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The purpose of this thesis is to analyse consumer decision-making processes on mobile service channels from both behavioural and perceptive perspectives on time dimension. With mobile channel becoming one of the major service channels, electronic retailers must ensure that their mobile retail application design is able to create usage value to their customers. The investigation of the impacts from the value co-creation on this channel to consumers' actual behaviours is based on the understanding of both cognitive and emotional perspective of consumer decision-making processes. The research aim is to therefore compare the results from survival analysis on behavioural data, and the results from structural equation modelling on questionnaire data, to explore the relationships between the usage of mobile application functions, the time consumption of a decision-making process and the probability of reaching a decision, and to provide insights on designing mobile retail application. This thesis, on one hand, employs Prospect Theory, the Theory of Planned Behaviour and Minkowski Spacetime as its theoretical foundations, and uses customer perceived value as a research lens to develop the research design. On the other hand, it develops survival analysis to investigate the actual practical value of using mobile retail applications in the context of a major health and beauty retailer, Boots' website, and uses structural equation modelling to test a conceptual model representing the prediction of customer perceived value on mobile service channels. The comparison and contrast between the results from these two separate studies offer a better understanding of consumer behaviours in this context. This study is one of the first to apply survival analysis to investigate consumer decision-making process on mobile service channels. It is also one of the first research that analyses consumer behaviours and perceptions from a temporal perspective. This work offers original insights and important findings for both marketing academics and practitioners.

Future wireless network may consist of a cluster of low-complexity battery-powered nodes or mobile stations (MS). Information is propagated from one location in the network to another by cooperation and relaying. Due to the channel fading or node failure, one or more relaying links could become unreliable during multiple-hop relaying. Inspired by conventional multiple-input multiple-output (MIMO) techniques exploiting multiple co-located transmit antennas to introduce temporal and spatial diversity, the error performance and robustness against channel fading of a multiple-hop cooperative network could be significantly improved by creating a virtual antenna array (VAA) with various distributed MIMO techniques. In this thesis, we concentrate on the low-complexity distributed MIMO designed for both coherent and non-coherent diversity signal reception at the destination node. Further improvement on the network throughput as well as spectral efficiency could be achieved by extending the concept of unidirectional relaying to bidirectional cooperative communication. Physical-layer network coding (PLNC) assisted distributed space-time block coding (STBC) scheme as well as non-coherent PLNC aided distributed differential STBC system are proposed. It is confirmed by the theoretical analysis that both approaches have the potential for offering full spatial diversity gain. 　　 Furthermore, differential encoding and non-coherent detection techniques are generally associated with performance degradation due to the doubled noise variance. More importantly, conventional differential schemes suffer from the incapability of recovering the source information in time-varying channels owing to the assumption of static channel model used in the derivation of non-coherent detection algorithm. Several low-complexity solutions are proposed and studied in this thesis, which are able to compensate the performance loss caused by non-coherent detection and guarantee the reliable recovery of information in applications with high mobility. A substantial amount of iteration gain is achieved by combining the differential encoding with error-correction code and sufficient interleaving, which allows iterative possessing at the receiver.

Digital technology has the potential to "democratize information" – making ideas, opinions, and knowledge accessible anywhere, anytime, and to everyone. But is this potential truly realized or will it ever be realized? Do systems enabled by digital technology exhibit or even enhance information bias, skewness, and polarization? How can we overcome them? In this dissertation, I investigate these questions in two major but distinct digital information systems: open collaboration systems (i.e., Wikipedia) and mass media broadcast networks (i.e., broadcast television in the United States). Open collaboration platforms have fundamentally changed the way knowledge is produced, disseminated, and consumed. Wikipedia is arguably one of the most successful examples of such platforms, serving millions of information seekers daily. Despite many benefits provided by the decentralization of knowledge production on Wikipedia, does the open nature and lack of broad oversight and coordination leave the question of information poverty and skewness to the mercy of the system’s natural dynamics? And if so, what can be done to address this? In Chapter 1, I examined this question using both causal inference from a natural experiment and empirically informed diffusion simulations. Another important and pervasive information system is that of televised mass media. Whereas Wikipedia is relatively open and does not have strong information gatekeeping, televised mass media has various forms of information gatekeeping, particularly through media ownership, government regulation and journalistic practice. But how does this gatekeeping affect skewness and polarization in the real-world information that is conveyed to the public? To investigate these questions, I study televised news information systems in the United States with a massive scale unstructured text data and various state-of-the-art text mining techniques in Chapter 2 and Chapter 3 of this dissertation. The text transcripts include the complete televised content from more than 800 television channels across all 210 designated media markets in the United States over a 5-year period between 2013 and 2018. Chapter 2 of this dissertation examines how media ownership impact political slant and information diversity in the news using massive-scale text transcripts. I found that when large owners act coherently, they can skew information to emphasize views, perspectives and framing that they advocate. This is important because previous studies have shown that broadcast media can have a dramatic impact on political and social outcomes and undeniably shapes the national dialogue surrounding important issues. In Chapter 3 of this dissertation, I study the skewed coverage of gun violence incidents in local televised news. I found that some types of gun violence, such as suicide, accidents, domestic violence and sex crimes are systematically covered less relative to other types such as assault weapon incidents, are systematically covered more. Importantly, areas of high vs. low gun ownership received different exposure to different incident types through local news coverage, further dividing an already divided population. I conducted ting a nationally representative survey found that the general public’s view on different type of gun violence is skewed in a manner that is consistent with "the warped mirror" that our media conveys.

There has been a dramatic increase in wireless awareness among the user community in the past few years. As the wireless communication devices require more integration in terms of both hardware and software, the low-power integrated circuit (IC) solution has gained higher dedication and will dominate in the future radio-frequency IC (RFIC) design. Complementary Metal-Oxide Semiconductor (CMOS) process is extremely attractive for such applications because of its low cost and the possibility to integrate baseband and high frequency circuits on the same chip. The transceiver is often the most power-hungry block in a wireless communication system. The frequency divider (prescaler) and the voltage controlled oscillator (VCO) which are essential building blocks of in the frequency synthesizer of the transmitter are among the major sources of power consumption. This work focuses on prescalers. The injection-locked frequency dividers (ILFD) were introduced in the recent past for low-power frequency division. ILFDs can consume an order of magnitude lower power when compared to conventional flip-flop based dividers. However their range of operating frequency, also known as the locking range, is limited. ILFDs can be classified as LC tank, ring or relaxation oscillator based. There have been a lot of published works on the LC tank and ring oscillator based ILFDs. However, the one on relaxation oscillator based ILFD has been rarely reported, especially for RF applications. Besides, it is usually employed to implement a single division ratio such as 2, 3, 4 with an ILFD, while dual- or multi- moduli prescaler is more attractive to an RF synthesizer and are also rarely studied among published ILFDs. The goal of this work is to initially characterize the relaxation ILFD for RF applications. The locking range is optimized by the proposed topology. Besides, mathematical derivation is developed to verify the optimization. ILFD is also designed for different moduli with an easily controlled manner. Finally, the dual-modulus ILFD is also implemented based on the proposed structure. A prototype is fabricated in a 90-nm CMOS process and successfully tested.

Atmospheric nucleation is a process of phase transformation like liquid water transforming into solid or gas phase water, which serves as a significant impact on many atmospheric and technological processes. During the process of the atmospheric nucleation, certain 3D molecular models for atmospheric nucleation will be generated, which are main mixtures of water molecules and hexanol molecules. Analyzing these 3D molecular models can promote the understanding for the nucleation and growth of the particles and phases in a multi-component mixture, as well as for the changes in climate and weather. Therefore, the research for atmospheric nucleation can be transformed into the research for the 3D molecular visualizations and comparisons, which are the similarity calculations. Unfortunately, the research on understanding atmospheric nucleation processes is restricted due to the lack of efficient visual data exploration tools. In this paper, the issue of lacking efficient data visualization tools is tackled by implementing our own application to visualize the atmospheric nucleation. The similarity calculation for these 3D molecules is implemented in order to analyze and compare the atmospheric nucleation processes and molecular models. Admittedly, there are various 3D molecular similarity calculation algorithms, such as clique-detection algorithms and point matching, etc; however, these algorithms are specifically utilized in the fields of protein amino-acids and pharmacophore. Due to the large scale of the atmospheric nucleation data, GPU (Graphical Processing Units) is employed in order to significantly reduce the computation times. This is achieved by utilizing CUDA (Compute Uniform Device Architecture) technology which allows us to execute our algorithm in a parallel method. Furthermore, in this research, the knowledge of hypertree visualization is intended to be utilized to enhance the previously developed web-based visualization and analysis tool that allows remote users to effectively mine the wealth of particle-based nucleation simulation data. The research goal is to speed up knowledge discovery and improve users' productivity through effective data visualization technique and more friendly user interface design. Meanwhile, a feasible parallel computing solution is developed to overcome the slow response due to expensive large data pre-processing. The core research of my thesis is to calculate the similarity between the distinct 3D molecules.

We first present a strategic analysis of end-to-end delay bounds and identify heuristics for scheduler design, then propose three new schedulers that are targeted at statistical delay bounds: Deadline-curve basedEarliest Deadline First (DC-EDF), Adaptive Quasi-Earliest Deadline First (AQE)and General Dynamic Guaranteed Rate Queueing (GDGRQ). Under DC-EDF, local deadlines are assigned as strict time-shifted versions ofsource packet arrival times. This is quite different from the well-known RC-EDF(Rate-controlled EDF), which deploys traffic shaping at each switching node. Weshow that even without traffic shapers, DC-EDF provides not only end-to-enddelay bounds, but also a schedulable region as large as that of RC-EDF. DC-EDFis self-adaptive in local delay bound assignments. This property makes DC-EDFsuitable as the scheduler at intermediate switching nodes along a flow's route. AQE is an enhancement of EDF with intelligence of adaptive scheduling. Under AQEpercentile delay bounds are the delay QoS metric. AQE behaves like EDF whenbandwidth is sufficient. When bandwidth becomes deficient, however, AQE onlyschedules a subset of flows which currently have relatively worse performance;other flows are completely blocked and will be unblocked only when bandwidthbecomes sufficient again. Essentially, AQE enforces shaping on packet delaydistributions. AQE is most suited for scheduling at the last switching nodealong a flow's route. The combination of DC-EDF and AQE provides a good solutiontowards statistical end-to-end delay bounds. GDGQR is designed for networks with fixed packet sizes. It is a subclass of thewell-known Guaranteed Rate (GR) schedulers, thus can guarantee minimum rates toflows. The GR property of GDGRQ is retained through a sophisticated datastructure called cell transmission table. The unique feature of GDGRQ is that itallows controllable adaptive strategy of excess bandwidth distribution, which isrealized by short-term rate adjustment according to queue measurement. GDGRQ isa framework for designing schedulers that can both provide (possibly large)deterministic delay bounds and allow statistical delay bounds.