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The purpose of this research is to analyze the association between corporate governance and firm performance. Specifically, it examines the impact of CEO duality on board characteristics and its relationship with firm performance through dynamic penal estimation. The findings of this research are based on a sample of 191 listed non-financial firms over the period 2004-2014. We document that corporate governance plays a pivotal role in determining the financial performance of firms operating in Pakistan. Consistent with past studies, findings of this research also show some statistical variations among the sampled firms (large and small size). CEO duality compromises the efficiency of board independence. Further, the non-linear relationship of managerial ownership with performance is also depicted through the results of this study. Keywords: Corporate governance, accounting-market based measures, firm performance

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The objective of this study is to investigate the impact of financial leverage on corporate financial performance of Pakistan's textile sector from 1999-2012 using panel data. The leverage-performance relationship is examined with a special focus on the Global Financial Crisis of [2007][2008]. Both accountingbased (Return on Assets -ROA) and market-based (Tobin's Q) measures of corporate financial performance are used. Regression analysis is performed with and without inclusion of financial crisis dummy. Total Debt to Total Assets (TDTA), Long Term Debt to Total Assets (LDTA), Short Term Debt to Total Assets (SDTA) and Debt to Equity (DE) ratios are used as proxies for financial leverage whereas firm's size and firm's efficiency are used as control variables. The results indicate that financial leverage has a negative impact on corporate performance when measured with ROA. Whereas in case of Tobin's Q, SDTA coefficient is positive. It can be concluded that since cost of borrowing is high in Pakistan and debt capital markets are less developed, firms are forced to resort to banks as their source of debt finance and thus have to repay huge amount of principal and interest which has a heavy toll on their financial health. In addition to this, financial crisis was found to have a negative impact on corporate performance and also affect the leverage-performance relationship.

In this paper, we proposed a new wireless localization technique based on the ideology of social network analysis (SNA), to study the different properties of networks as a graph. Centrality is a main concept in SNA, so we propose using closeness centrality (CC) as a measurement to denote the importance of the node inside the network due to its geo-location to others. The node with highest degree of CC is chosen as a cluster heads, then each cluster head can form its trilateration process to collect data from its cluster. The selection of closest cluster based on CC values, and the unknown node’s location can be estimated through the trilateration process. To form a perfect trilateration, the cluster head chooses three anchor nodes. The proposed algorithm provides high accuracy even in different network topologies like concave shape, O shape, and C shape as compared to existing received signal strength indicator (RSSI) techniques. Matlab simulation results based on practical radio propagation data sets showed a localization error of 0.32 m with standard deviation of 0.26 m.

Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m.

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