Fahad Khan

Academic performance is among the several components of academic success. Many factors, including socioeconomic status, student temperament and motivation, peer and parental support influence academic performance. Our study aims to investigate the determinants of academic performance with emphasis on the role of parental styles in adolescent students in Peshawar Pakistan. A total of 456 students from 4 public and 4 private schools were interviewed. Academic performance was assessed based on self-reported grades in the latest internal examinations. Parenting styles were assessed through the administration of the Parental bonding instrument. Regression analysis was conducted to assess the influence of socio-demographic factors and parenting styles on academic performance. Factors associated with and differences between “care” and “overprotection” scores of fathers and mothers were analyzed. Higher socio-economic status, father’s education level and higher care scores were independently associated with better academic performance in adolescent students. Affectionless control was the most common parenting style for fathers and mothers. When adapted by the father, it was also the only parenting style independently improving academic performance. Overall, mean “care” scores were higher for mothers and mean “overprotection” scores were higher for fathers. Parenting workshops and school activities emphasizing the involvement of mothers and fathers in the parenting of adolescent students might have a positive influence on their academic performance. Affectionless control may be associated with improved academics but the emotional and psychosocial effects of this style of parenting need to be investigated before recommendations are made.

Streaming network traffic measurement and analysis is critical for detecting and preventing any real-time anomalies in the network. The high speeds and complexity of today's networks, coupled with ever evolving threats, necessitate closing of the loop between measurements and their analysis in real time. The ensuing system demands high levels of programmability and processing where streaming measurements adapt to the changing network behavior in a goal-oriented manner. In this work, we exploit the features and requirements of the problem and develop an application-specific FPGA-based closed-loop measurement system. We make novel use of fine-grained partial dynamic reconfiguration as underlying reprogramming paradigm, performing low-latency just-in-time compiled logic changes in FPGA fabric corresponding to the dynamic measurement requirements. Our innovative dynamically reconfigurable socket offers 3× logic savings over conventional static solutions, while offering much reduced reconfiguration latencies over conventional PDR mechanisms. We integrate multiple sockets in a highly parallel CLM framework and demonstrate its effectiveness in identifying heavy flows in streaming network traffic. The results using an FPGA prototype offer 100 percent detection accuracy while sustaining increasing link speeds. © 1968-2012 IEEE.

Online network traffic measurements and analysis is critical for detecting and preventing any real-time anomalies in the network. We propose, implement, and evaluate an online, adaptive measurement platform, which utilizes real-time traffic analysis results to refine subsequent traffic measurements. Central to our solution is the concept of Multi-Resolution Tiling, a heuristic approach that performs sequential analysis of traffic data to zoom into traffic subregions of interest. However, MRT is sensitive to transient traffic spikes. In this paper, we propose three novel traffic streaming algorithms that overcome the limitations of MRT and can cater to varying degrees of computational and storage budgets, detection latency, and accuracy of query response. We evaluate our streaming algorithms on a highly parallel and programmable hardware as well as a traditional software-based platforms. The algorithms demonstrate significant accuracy improvement over MRT in detecting anomalies consisting of synthetic hard-to-track elephant flows and global icebergs. Our proposed algorithms maintain the worst-case complexities of the MRT while incurring only a moderate increase in average resource utilization. © 2013 IEEE.