing) under the presence of varying amounts of missing data and error level in the data. Some performance measures were developed to assess how well the program recovers the stimulus coordinates, subject weights, and stimulus specificities. The measures were generally very good and suggest that EXSCAL handles missing data very well. Other factors such as presence of specificities, and amount of error were determined to be a greater influence on the performance of the program than the presence of missing data.

Today, industries high developments and technology increasing progress cause some problems like air pollution, job side effects and occupational diseases which force us to implement a HSE-MS management system in different projects. Implementation of this system is the need to spend money and time, for this reason, some managers are hesitating to implement it completely.\nThis paper seeks to measure the profitability of investment in HSE-MS system using the internal rate of return (IRR) method as one of the most attractive economic evaluation index. To this end, we should predict the values of project cash flow stream in terms of different time periods. So the calculation of these values as crisp numbers is so risky and the accuracy of final results will be ambiguous. Hence, this paper define the values of cash flow streams as fuzzy numbers and then calculate the profitability of the HSE-MS system implementation project using the IRR measure under fuzzy environment. \nThe mean value of IRR was equal to 22% by using the FIRR. Also considering the point that the minimum value of IRR based on the FIRR was 14% and 18%, respectively, and the fact that, these values are greater than the market rate (7%), the HSE-MS system implementation is an economic and advisable project.\nThe economic evaluation of the HSE-MS system is performed using the greater possibility index. Also a power plant is investigated as a case study. Based on the obtained results, the HSE-MS system implementation is strictly advisable because of its benefits.

The paper presents a case study to predict the survival rate of oral cancer patients. Two predictive models, Linear Regression (LR), which is a contemporary statistical model and Multilayer Perceptron (MLP), which is an artificial neural network model, are designed and developed. The data of 1025 patients who visited a tertiary care centre during June 2004 and June 2009 is collected in non-randomized way and is used to build models. Analytical comparison of the performance of both the model is carried out. The experimental result shows that the classification accuracy of MLP model for training data is 70.05% and validation data is 69.76%, whereas classification accuracy of LR model for training data is 60.10% and validation data is 61.27%. After comparing on various evaluation criteria , it is concluded that the MLP model is a better model for predicting the survival rate of oral cancer patients, in comparison to LR model.

Aluminum zinc oxide (AZO), as one of the most promising transparent conducting oxide (TCO) material, has now been widely used in thin film solar cells. In this study the optimization process of the DC magnetron sputtered AZO films was carried out at room temperature by studying it’s structural, optical, electrical and morphological properties at different deposition times (5, 10, 15, 20 and 25 min’s) for its use as a front contact for the cadmium telluride (CdTe) based thin film solar cell. The structural study suggests that the preferred orientation of grains along (002) plane having hexagonal structure of the grains. The optical and electrical properties suggest that the films show an average transmission of 70% and a resistivity of the order of 10-4Ωcm. The morphology analysis suggests the formation of packed grains having a homogeneous surface.