http://hdl.handle.net/123456789/15 2026-04-04T12:05:59Z 2026-04-04T12:05:59Z Qazi Zia Ullah Farman Ullah Fazal Wahab Karam Shahzad Hassan Sungchang Lee http://hdl.handle.net/123456789/7171 2018-08-08T06:31:14Z 2017-01-01T00:00:00Z

A MOGA-Markov Chain Optimized Ranking Algorithm for Wireless Access Networks in Heterogeneous Environment Qazi Zia Ullah; Farman Ullah; Fazal Wahab Karam; Shahzad Hassan; Sungchang Lee The mounting customer demands for bandwidth-desirous services are deriving for a cost effective, robust, and high capacity wireless access network. The end users expect a satisfactory and economical delivery of “Quad-play” applications (voice, video, data, and mobility) and rich-media applications (multimedia, interactive gaming, and meta-verse) over the wireless network. In last two decades, a remarkable evolution of wireless networks is observed. Moreover, after the advent of software defined radio enabled wireless sets, the selection of the optimum wireless access network for different applications (live video streaming, online gaming, voice calling and browsing) is gaining vital importance. In this paper, a ranking algorithm based on Markov chain optimized learning approach is formulated for the heterogeneous environment. The algorithm is designed on the basis of most important Quality of Service (QoS) parameters like throughput, delay/error and cost. The proposed technique is robust against the change in number of available networks where, previously proposed techniques TOPSIS, VIKOR and RafoQ are unable to handle the change in available networks adequately. The Simulation results verify the selection of optimal access network for varying applications conforming to defined ranking algorithm.

2017-01-01T00:00:00Z Usman Hashmi Ammar Ajmal Arsalan Akhter Shehzad Khalid Waleed Manzoor http://hdl.handle.net/123456789/4984 2017-11-22T05:39:39Z 2016-01-01T00:00:00Z

Application Layer Time Synchronization Utilizing Symbol Timing Recovery In Wireless Sensor Networks Usman Hashmi; Ammar Ajmal; Arsalan Akhter; Shehzad Khalid; Waleed Manzoor Information sharing, scheduling and organization in a Wireless Sensor Network (WSN) is highly dependent upon achieving the same notion of time. Hence timing synchronization becomes a vital concern in most of the distributed wireless networks. Similarly, different layers of a network also need to synchronize among themselves for efficient performance and energy optimization. Bandwidth, energy consumption and storage capacity along with the high density of nodes are some of the practices limitations present in the WSNs. Symbol timing recovery (physical layer time synchronization) is used in this work for time synchronization at the application layer to achieve higher energy conservation.

2016-01-01T00:00:00Z Zuhaib Musaddiq Bushra Sabir http://hdl.handle.net/123456789/4988 2017-11-22T05:48:24Z 2015-01-01T00:00:00Z

Heuristic Based Labeling Using Edgelet Based Contour Detection for Low Resolution Small to Medium Scaled Monocular Pedestrian Detection Zuhaib Musaddiq; Bushra Sabir Outdoor pedestrian detection is one of most important, primary and challenging preprocessing step for any automated visual surveillance activity ranging from event to activity detection. Currently used algorithms are resolution, scale and clothing dependent, their performance decreases as resolution of camera decreases and the size of pedestrian decreases to small scale (30-80 pixels). Moreover, regions like Middle East where loose clothes are mostly used the performance of these systems get worse. The reason behind the failure of these systems is that most of them target the contour information of pedestrian and as the scale decreases or cloth varies the contour information becomes ambiguous. Noise accumulation, wide area view, low resolution, outdoor environment artifacts, low frame rate further add to the complexity of pedestrian detection. The paper proposes a pedestrian detection algorithm that detects the pedestrian of small scale from the low frame rate (5 frames per second) video captured by low resolution CCTV camera (352x288) resolution. The algorithm is clothing and illumination invariant and proposes two main contributions: first, motion cues and edgelets based contour detection (ECD) are used to target temporal and low level pixel details, handling clothing variation and providing a heuristic window for pedestrian detection and second, the heuristic window is searched for presence of pedestrian using linear support vector machine (SVM)classifier trained over hybrid of histogram of oriented gradients (HOG) and statistical shape based feature vector.

2015-01-01T00:00:00Z Arsalan Akhter Muhammad Tahir Ammar Ajmal Syed Muhammad Hashmi http://hdl.handle.net/123456789/5002 2017-11-22T06:49:55Z 2015-01-01T00:00:00Z

A Review of Techniques and Approaches in Robocup @Home Arsalan Akhter; Muhammad Tahir; Ammar Ajmal; Syed Muhammad Hashmi RoboCup is a platform for professionals, students and enthusiasts to demonstrate their technical skills in the domain of Artificial Intelligence for everyday life usage like in soccer, home or work. RobCup@Home is a part of RoboCup, which deals with domestic service Robots. In this paper we discuss different development approaches, components and algorithms used to design and develop Robots used in the RobCup@Home League.

2015-01-01T00:00:00Z