Doctor of Philosophy

dissertationA fundamental characteristic of wireless communications is in their broadcast nature, which allows accessibility of information without placing restrictions on a user’s location. However, the ease of accessibility also makes it vulnerable to eavesdropping. This dissertation considers the security issues of spread spectrum systems and in this context, a secure information transmission system compromised of two main parts is presented. The first component makes use of the principle of reciprocity in frequency-selective wireless channels to derive a pair of keys for two legitimate parties. The proposed key generation algorithm allows for two asynchronous transceivers to derive a pair of similar keys. Moreover, a unique augmentation - called strongest path cancellation (SPC) - is applied to the keys and has been validated through simulation and real-world measurements to significantly boost the security level of the design. In the second part of the secure information transmission system, the concept of artificial noise is introduced to multicarrier spread spectrum systems. The keys generated in the first part of the protocol are used as spreading code sequences for the spread spectrum system. Artificial noise is added to further enhance the security of the communication setup. Two different attacks on the proposed security system are evaluated. First, a passive adversary following the same steps as the legitimate users to detect confidential information is considered. The second attack studies a more sophisticated adversary with significant blind detection capabilities

Fast Visual Tracking Using Spatial Temporal Background Context Learning

Visual Tracking by now has gained much provenience among researchers in recent years due to its vast variety of applications that occur in daily life. Various applications of visual tracking include counting of cars on a high way, analyzing the crowd intensity in a concert or a football ground or a surveillance camera tracking a single person to track its movements. Various techniques have been proposed and implemented in this research domain where researchers have analyzed various parameters. Still this area has a lot to offer. There are two common approaches that are currently deployed in visual tracking. One is discriminative tracking and the other one is generative tracking. Discriminative tracking requires a pre-trained model that requires the learning of the data and solves the object recognition as a binary classification problem. On the other hand, generative model in tracking makes use of the previous states so that next state can be predicted. In this paper, a novel tacking based on generative tracking method is proposed called as Illumination Inavariant Spatio Temporal Tracker (IISTC). The proposed technique takes into account of the nearby surrounding regions and performs context learning so that the state of the object under consideration and its surrounding regions can be estimated in the next frame. The learning model is deployed both in the spatial domain as well as the temporal domain. Spatial domain part of the tracker takes into consideration the nearby pixels in a frame while the temporal model takes account of the possible change of object location. The proposed tracker was tested on a set of 50 images against other state of the art four trackers. Experimental results reveal that our proposed tracker performs reasonably well as compared with other trackers. The proposed visual tracker is both efficiently with respect to computation power as well as accuracy. The proposed tracker takes only 4 fast Fourier transform computations thus making it reasonably faster. The proposed trackers perform exceptionally well when there is a sudden change in back ground illumination

Interference Localization for Uplink OFDMA Systems in Presence of CFOs

Multiple carrier frequency offsets (CFOs) present in the uplink of orthogonal frequency division multiple access (OFDMA) systems adversely affect subcarrier orthogonality and impose a serious performance loss. In this paper, we propose the application of time domain receiver windowing to concentrate the leakage caused by CFOs to a few adjacent subcarriers with almost no additional computational complexity. This allows us to approximate the interference matrix with a quasi-banded matrix by neglecting small elements outside a certain band which enables robust and computationally efficient signal detection. The proposed CFO compensation technique is applicable to all types of subcarrier assignment techniques. Simulation results show that the quasi-banded approximation of the interference matrix is accurate enough to provide almost the same bit error rate performance as that of the optimal solution. The excellent performance of our proposed method is also proven through running an experiment using our FPGA-based system setup.Comment: Accepted in IEEE WCNC 201

Robust Visual Tracking Using Illumination Invariant Features in Adaptive Scale Model

When entering into the realm of Computer Vision, the first thing which comes in to mind is Visual tracking. Visual tracking by far comes into one of the most actively investigated research areas because of the fact that it has an extensive collection of applications in areas such as activity recognition, surveillance, motion analysis and as well as human computer interaction. Some serious challenges of this area which still create hindrance in achieving 100% accuracy are abrupt appearance and pose changes of an object along with its background blockage due to blockages called occlusion, illumination and lighting variances and changes in scale of target object in the frames. Moreover, diverse algorithms had been proposed for the resolution of said issue. Now in such cases, if we study the statistical analysis of correlation between two frames in a certain video, it can be efficiently utilized to get the most exact location of the targeted object. The algorithms in existence today do not completely exploit a strong spatio-temporal relationship that very often occurs between the two successive frames in a video sequence. Recent advances in correlation-based tracking systems have been proposed to address the problem in successive frames. In this thesis a very simple yet quite speedy and robust algorithm that in actual brings all the relevant information used for Visual Tracking. Two of the Models proposed are the “Locality Sensitive Histogram” and “Discriminative Scale Tracking Method”. These are robust enough to the variations which are based on appearance which are normally presented by blockage, pose, illumination and lighting variations alike. A scheme is proposed called scale adaptation which is very much clever to adapt variations of targeted scale in the most efficient manner. The Discriminative Scale Tracking Method is used for detection as well as scale change ultimately resulting in an effective tracking method in the end. Various different experiments with the best algorithms have demonstrated on challenging sequences that the suggested methodology attains promising results as far as robustness, accuracy, and speed is concerned

Servitized SMEs’ performance and the influences of sustainable procurement, packaging, and distribution:The mediating role of eco-innovation

The current paper is one of the pioneering studies to specifically analyze the role of both inbound and outbound sustainable supply chain practices (SSCP) of servitized SMEs in a relatively high-risk emerging economy context of Pakistan. Building on Porter's Value Chain Model, this study analyzes the influence of sustainable servitization on multiple performance indicators (including environmental, economic, social, and operational) of servitized SMEs. We further investigate the role of eco-innovation as a mediator. The study employs a time-lagged research design, based on primary data collected from 280 managers of servitized SMEs. We found that sustainable practices positively impact servitized SMEs’ performance, except for sustainable procurement's influence on operational performance. Finally, eco-innovation was found to partially mediate the analyzed inter-relationships.</p

Tolerance of faba bean, chickpea and lentil to salinity: accessions' salinity response functions

The productivity of crops irrigated with saline water or grown on salt-affected soils depends on the salt tolerance of the crops, their accessions, and various environmental and cultural conditions such as soil properties, climate and irrigation methods. The level and ability of plants to tolerate salt stress is the most critical information for the successful management of salt-affected agricultural lands and saline irrigation waters. In this paper, responses of three food legume crops (faba bean, chickpea and lentil) to salinity stress were analysed using the threshold-slope linear response function and modified discount function. The response functions are calibrated using the 2009–2010 season data and validated using the 2010–2011 season data from faba bean, chickpea and lentil experiments conducted in Raqqa, Syria. The comparison was also made through SALTMED model predictions. The results of this study show that the salinity response functions and productivity of grain yield are highly variable within the accessions of the same crop. For optimum outcome, practitioners need to consider salinity response functions and also the productivity of different accessions and their response to salinity in relation to the soil and available irrigation water salinity level

Evaluating the productivity potential of chickpea, lentil and faba bean under saline water irrigation systems

The information on salinity threshold levels for food legumes when irrigating with saline water is limited and old. In a multi-year study at two sites in the Euphrates Basin, we aimed at (i) evaluating the potential of saline water irrigation for chickpea, faba bean and lentil production; and (ii) using the SALTMED model to determine threshold crop yields based on irrigation water salinity in equilibrium with ambient soil solution salinity. To evaluate 15 accessions each of lentil and chickpea, and 11 accessions of faba bean, three irrigation treatments were used with salinity levels of 0.87, 2.50 and 3.78 dS m-1 at Hassake and 0.70, 3.0 and 5.0 dS m-1 at Raqqa. Aggregated grain yields showed significant differences (p < 0.05) among crop accessions. Calibration and validation of the SALTMED model revealed a close relationship between actual grain yields from the field sites and those predicted by the model. The 50% yield reduction (π50 value) in chickpea, lentil, and faba bean occurred at salinity levels of 4.2, 4.4 and 5.2 dS m-1, respectively. These results suggest that of the three food legume crops, faba bean can withstand relatively high levels of irrigation water salinity, followed by lentil and chickpea