An Investigation into the Implementation of CYP-IAPT Routine Outcome Measures in their First Year of Integration into Child Psychotherapy Practice

This thesis examines the impact on child and adolescent psychotherapists within CAMHS of the introduction of routine outcome measures (ROMs) associated with the Children and Young People’s Improving access to Psychological Therapies programme (CYP-IAPT). All CAMHS therapists working within a particular NHS mental health Trust1 were required to trial CYP-IAPT ROMs as part of their everyday clinical practice from October 2013-September 2014. During this period considerable freedom was allowed as to which of the measures each therapist used and at what frequency. In order to assess the impact of CYP-IAPT ROMs on child psychotherapy, I conducted semi-structured interviews with eight psychotherapists within a particular CAMHS partnership within one NHS Trust. Each statement was coded and grouped according to whether it related to initial (generic) assessment, goal setting / monitoring, monitoring on-going progress, therapeutic alliance, or to issues concerning how data might be used or interpreted by managers and commissioners. Analysis of interviews revealed greatest concern about session-by session ROMs, as these are felt to impact most significantly on psychotherapy; therapists felt that session-by-session ROMs do not take account of negative transference relationships, they are overly repetitive and used to reward / punish the therapist. Measures used at assessment and review were viewed as most compatible with psychotherapy, although often experienced as excessively time consuming. The Goal Based Outcome Measure was generally experienced as compatible with psychotherapy so long as goals are formed collaboratively between therapist and young person. There was considerable anxiety about how data may be (mis)used and (mis)interpreted by managers and commissioners, for example to end treatment prematurely, trigger change of therapist in the face of negative ROMs data, or to damage psychotherapy. Use of ROMs for short term and generic work was experienced as less intrusive and contentious.

Pico Cell Integration to Operator’s Incident Management Process

Mobile network coverage is traditionally provided by outdoor macro base stations, which have a long range and serve several of customers. Due to modern passive houses and tightening construction legislation, mobile network service is deteriorated in many indoor locations. Typically, solutions for indoor coverage problem are expensive and demand actions from the mobile operator. Due to these, superior solutions are constantly researched. The solution presented in this thesis is based on Small Cell technology. Small Cells are low power access nodes designed to provide voice and data services.. This thesis concentrates on a specific Small Cell solution, which is called a Pico Cell. The problem regarding Pico Cells and Small Cells in general is that they are a new technological solution for the mobile operator, and the possible problem sources and incidents are not properly mapped. The purpose of this thesis is to figure out the possible problems in the Pico Cell deployment and how they could be solved within the operator’s incident management process. The research in the thesis is carried out with a literature research and a case study. The possible problems are investigated through lab testing. Pico Cell automated deployment process was tested in the lab environment and its proper functionality is confirmed. The related network elements were also tested and examined, and the emerged problems are resolvable. Operators existing incident management process can be used for Pico Cell troubleshooting with minor updates. Certain pre-requirements have to be met before Pico Cell deployment can be considered. The main contribution of this thesis is the Pico Cell integrated incident management process. The presented solution works in theory and solves the problems found during the lab testing. The limitations in the customer service level were solved by adding the necessary tools and by designing a working question pattern. Process structures for automated network discovery and pico specific radio parameter planning were also added for the mobile network management layer..

Medisuite + Iplate Integration EAFIT & Ilimitada S.A.

Force plate or pressure plate analysis came as an innovative tool to biomechanics and sport medicine -- This allows engineers, scientists and doctors to virtually reconstruct the way a person steps while running or walking using a measuring system and a computer -- With this information they can calculate and analyze a whole set of variables and factors that characterize the step -- Then they are able to make corrections and/or optimizations, designing appropriate shoes and insoles for the patient -- The idea is to study and understand all the hardware and software implications of this process and all the components involved, and then propose an alternative solution -- This solution should have at least similar performance to existing systems -- It should increase the accuracy and/or the sampling frequency to obtain better results -- By the end, there should be a working prototype of a pressure measuring system and a mathematical model to govern it -- The costs of the system have to be lower than most of the systems in the market

An E-government Interoperability Platform Supporting Personal Data Protection Regulations

Public agencies are increasingly required to collaborate with each other in order to provide high-quality e-government services. This collaboration is usually based on the service-oriented approach and supported by interoperability platforms. Such platforms are specialized middleware-based infrastructures enabling the provision, discovery and invocation of interoperable software services. In turn, given that personal data handled by governments are often very sensitive, most governments have developed some sort of legislation focusing on data protection. This paper proposes solutions for monitoring and enforcing data protection laws within an E-government Interoperability Platform. In particular, the proposal addresses requirements posed by the Uruguayan Data Protection Law and the Uruguayan E-government Platform, although it can also be applied in similar scenarios. The solutions are based on well-known integration mechanisms (e.g. Enterprise Service Bus) as well as recognized security standards (e.g. eXtensible Access Control Markup Language) and were completely prototyped leveraging the SwitchYard ESB product.

Reuse and integration of specification logics: the hybridisation perspective

Hybridisation is a systematic process along which the characteristic features of hybrid logic, both at the syntactic and the semantic levels, are developed on top of an arbitrary logic framed as an institution. It also captures the construction of first-order encodings of such hybridised institutions into theories in first-order logic. The method was originally developed to build suitable logics for the specification of reconfigurable software systems on top of whatever logic is used to describe local requirements of each system’s configuration. Hybridisation has, however, a broader scope, providing a fresh example of yet another development in combining and reusing logics driven by a problem from Computer Science. This paper offers an overview of this method, proposes some new extensions, namely the introduction of full quantification leading to the specification of dynamic modalities, and exemplifies its potential through a didactical application. It is discussed how hybridisation can be successfully used in a formal specification course in which students progress from equational to hybrid specifications in a uniform setting, integrating paradigms, combining data and behaviour, and dealing appropriately with systems evolution and reconfiguration.

Identifying health inequalities in individuals with major mental illness (MMI) using routine data

Abstract and Summary of Thesis: Background: Individuals with Major Mental Illness (such as schizophrenia and bipolar disorder) experience increased rates of physical health comorbidity compared to the general population. They also experience inequalities in access to certain aspects of healthcare. This ultimately leads to premature mortality. Studies detailing patterns of physical health comorbidity are limited by their definitions of comorbidity, single disease approach to comorbidity and by the study of heterogeneous groups. To date the investigation of possible sources of healthcare inequalities experienced by individuals with Major Mental Illness (MMI) is relatively limited. Moreover studies detailing the extent of premature mortality experienced by individuals with MMI vary both in terms of the measure of premature mortality reported and age of the cohort investigated, limiting their generalisability to the wider population. Therefore local and national data can be used to describe patterns of physical health comorbidity, investigate possible reasons for health inequalities and describe mortality rates. These findings will extend existing work in this area. Aims and Objectives: To review the relevant literature regarding: patterns of physical health comorbidity, evidence for inequalities in physical healthcare and evidence for premature mortality for individuals with MMI. To examine the rates of physical health comorbidity in a large primary care database and to assess for evidence for inequalities in access to healthcare using both routine primary care prescribing data and incentivised national Quality and Outcome Framework (QOF) data. Finally to examine the rates of premature mortality in a local context with a particular focus on cause of death across the lifespan and effect of International Classification of Disease Version 10 (ICD 10) diagnosis and socioeconomic status on rates and cause of death. Methods: A narrative review of the literature surrounding patterns of physical health comorbidity, the evidence for inequalities in physical healthcare and premature mortality in MMI was undertaken. Rates of physical health comorbidity and multimorbidity in schizophrenia and bipolar disorder were examined using a large primary care dataset (Scottish Programme for Improving Clinical Effectiveness in Primary Care (SPICE)). Possible inequalities in access to healthcare were investigated by comparing patterns of prescribing in individuals with MMI and comorbid physical health conditions with prescribing rates in individuals with physical health conditions without MMI using SPICE data. Potential inequalities in access to health promotion advice (in the form of smoking cessation) and prescribing of Nicotine Replacement Therapy (NRT) were also investigated using SPICE data. Possible inequalities in access to incentivised primary healthcare were investigated using National Quality and Outcome Framework (QOF) data. Finally a pre-existing case register (Glasgow Psychosis Clinical Information System (PsyCIS)) was linked to Scottish Mortality data (available from the Scottish Government Website) to investigate rates and primary cause of death in individuals with MMI. Rate and primary cause of death were compared to the local population and impact of age, socioeconomic status and ICD 10 diagnosis (schizophrenia vs. bipolar disorder) were investigated. Results: Analysis of the SPICE data found that sixteen out of the thirty two common physical comorbidities assessed, occurred significantly more frequently in individuals with schizophrenia. In individuals with bipolar disorder fourteen occurred more frequently. The most prevalent chronic physical health conditions in individuals with schizophrenia and bipolar disorder were: viral hepatitis (Odds Ratios (OR) 3.99 95% Confidence Interval (CI) 2.82-5.64 and OR 5.90 95% CI 3.16-11.03 respectively), constipation (OR 3.24 95% CI 3.01-3.49 and OR 2.84 95% CI 2.47-3.26 respectively) and Parkinson’s disease (OR 3.07 95% CI 2.43-3.89 and OR 2.52 95% CI 1.60-3.97 respectively). Both groups had significantly increased rates of multimorbidity compared to controls: in the schizophrenia group OR for two comorbidities was 1.37 95% CI 1.29-1.45 and in the bipolar disorder group OR was 1.34 95% CI 1.20-1.49. In the studies investigating inequalities in access to healthcare there was evidence of: under-recording of cardiovascular-related conditions for example in individuals with schizophrenia: OR for Atrial Fibrillation (AF) was 0.62 95% CI 0.52 - 0.73, for hypertension 0.71 95% CI 0.67 - 0.76, for Coronary Heart Disease (CHD) 0.76 95% CI 0.69 - 0.83 and for peripheral vascular disease (PVD) 0.83 95% CI 0.72 - 0.97. Similarly in individuals with bipolar disorder OR for AF was 0.56 95% CI 0.41-0.78, for hypertension 0.69 95% CI 0.62 - 0.77 and for CHD 0.77 95% CI 0.66 - 0.91. There was also evidence of less intensive prescribing for individuals with schizophrenia and bipolar disorder who had comorbid hypertension and CHD compared to individuals with hypertension and CHD who did not have schizophrenia or bipolar disorder. Rate of prescribing of statins for individuals with schizophrenia and CHD occurred significantly less frequently than in individuals with CHD without MMI (OR 0.67 95% CI 0.56-0.80). Rates of prescribing of 2 or more anti-hypertensives were lower in individuals with CHD and schizophrenia and CHD and bipolar disorder compared to individuals with CHD without MMI (OR 0.66 95% CI 0.56-0.78 and OR 0.55 95% CI 0.46-0.67, respectively). Smoking was more common in individuals with MMI compared to individuals without MMI (OR 2.53 95% CI 2.44-2.63) and was particularly increased in men (OR 2.83 95% CI 2.68-2.98). Rates of ex-smoking and non-smoking were lower in individuals with MMI (OR 0.79 95% CI 0.75-0.83 and OR 0.50 95% CI 0.48-0.52 respectively). However recorded rates of smoking cessation advice in smokers with MMI were significantly lower than the recorded rates of smoking cessation advice in smokers with diabetes (88.7% vs. 98.0%, p<0.001), smokers with CHD (88.9% vs. 98.7%, p<0.001) and smokers with hypertension (88.3% vs. 98.5%, p<0.001) without MMI. The odds ratio of NRT prescription was also significantly lower in smokers with MMI without diabetes compared to smokers with diabetes without MMI (OR 0.75 95% CI 0.69-0.81). Similar findings were found for smokers with MMI without CHD compared to smokers with CHD without MMI (OR 0.34 95% CI 0.31-0.38) and smokers with MMI without hypertension compared to smokers with hypertension without MMI (OR 0.71 95% CI 0.66-0.76). At a national level, payment and population achievement rates for the recording of body mass index (BMI) in MMI was significantly lower than the payment and population achievement rates for BMI recording in diabetes throughout the whole of the UK combined: payment rate 92.7% (Inter Quartile Range (IQR) 89.3-95.8 vs. 95.5% IQR 93.3-97.2, p<0.001 and population achievement rate 84.0% IQR 76.3-90.0 vs. 92.5% IQR 89.7-94.9, p<0.001 and for each country individually: for example in Scotland payment rate was 94.0% IQR 91.4-97.2 vs. 96.3% IQR 94.3-97.8, p<0.001. Exception rate was significantly higher for the recording of BMI in MMI than the exception rate for BMI recording in diabetes for the UK combined: 7.4% IQR 3.3-15.9 vs. 2.3% IQR 0.9-4.7, p<0.001 and for each country individually. For example in Scotland exception rate in MMI was 11.8% IQR 5.4-19.3 compared to 3.5% IQR 1.9-6.1 in diabetes. Similar findings were found for Blood Pressure (BP) recording: across the whole of the UK payment and population achievement rates for BP recording in MMI were also significantly reduced compared to payment and population achievement rates for the recording of BP in chronic kidney disease (CKD): payment rate: 94.1% IQR 90.9-97.1 vs.97.8% IQR 96.3-98.9 and p<0.001 and population achievement rate 87.0% IQR 81.3-91.7 vs. 97.1% IQR 95.5-98.4, p<0.001. Exception rates again were significantly higher for the recording of BP in MMI compared to CKD (6.4% IQR 3.0-13.1 vs. 0.3% IQR 0.0-1.0, p<0.001). There was also evidence of differences in rates of recording of BMI and BP in MMI across the UK. BMI and BP recording in MMI were significantly lower in Scotland compared to England (BMI:-1.5% 99% CI -2.7 to -0.3%, p<0.001 and BP: -1.8% 99% CI -2.7 to -0.9%, p<0.001). While rates of BMI and BP recording in diabetes and CKD were similar in Scotland compared to England (BMI: -0.5 99% CI -1.0 to 0.05, p=0.004 and BP: 0.02 99% CI -0.2 to 0.3, p=0.797). Data from the PsyCIS cohort showed an increase in Standardised Mortality Ratios (SMR) across the lifespan for individuals with MMI compared to the local Glasgow and wider Scottish populations (Glasgow SMR 1.8 95% CI 1.6-2.0 and Scotland SMR 2.7 95% CI 2.4-3.1). Increasing socioeconomic deprivation was associated with an increased overall rate of death in MMI (350.3 deaths/10,000 population/5 years in the least deprived quintile compared to 794.6 deaths/10,000 population/5 years in the most deprived quintile). No significant difference in rate of death for individuals with schizophrenia compared with bipolar disorder was reported (6.3% vs. 4.9%, p=0.086), but primary cause of death varied: with higher rates of suicide in individuals with bipolar disorder (22.4% vs. 11.7%, p=0.04). Discussion: Local and national datasets can be used for epidemiological study to inform local practice and complement existing national and international studies. While the strengths of this thesis include the large data sets used and therefore their likely representativeness to the wider population, some limitations largely associated with using secondary data sources are acknowledged. While this thesis has confirmed evidence of increased physical health comorbidity and multimorbidity in individuals with MMI, it is likely that these findings represent a significant under reporting and likely under recognition of physical health comorbidity in this population. This is likely due to a combination of patient, health professional and healthcare system factors and requires further investigation. Moreover, evidence of inequality in access to healthcare in terms of: physical health promotion (namely smoking cessation advice), recording of physical health indices (BMI and BP), prescribing of medications for the treatment of physical illness and prescribing of NRT has been found at a national level. While significant premature mortality in individuals with MMI within a Scottish setting has been confirmed, more work is required to further detail and investigate the impact of socioeconomic deprivation on cause and rate of death in this population. It is clear that further education and training is required for all healthcare staff to improve the recognition, diagnosis and treatment of physical health problems in this population with the aim of addressing the significant premature mortality that is seen. Conclusions: Future work lies in the challenge of designing strategies to reduce health inequalities and narrow the gap in premature mortality reported in individuals with MMI. Models of care that allow a much more integrated approach to diagnosing, monitoring and treating both the physical and mental health of individuals with MMI, particularly in areas of social and economic deprivation may be helpful. Strategies to engage this “hard to reach” population also need to be developed. While greater integration of psychiatric services with primary care and with specialist medical services is clearly vital the evidence on how best to achieve this is limited. While the National Health Service (NHS) is currently undergoing major reform, attention needs to be paid to designing better ways to improve the current disconnect between primary and secondary care. This should then help to improve physical, psychological and social outcomes for individuals with MMI.

Dynamically managing sensed context data

This thesis reports on an investigation of the feasibility and usefulness of incorporating dynamic management facilities for managing sensed context data in a distributed contextaware mobile application. The investigation focuses on reducing the work required to integrate new sensed context streams in an existing context aware architecture. Current architectures require integration work for new streams and new contexts that are encountered. This means of operation is acceptable for current fixed architectures. However, as systems become more mobile the number of discoverable streams increases. Without the ability to discover and use these new streams the functionality of any given device will be limited to the streams that it knows how to decode. The integration of new streams requires that the sensed context data be understood by the current application. If the new source provides data of a type that an application currently requires then the new source should be connected to the application without any prior knowledge of the new source. If the type is similar and can be converted then this stream too should be appropriated by the application. Such applications are based on portable devices (phones, PDAs) for semi-autonomous services that use data from sensors connected to the devices, plus data exchanged with other such devices and remote servers. Such applications must handle input from a variety of sensors, refining the data locally and managing its communication from the device in volatile and unpredictable network conditions. The choice to focus on locally connected sensory input allows for the introduction of privacy and access controls. This local control can determine how the information is communicated to others. This investigation focuses on the evaluation of three approaches to sensor data management. The first system is characterised by its static management based on the pre-pended metadata. This was the reference system. Developed for a mobile system, the data was processed based on the attached metadata. The code that performed the processing was static. The second system was developed to move away from the static processing and introduce a greater freedom of handling for the data stream, this resulted in a heavy weight approach. The approach focused on pushing the processing of the data into a number of networked nodes rather than the monolithic design of the previous system. By creating a separate communication channel for the metadata it is possible to be more flexible with the amount and type of data transmitted. The final system pulled the benefits of the other systems together. By providing a small management class that would load a separate handler based on the incoming data, Dynamism was maximised whilst maintaining ease of code understanding. The three systems were then compared to highlight their ability to dynamically manage new sensed context. The evaluation took two approaches, the first is a quantitative analysis of the code to understand the complexity of the relative three systems. This was done by evaluating what changes to the system were involved for the new context. The second approach takes a qualitative view of the work required by the software engineer to reconfigure the systems to provide support for a new data stream. The evaluation highlights the various scenarios in which the three systems are most suited. There is always a trade-o↵ in the development of a system. The three approaches highlight this fact. The creation of a statically bound system can be quick to develop but may need to be completely re-written if the requirements move too far. Alternatively a highly dynamic system may be able to cope with new requirements but the developer time to create such a system may be greater than the creation of several simpler systems.

REFUGEES AND RESETTLEMENT: A QUALITATIVE ANALYSIS OF REFUGEE INTEGRATION THROUGH SOCIAL & SUPPORT SERVICES

This dissertation studies refugee resettlement in the United States utilizing the Integration Indicator’s framework developed by Ager and Strang for the U.S. context. The study highlights the U.S. refugee admissions program and the policies in the states of Maryland and Massachusetts while analyzing the service delivery models and its effects on refugee integration in these locations. Though immigration policy and funding for refugee services are primarily the domain of the federal government, funds are allocated through and services are delivered at the state level. The Office of Refugee Resettlement (ORR), which operates under the Department of Health and Human Services, was established after the Refugee Act of 1980 to deliver assistance to displaced persons. The ORR provides funds to individual states primarily through The Refugee Social Service and Targeted Assistance Formula Grant programs. Since the inauguration of the ORR three primary models of refugee integration through service delivery have emerged. Two of the models include the publicly/privately administered programs, where resources are allocated to the state in conjunction with private voluntary agencies; and the Wilson/Fish Alternative programs, where states sub-contract all elements of the resettlement program to voluntary agencies and private organizations —in which they can cease all state level participation and voluntary agencies or private organizations contract directly from the ORR in order for all states to deliver refugee services where the live. The specific goals of this program are early employment and economic self-sufficiency. This project utilizes US Census, state, and ORR data in conjunction with interviews of refugee resettlement practitioners involved in the service delivery and refugees. The findings show that delivery models emphasizing job training, English instruction courses, institutional collaboration, and monetary assistance, increases refugee acclimation and adaptation, providing insight into their potential for integration into the United States.

Data-Driven Wildfire Propagation Modeling with FARSITE-EnKF

The goal of this study is to provide a framework for future researchers to understand and use the FARSITE wildfire-forecasting model with data assimilation. Current wildfire models lack the ability to provide accurate prediction of fire front position faster than real-time. When FARSITE is coupled with a recursive ensemble filter, the data assimilation forecast method improves. The scope includes an explanation of the standalone FARSITE application, technical details on FARSITE integration with a parallel program coupler called OpenPALM, and a model demonstration of the FARSITE-Ensemble Kalman Filter software using the FireFlux I experiment by Craig Clements. The results show that the fire front forecast is improved with the proposed data-driven methodology than with the standalone FARSITE model.

Using text-mining-assisted analysis to examine the applicability of unstructured data in the context of customer complaint management

Double Degree

Shaping the Dicot Fruit: Molecular and Genomic Approaches to Fruit Development

The fruit is one of the most complex and important structures produced by flowering plants, and understanding the development and maturation process of fruits in different angiosperm species with diverse fruit structures is of immense interest. In the work presented here, molecular genetics and genomic analysis are used to explore the processes that form the fruit in two species: The model organism Arabidopsis and the diploid strawberry Fragaria vesca. One important basic question concerns the molecular genetic basis of fruit patterning. A long-standing model of Arabidopsis fruit (the gynoecium) patterning holds that auxin produced at the apex diffuses downward, forming a gradient that provides apical-basal positional information to specify different tissue types along the gynoecium’s length. The proposed gradient, however, has never been observed and the model appears inconsistent with a number of observations. I present a new, alternative model, wherein auxin acts to establish the adaxial-abaxial domains of the carpel primordia, which then ensures proper development of the final gynoecium. A second project utilizes genomics to identify genes that regulate fruit color by analyzing the genome sequences of Fragaria vesca, a species of wild strawberry. Shared and distinct SNPs among three F. vesca accessions were identified, providing a foundation for locating candidate mutations underlying phenotypic variations among different F. vesca accessions. Through systematic analysis of relevant SNP variants, a candidate SNP in FveMYB10 was identified that may underlie the fruit color in the yellow-fruited accessions, which was subsequently confirmed by functional assays. Our lab has previously generated extensive RNA-sequencing data that depict genome-scale gene expression profiles in F. vesca fruit and flower tissues at different developmental stages. To enhance the accessibility of this dataset, the web-based eFP software was adapted for this dataset, allowing visualization of gene expression in any tissues by user-initiated queries. Together, this thesis work proposes a well-supported new model of fruit patterning in Arabidopsis and provides further resources for F. vesca, including genome-wide variant lists and the ability to visualize gene expression. This work will facilitate future work linking traits of economic importance to specific genes and gaining novel insights into fruit patterning and development.

Capability Matrix for Open Data

Part 14: Interoperability and Integration

Identifying wind power ramp causes from multivariate datasets: a methodological proposal and its application to reanalysis data.

Forecasting abrupt variations in wind power generation (the so-called ramps) helps achieve large scale wind power integration. One of the main issues to be confronted when addressing wind power ramp forecasting is the way in which relevant information is identified from large datasets to optimally feed forecasting models. To this end, an innovative methodology oriented to systematically relate multivariate datasets to ramp events is presented. The methodology comprises two stages: the identification of relevant features in the data and the assessment of the dependence between these features and ramp occurrence. As a test case, the proposed methodology was employed to explore the relationships between atmospheric dynamics at the global/synoptic scales and ramp events experienced in two wind farms located in Spain. The achieved results suggested different connection degrees between these atmospheric scales and ramp occurrence. For one of the wind farms, it was found that ramp events could be partly explained from regional circulations and zonal pressure gradients. To perform a comprehensive analysis of ramp underlying causes, the proposed methodology could be applied to datasets related to other stages of the wind-topower conversion chain.

Predictive ability of Genomic Estimated Family Values (GEFV).

Genomic selection (GS) has been used to compute genomic estimated breeding values (GEBV) of individuals; however, it has only been applied to animal and major plant crops due to high costs. Besides, breeding and selection is performed at the family level in some crops. We aimed to study the implementation of genome-wide family selection (GWFS) in two loblolly pine (Pinus taeda L.) populations: i) the breeding population CCLONES composed of 63 families (5-20 individuals per family), phenotyped for four traits (stem diameter, stem rust susceptibility, tree stiffness and lignin content) and genotyped using an Illumina Infinium assay with 4740 polymorphic SNPs, and ii) a simulated population that reproduced the same pedigree as CCLONES, 5000 polymorphic loci and two traits (oligogenic and polygenic). In both populations, phenotypic and genotypic data was pooled at the family level in silico. Phenotypes were averaged across replicates for all the individuals and allele frequency was computed for each SNP. Marker effects were estimated at the individual (GEBV) and family (GEFV) levels with Bayes-B using the package BGLR in R and models were validated using 10-fold cross validations. Predicted ability, computed by correlating phenotypes with GEBV and GEFV, was always higher for GEFV in both populations, even after standardizing GEFV predictions to be comparable to GEBV. Results revealed great potential for using GWFS in breeding programs that select families, such as most outbreeding forage species. A significant drop in genotyping costs as one sample per family is needed would allow the application of GWFS in minor crops.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.