The study aims to through a qualitative case study describe how six Swedish high-end apparel companies attributed as part of “the Swedish fashion wonder” with online distribution have been affected by six chosen factors. The six factors presented are extracted from previous studies and consist of customer relationships, intermediary relationships, pricing, costs and revenue, competitors and impact on the brand. The results show that customer relationships is an important factor that most companies value and was also the factor they presented as determining when they made the decision to go online. Costs and revenue have an effect on the companies and was something the companies had to consider after going online. Intermediary relationships are important to some extent and demand continual communications, but nothing that worried the companies. Competitors and pricing were not regarded as important, where price setting was primarily seen as a valuable tool to control and maintain intermediary relationships. Impact on the brand was regarded as an important factor when engaging online, and the positive aspects of increased brand knowledge and brand awareness were appreciated.

Microscopic imaging in the biomedical sciences allows for detailed study of the structure and function of normal and abnormal (i.e., diseased) states of cells and tissues. The expression patterns of proteins and/or physiological parameters within these specimens can be related to disease progression and prognosis, and are often heterogeneously spread throughout the entire specimen. With conventional microscopy, a large number of individual image ‘tiles’ must be captured and subsequently combined into a mosaic of the entire specimen. This has the potential to introduce artefacts at the image seams, as well as introducing non-uniform illumination of the entire specimen. A further limitation often encountered in biomedical fluorescence microscopy is the high background due to the autofluorescence (AF) of endogenous compounds within cells and tissues. Often, AF can prevent the detection and/or accurate quantification in fluorescently- labelled tissues and, in general, can reduce the reliability of results obtained from such specimens. AF spectra are relatively broad and so can be present across a large number of image spectral channels. The intensity of AF also increases as the excitation wavelength is decreased, causing increasing amounts of autofluorescence when exciting in the blue and near-UV range of the spectrum (400 - 500 nm). This thesis reports the development of hyperspectral, fluorescence and brightfield imaging of entire, paraffin-embedded, formalin-fixed (PEFF) tissue slides using a prototype confocal scanner with a large field of view (FOV). This technology addresses the challenges of imaging large tissue sections through the use of a telecentric f-theta laser scan lens thus allowing an entire microscope slide (22x70 mm) to be imaged in a single scan at resolution equivalent to a 10x microscope objective. The development and optimization of brightfield and single-channel fluorescence imaging modes are discussed in the first half of this thesis, while the second half and appendices concentrate on the spectral properties of the system and removal of AF from PEFF tissue sections. The hyperspectral imaging mode designed for this system allows the fluorescence emission spectrum of each image pixel to be sampled at 6.7 nm/channel over a spectral range of 500-700 nm. This results in the ability to separate distinct fluorescence signatures from each other, and enables quantification even in situations where the AF completely masks the signal from the applied labels.

Microscopic imaging in the biomedical sciences allows for detailed study of the structure and function of normal and abnormal (i.e., diseased) states of cells and tissues. The expression patterns of proteins and/or physiological parameters within these specimens can be related to disease progression and prognosis, and are often heterogeneously spread throughout the entire specimen. With conventional microscopy, a large number of individual image ‘tiles’ must be captured and subsequently combined into a mosaic of the entire specimen. This has the potential to introduce artefacts at the image seams, as well as introducing non-uniform illumination of the entire specimen. A further limitation often encountered in biomedical fluorescence microscopy is the high background due to the autofluorescence (AF) of endogenous compounds within cells and tissues. Often, AF can prevent the detection and/or accurate quantification in fluorescently- labelled tissues and, in general, can reduce the reliability of results obtained from such specimens. AF spectra are relatively broad and so can be present across a large number of image spectral channels. The intensity of AF also increases as the excitation wavelength is decreased, causing increasing amounts of autofluorescence when exciting in the blue and near-UV range of the spectrum (400 - 500 nm). This thesis reports the development of hyperspectral, fluorescence and brightfield imaging of entire, paraffin-embedded, formalin-fixed (PEFF) tissue slides using a prototype confocal scanner with a large field of view (FOV). This technology addresses the challenges of imaging large tissue sections through the use of a telecentric f-theta laser scan lens thus allowing an entire microscope slide (22x70 mm) to be imaged in a single scan at resolution equivalent to a 10x microscope objective. The development and optimization of brightfield and single-channel fluorescence imaging modes are discussed in the first half of this thesis, while the second half and appendices concentrate on the spectral properties of the system and removal of AF from PEFF tissue sections. The hyperspectral imaging mode designed for this system allows the fluorescence emission spectrum of each image pixel to be sampled at 6.7 nm/channel over a spectral range of 500-700 nm. This results in the ability to separate distinct fluorescence signatures from each other, and enables quantification even in situations where the AF completely masks the signal from the applied labels.

Multi-hop wireless networks based on 802. 11 are being used more widely as an alternative technology for last-mile broadband Internet access. Their benefits include ease of deployment and lower cost. Such networks are not without problems. Current research on such networks aims at a number of challenges, including overcoming capacity limitation and poor fairness. <br /><br /> The focus of our research is for achieving fairness in multi-channel multi-hop wireless networks. First, we review the literature for different methods for representing link-contention areas, and the existing single-channel fairness computational model. Second, we generalize the fairness constraints applied to each link-contention area, defined in the existing single-channel fairness reference model, to multi-channel models. Third, by adopting the concepts of link-usage matrix and medium-usage matrix to represent network topology and flow status, and using Collision Domain theory and Clique Graph theory to represent link-contention area, we develop a computational model to compute optimal MAC-layer bandwidth allocated to each flow in a multi-channel multi-hop WMN. We simulate various network configurations to evaluate the performance of the fairness algorithm based on the above computational model in different scenarios. We have found that in the multi-channel environment, our extension to the Collision Domain model generally provides a more accurate estimation of network capacity. Based on this model, we have extended the source-rate-limiting mechanism, which limits the flow rate to its fair share computed by the computational model. Experimental results that validate these findings are presented in this thesis.

Traditional remote sensing image classification has primarily relied on image spectral information and texture information was ignored or not fully utilized. Existing remote sensing software packages have very limited functionalities with respect to texture information extraction and utilization. This research focuses on the use of multi-scale image texture analysis techniques using Gabor filter banks and Wavelet transformations. Gabor filter banks model texture as irradiance patterns in an image over a limited range of spatial frequencies and orientations. Using Gabor filters, each image texture can be differentiated with respect to its dominant spatial frequency and orientation. Wavelet transformations are useful for decomposition of an image into a set of images based on an orthonormal basis. Dyadic transformations are applied to generate a multi-scale image pyramid which can be used for texture analysis. The analysis of texture is carried out using both artificial textures and remotely sensed image corresponding to natural scenes. This research has shown that texture can be extracted and incorporated in conventional classification algorithms to improve the accuracy of classified results. The applicability of Gabor filter banks and Wavelets is explored for classifying and segmenting remote sensing imagery for geographical applications. A qualitative and quantitative comparison between statistical texture indicators and multi-scale texture indicators has been performed. Multi-scale texture indicators derived from Gabor filter banks have been found to be very effective due to the nature of their configurability to target specific textural frequencies and orientations in an image. Wavelet transformations have been found to be effective tools in image texture analysis as they help identify the ideal scale at which texture indicators need to be measured and reduce the computation time taken to derive statistical texture indicators. A robust set of software tools for texture analysis has been developed using the popular .NET and ArcObjects. ArcObjects has been chosen as the API of choice, as these tools can be seamlessly integrated into ArcGIS. This will aid further exploration of image texture analysis by the remote sensing community.

Transform-domain (TD) sampling is seen as a potential candidate for wideband and ultra-wideband high-performance receivers and is investigated in detail in this research. TD receivers expand the signal over a set of basis functions and operate on the digitized basis coefficients. This parallel digital signal processing relaxes the sampling requirements opening the doors to higher dynamic range and wider bandwidth in receivers. This research is focused on the implementation of a high performance multi-channel wideband receiver that is based on Frequency-domain (FD) sampling, a special case of TD sampling. To achieve high dynamic ranges in these receivers, it is critical that the digital post processing block matches the analog RF front end accurately. This accurate matching has to be ensured across several process variations, mismatches and o�sets that can be present in integrated circuit implementations. A unified model has been defined for the FD multi-channel receiver that contains all these imperfections and a joint synchronization and calibration technique, based on the Least-mean-squared (LMS) algorithm, is presented to track them. A maximum likelihood (ML) algorithm is used to estimate the frequency offset in carriers which is corrected prior to LMS calibration. Simulation results are provided to support these concepts. The sampling circuits in FD receivers are based on charge-sampling and a multi-channel charge-sampling receiver creates an inherent sinc filter-bank that has several advantages compared to the conventional analog filter banks used in other multi-channel receivers. It is shown that the sinc filter banks, besides reduced analog complexity, have very low computational complexity in data estimation which greatly reduces the digital power consumption of these filters. The digital complexity of data estimation in the sinc fiter bank is shown to be less than 1=10th of the complexity in analog filter banks.

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The methods for efficient safety message dissemination in VANETs were proposed. First, the method for using multi-channel was proposed. Using the proposed multi-channel method (divide-and-deliver algorithm), the safety message was delivered to the target device with less delay compared to the traditional single-channel method. This method showed resilient performance even in poor wireless channels compared to the single-channel method. Second, to improve low reliability in low vehicle density situations, the enhanced divide-and-deliver algorithm was proposed. The network coding was a key technique to the enhancement. For the efficient use of network coding, rigorous analysis was conducted and an algorithm was proposed to change the number of network coding packets adaptively by the vehicle densities. Finally, the method for delivering safety messages to multi-direction was proposed. This multi-vehicle selection broadcast (MSB) algorithm avoided the collision between multiple rebroadcasts among vehicles and removed unnecessary packets by using backoff slots. The contributions of this research include reducing delay and increasing reliability for the dissemination of safety messages.

Wireless services have become an indispensable part of our social, economic, and everyday activities. They have facilitated and continue to facilitate rapid access to information and have created a highly-interconnected web of users who are untethered to particular locations. In fact, it is expected that in the very near future, the number of users that access the Internet through their mobile devices will surpass those access the Internet from the fixed infrastructure. Aside from mobile Internet access, wireless technologies enable many critical applications such as emergency response, healthcare and implantable medical devices, industrial automation, tactical communications, transportation networks, smart grids, smart homes, navigation, and weather services. The proliferation and wealth of wireless applications has created a soaring demand for ubiquitous broadband wireless access. This demand is further fueled by the richness of the information accessed by users. Low-bit rate voice communications and text have been replaced with graphics, high-definition video, multi-player gaming, and social networking. Meeting the growing traffic demand poses many challenges due to the spectrum scarcity, the cost of deploying additional infrastructure, and the coexistence of several competing technologies. These challenges can be addressed by developing novel wireless technologies, which can efficiently and securely manage multi-user access to the wireless medium. The multi-user access problem deals with the sharing of the wireless resource among contending users in an efficient, secure, and scalable manner. To alleviate contention and interference among the multiple users, contemporary wireless technologies divide the available spectrum to orthogonal frequency bands (channels). The availability of multiple channels has been demonstrated to substantially improve the performance and reliability of wireless networks by alleviating contention and interference. Multi-channel networks, whether cellular, sensor, mesh, cognitive radio, or heterogeneous ones, can potentially achieve higher throughput and lower delay compared to single-channel networks. However, the gains from the existence of orthogonal channels are contingent upon the efficient and secure coordination of channel access. Typically, this coordination is implemented at the medium access control (MAC) layer using a multi-channel MAC (MMAC) protocol. MMAC protocols are significantly more sophisticated than their single-channel counterparts, due to the additional operations of destination discovery, contention management across channels, and load balancing. A significant body of research has been devoted to designing MMAC protocols. The majority of solutions negotiate channel assignment every few packet transmissions on a default control channel. This design has several critical limitations. First, it incurs significant overhead due to the use of in-band or out-of-band control channels. Second, from a security standpoint, operating over a default control channel constitutes a single point of failure. A DoS attack on the control channel(s) would render all channels inoperable. Moreover, MMAC protocols are vulnerable to misbehavior from malicious users who aim at monopolizing the network resources, or degrading the overall network performance. In this dissertation, we improve the security and spectral efficiency of channel access mechanisms in multi-channel wireless networks. In particular, we are concerned with MAC-layer misbehavior in multi-channel wireless networks. We show that selfish users can manipulate MAC-layer protocol parameters to gain an unfair share of network resources, while remaining undetected. We identify possible misbehavior at the MAC-layer, evaluate their impact on network performance, and develop corresponding detection and mitigation schemes that practically eliminate the misbehavior gains. We extend our misbehavior analysis to MAC protocols specifically designed for opportunistic access in cognitive radio networks. Such protocols implement additional tasks such as cooperative spectrum sensing and spectrum management. We then discuss corresponding countermeasures for detecting and mitigating these misbehavior. We further design a low-overhead multi-channel access protocol that enables the distributed coordination of channel access over orthogonal channels for devices using a single transceiver. Compared with prior art, our protocol eliminates inband and out-of-band control signaling, increases spatial channel reuse, and thus achieves significant higher throughput and lowers delay. Furthermore, we investigate DoS attacks launched against the channel access mechanism. We focus on reactive jamming attacks and show that most MMAC protocols are vulnerable to low-effort jamming due to the utilization of a default control channel. We extend our proposed MMAC protocol to combat jamming by implementing cryptographic interleaving at the PHY-layer, random channel switching, and switching according to cryptographically protected channel priority lists. Our results demonstrate that under high load conditions, the new protocol maintains communications despite the jammer's effort. Extensive simulations and experiments are conducted to evaluate the impact of the considered misbehaviors on network performance, and verify the validity of the proposed mechanisms.