Statistical analysis and reduction of multiple access interference in MC-CDMA systems

Multicarrier code division multiple access (MC-CDMA) is a very promising candidate for the multiple access scheme in fourth generation wireless communi- cation systems. During asynchronous transmission, multiple access interference (MAI) is a major challenge for MC-CDMA systems and significantly affects their performance. The main objectives of this thesis are to analyze the MAI in asyn- chronous MC-CDMA, and to develop robust techniques to reduce the MAI effect. Focus is first on the statistical analysis of MAI in asynchronous MC-CDMA. A new statistical model of MAI is developed. In the new model, the derivation of MAI can be applied to different distributions of timing offset, and the MAI power is modelled as a Gamma distributed random variable. By applying the new statistical model of MAI, a new computer simulation model is proposed. This model is based on the modelling of a multiuser system as a single user system followed by an additive noise component representing the MAI, which enables the new simulation model to significantly reduce the computation load during computer simulations. MAI reduction using slow frequency hopping (SFH) technique is the topic of the second part of the thesis. Two subsystems are considered. The first sub- system involves subcarrier frequency hopping as a group, which is referred to as GSFH/MC-CDMA. In the second subsystem, the condition of group hopping is dropped, resulting in a more general system, namely individual subcarrier frequency hopping MC-CDMA (ISFH/MC-CDMA). This research found that with the introduction of SFH, both of GSFH/MC-CDMA and ISFH/MC-CDMA sys- tems generate less MAI power than the basic MC-CDMA system during asyn- chronous transmission. Because of this, both SFH systems are shown to outper- form MC-CDMA in terms of BER. This improvement, however, is at the expense of spectral widening. In the third part of this thesis, base station polarization diversity, as another MAI reduction technique, is introduced to asynchronous MC-CDMA. The com- bined system is referred to as Pol/MC-CDMA. In this part a new optimum com- bining technique namely maximal signal-to-MAI ratio combining (MSMAIRC) is proposed to combine the signals in two base station antennas. With the applica- tion of MSMAIRC and in the absents of additive white Gaussian noise (AWGN), the resulting signal-to-MAI ratio (SMAIR) is not only maximized but also in- dependent of cross polarization discrimination (XPD) and antenna angle. In the case when AWGN is present, the performance of MSMAIRC is still affected by the XPD and antenna angle, but to a much lesser degree than the traditional maximal ratio combining (MRC). Furthermore, this research found that the BER performance for Pol/MC-CDMA can be further improved by changing the angle between the two receiving antennas. Hence the optimum antenna angles for both MSMAIRC and MRC are derived and their effects on the BER performance are compared. With the derived optimum antenna angle, the Pol/MC-CDMA system is able to obtain the lowest BER for a given XPD.

Infrastructure Sustainability : Damage Assessment in Multiple-Girder Composite Bridges Using Vibration Characteristics

Assessing the structural health state of urban infrastructure is crucial in terms of infrastructure sustainability. This chapter uses dynamic computer simulation techniques to apply a procedure using vibration-based methods for damage assessment in multiple-girder composite bridges. In addition to changes in natural frequencies, this multi-criteria procedure incorporates two methods, namely, the modal flexibility and the modal strain energy method. Using the numerically simulated modal data obtained through finite element analysis software, algorithms based on modal flexibility and modal strain energy change, before and after damage, are obtained and used as the indices for the assessment of structural health state. The feasibility and capability of the approach is demonstrated through numerical studies of a proposed structure with six damage scenarios. It is concluded that the modal strain energy method is capable of application to multiple-girder composite bridges, as evidenced through the example treated in this chapter.

Multiple human single-stranded DNA binding proteins function in genome maintenance : structural, biochemical and functional analysis

DNA exists predominantly in a duplex form that is preserved via specific base pairing. This base pairing affords a considerable degree of protection against chemical or physical damage and preserves coding potential. However, there are many situations, e.g. during DNA damage and programmed cellular processes such as DNA replication and transcription, in which the DNA duplex is separated into two singlestranded DNA (ssDNA) strands. This ssDNA is vulnerable to attack by nucleases, binding by inappropriate proteins and chemical attack. It is very important to control the generation of ssDNA and protect it when it forms, and for this reason all cellular organisms and many viruses encode a ssDNA binding protein (SSB). All known SSBs use an oligosaccharide/oligonucleotide binding (OB)-fold domain for DNA binding. SSBs have multiple roles in binding and sequestering ssDNA, detecting DNA damage, stimulating strand-exchange proteins and helicases, and mediation of protein–protein interactions. Recently two additional human SSBs have been identified that are more closely related to bacterial and archaeal SSBs. Prior to this it was believed that replication protein A, RPA, was the only human equivalent of bacterial SSB. RPA is thought to be required for most aspects of DNA metabolism including DNA replication, recombination and repair. This review will discuss in further detail the biological pathways in which human SSBs function.

Model and prototype for querying multiple linked scientific datasets

Scientists need to transfer semantically similar queries across multiple heterogeneous linked datasets. These queries may require data from different locations and the results are not simple to combine due to differences between datasets. A query model was developed to make it simple to distribute queries across different datasets using RDF as the result format. The query model, based on the concept of publicly recognised namespaces for parts of each scientific dataset, was implemented with a configuration that includes a large number of current biological and chemical datasets. The configuration is flexible, providing the ability to transparently use both private and public datasets in any query. A prototype implementation of the model was used to resolve queries for the Bio2RDF website, including both Bio2RDF datasets and other datasets that do not follow the Bio2RDF URI conventions.

A cell migration device that maintains a defined surface with no cellular damage during wound edge generation

Studying the rate of cell migration provides insight into fundamental cell biology as well as a tool to assess the functionality of synthetic surfaces and soluble environments used in tissue engineering. The traditional tools used to study cell migration include the fence and wound healing assays. In this paper we describe the development of a microchannel based device for the study of cell migration on defined surfaces. We demonstrate that this device provides a superior tool, relative to the previously mentioned assays, for assessing the propagation rate of cell wave fronts. The significant advantage provided by this technology is the ability to maintain a virgin surface prior to the commencement of the cell migration assay. Here, the device is used to assess rates of mouse fibroblasts (NIH 3T3) and human osteosarcoma (SaOS2) cell migration on surfaces functionalized with various extracellular matrix proteins as a demonstration that confining cell migration within a microchannel produces consistent and robust data. The device design enables rapid and simplistic assessment of multiple repeats on a single chip, where surfaces have not been previously exposed to cells or cellular secretions.

Live my work : rural nurses and their multiple perspectives of self

Aim. This paper is a report of a study to explore rural nurses' experiences of mentoring. Background. Mentoring has recently been proposed by governments, advocates and academics as a solution to the problem for retaining rural nurses in the Australian workforce. Action in the form of mentor development workshops has changed the way that some rural nurses now construct supportive relationships as mentoring. Method. A grounded theory design was used with nine rural nurses. Eleven semi-structured interviews were conducted in various states of Australia during 2004-2005. Situational analysis mapping techniques and frame analysis were used in combination with concurrent data generation and analysis and theoretical sampling. Findings. Experienced rural nurses cultivate novices through supportive mentoring relationships. The impetus for such relationships comes from their own histories of living and working in the same community, and this was termed 'live my work'. Rural nurses use multiple perspectives of self in order to manage their interactions with others in their roles as community members, consumers of healthcare services and nurses. Personal strategies adapted to local context constitute the skills that experienced rural nurses pass-on to neophyte rural nurses through mentoring, while at the same time protecting them through troubleshooting and translating local cultural norms. Conclusion. Living and working in the same community creates a set of complex challenges for novice rural nurses that are better faced with a mentor in place. Thus, mentoring has become an integral part of experienced rural nurses' practice to promote staff retention. © 2007 The Authors.

Service delivery framework : an architectural strategy for next-generation service delivery in business network

The next-generation of service-oriented architecture (SOA) needs to scale for flexible service consumption, beyond organizational and application boundaries, into communities, ecosystems and business networks. In wider and, ultimately, global settings, new capabilities are needed so that business partners can efficiently and reliably enable, adapt and expose services. Those services can then be discovered, ordered, consumed, metered and paid for, through new applications and opportunities, driven by third-parties in the global “village”. This trend is already underway, in different ways, through different early adopter market segments. This paper proposes an architectural strategy for the provisioning and delivery of services in communities, ecosystems and business networks – a Service Delivery Framework (SDF). The SDF is intended to support multiple industries and deployments where a SOA platform is needed for collaborating partners and diverse consumers. Specifically, it is envisaged that the SDF allows providers to publish their services into network directories so that they can be repurposed, traded and consumed, and leveraging network utilities like B2B gateways and cloud hosting. To support these different facets of service delivery, the SDF extends the conventional service provider, service broker and service consumer of the Web Services Architecture to include service gateway, service hoster, service aggregator and service channel maker.

A review of models and model usage scenarios for an airport complex system

Airports represent the epitome of complex systems with multiple stakeholders, multiple jurisdictions and complex interactions between many actors. The large number of existing models that capture different aspects of the airport are a testament to this. However, these existing models do not consider in a systematic sense modelling requirements nor how stakeholders such as airport operators or airlines would make use of these models. This can detrimentally impact on the verification and validation of models and makes the development of extensible and reusable modelling tools difficult. This paper develops from the Concept of Operations (CONOPS) framework a methodology to help structure the review and development of modelling capabilities and usage scenarios. The method is applied to the review of existing airport terminal passenger models. It is found that existing models can be broadly categorised according to four usage scenarios: capacity planning, operational planning and design, security policy and planning, and airport performance review. The models, the performance metrics that they evaluate and their usage scenarios are discussed. It is found that capacity and operational planning models predominantly focus on performance metrics such as waiting time, service time and congestion whereas performance review models attempt to link those to passenger satisfaction outcomes. Security policy models on the other hand focus on probabilistic risk assessment. However, there is an emerging focus on the need to be able to capture trade-offs between multiple criteria such as security and processing time. Based on the CONOPS framework and literature findings, guidance is provided for the development of future airport terminal models.

Multiple distribution static synchronous compensators for distribution feeder voltage support

The potential of multiple distribution static synchronous compensators (DSTATCOMs) to improve the voltage profile of radial distribution networks has been reported in the literature by few authors. However, the operation of multiple DSTATCOMs across a distribution feeder may introduce control interactions and/or voltage instability. This study proposes a control scheme that alleviates interactions among controllers and enhances proper reactive power sharing among DSTATCOMs. A generalised mathematical model is presented to analyse the interactions among any number of DSTATCOMs in the network. The criterion for controller design is developed by conducting eigenvalue analysis on this mathematical model. The proposed control scheme is tested in time domain on a sample radial distribution feeder installed with multiple DSTATCOMs and test results are presented.

Embedding human expert cognition and real-time trajectory planning in autonomous UAS

This thesis presents a new approach to compute and optimize feasible three dimensional (3D) flight trajectories using aspects of Human Decision Making (HDM) strategies, for fixed wing Unmanned Aircraft (UA) operating in low altitude environments in the presence of real time planning deadlines. The underlying trajectory generation strategy involves the application of Manoeuvre Automaton (MA) theory to create sets of candidate flight manoeuvres which implicitly incorporate platform dynamic constraints. Feasible trajectories are formed through the concatenation of predefined flight manoeuvres in an optimized manner. During typical UAS operations, multiple objectives may exist, therefore the use of multi-objective optimization can potentially allow for convergence to a solution which better reflects overall mission requirements and HDM preferences. A GUI interface was developed to allow for knowledge capture from a human expert during simulated mission scenarios. The expert decision data captured is converted into value functions and corresponding criteria weightings using UTilite Additive (UTA) theory. The inclusion of preferences elicited from HDM decision data within an Automated Decision System (ADS) allows for the generation of trajectories which more closely represent the candidate HDM’s decision strategies. A novel Computationally Adaptive Trajectory Decision optimization System (CATDS) has been developed and implemented in simulation to dynamically manage, calculate and schedule system execution parameters to ensure that the trajectory solution search can generate a feasible solution, if one exists, within a given length of time. The inclusion of the CATDS potentially increases overall mission efficiency and may allow for the implementation of the system on different UAS platforms with varying onboard computational capabilities. These approaches have been demonstrated in simulation using a fixed wing UAS operating in low altitude environments with obstacles present.

Next-generation sequencing of cervical DNA detects human papillomavirus types not detected by commercial kits

Background Human papillomavirus (HPV) is the aetiological agent for cervical cancer and genital warts. Concurrent HPV and HIV infection in the South African population is high. HIV positive (+) women are often infected with multiple, rare and undetermined HPV types. Data on HPV incidence and genotype distribution are based on commercial HPV detection kits, but these kits may not detect all HPV types in HIV + women. The objectives of this study were to (i) identify the HPV types not detected by commercial genotyping kits present in a cervical specimen from an HIV positive South African woman using next generation sequencing, and (ii) determine if these types were prevalent in a cohort of HIV-infected South African women. Methods Total DNA was isolated from 109 cervical specimens from South African HIV + women. A specimen within this cohort representing a complex multiple HPV infection, with 12 HPV genotypes detected by the Roche Linear Array HPV genotyping (LA) kit, was selected for next generation sequencing analysis. All HPV types present in this cervical specimen were identified by Illumina sequencing of the extracted DNA following rolling circle amplification. The prevalence of the HPV types identified by sequencing, but not included in the Roche LA, was then determined in the 109 HIV positive South African women by type-specific PCR. Results Illumina sequencing identified a total of 16 HPV genotypes in the selected specimen, with four genotypes (HPV-30, 74, 86 and 90) not included in the commercial kit. The prevalence's of HPV-30, 74, 86 and 90 in 109 HIV positive South African women were found to be 14.6 %, 12.8 %, 4.6 % and 8.3 % respectively. Conclusions Our results indicate that there are HPV types, with substantial prevalence, in HIV positive women not being detected in molecular epidemiology studies using commercial kits. The significance of these types in relation to cervical disease remains to be investigated.

Prenatal Vitamin D deficiency induces an early and more severe experimental autoimmune encephalomyelitis in the second generation

In a previous study, we demonstrated that mouse adult F(1) offspring, exposed to a vitamin d deficiency during pregnancy, developed a less severe and delayed Experimental Autoimmune Encephalomyelitis (EAE), when compared with control offspring. We then wondered whether a similar response was observed in the subsequent generation. To answer this question, we assessed F(2) females whose F(1) parents (males or females) were vitamin d-deprived when developing in the uterus of F(0) females. Unexpectedly, we observed that the vitamin d deficiency affecting the F(0) pregnant mice induced a precocious and more severe EAE in the F(2) generation. This paradoxical finding led us to assess its implications for the epidemiology of Multiple Sclerosis (MS) in humans. Using the REFGENSEP database for MS trios (the patient and his/her parents), we collected the parents' dates of birth and assessed a potential season of birth effect that could potentially be indicative of the vitamin d status of the pregnant grandmothers. A trend for a reduced number of births in the Fall for the parents of MS patients was observed but statistical significance was not reached. Further well powered studies are warranted to validate the latter finding.

Embedding human expert cognition into autonomous UAS trajectory planning

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

Using real-time authentic online learning scenarios to teach criminal intelligence

Criminal intelligence is an area of expertise highly sought-after internationally and within a variety of justice-related professions; however, producing university graduates with the requisite professional knowledge, as well as analytical, organisational and technical skills presents a pedagogical and technical challenge to university educators. The situation becomes even more challenging when students are undertaking their studies by distance education. This best practice session showcases the design of an online undergraduate unit for final year justice students which uses an evolving real-time criminal scenario as the focus of authentic learning activities in order to prepare students for graduate roles within the criminal intelligence and justice professions. Within the unit, students take on the role of criminal intelligence analysts, applying relevant theories, models and strategies to solve a complex but realistic crime and complete briefings and documentation to industry standards as their major summative assessment task. The session will demonstrate how the design of the online unit corresponds to authentic learning principles, and will specifically map the elements of the unit design to Herrington & Oliver’s instructional design framework for authentic learning (2000; Herrington & Herrington 2006). The session will show how a range of technologies was used to create a rich learning experience for students that could be easily maintained over multiple unit iterations without specialist technical support. The session will also discuss the unique pedagogical affordances and challenges implicated in the location of the unit within an online learning environment, and will reflect on some of the lessons learned from the development which may be relevant to other authentic online learning contexts.

Using real-time authentic online learning scenarios to teach criminal intelligence : presentation

Criminal intelligence is an area of expertise highly sought-after internationally and within a variety of justice-related professions; however, producing university graduates with the requisite professional knowledge, as well as analytical, organisational and technical skills presents a pedagogical and technical challenge to university educators. The situation becomes even more challenging when students are undertaking their studies by distance education. This best practice session showcases the design of an online undergraduate unit for final year justice students which uses an evolving real-time criminal scenario as the focus of authentic learning activities in order to prepare students for graduate roles within the criminal intelligence and justice professions. Within the unit, students take on the role of criminal intelligence analysts, applying relevant theories, models and strategies to solve a complex but realistic crime and complete briefings and documentation to industry standards as their major summative assessment task. The session will demonstrate how the design of the online unit corresponds to authentic learning principles, and will specifically map the elements of the unit design to Herrington & Oliver’s instructional design framework for authentic learning (2000; Herrington & Herrington 2006). The session will show how a range of technologies was used to create a rich learning experience for students that could be easily maintained over multiple unit iterations without specialist technical support. The session will also discuss the unique pedagogical affordances and challenges implicated in the location of the unit within an online learning environment, and will reflect on some of the lessons learned from the development which may be relevant to other authentic online learning contexts.