Novel particle swarm optimization algorithms with applications to healthcare data analysis

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.Optimization problem is a fundamental research topic which has been receiving increasing interest according to its application potential in almost all real-world systems including engineering systems, large-scaled complex networks, healthcare management systems and so on. A large number of heuristic algorithms have been developed with the purpose of effectively solving the optimization problems during the past few decades. Served as a powerful family of heuristic algorithms, the particle swarm optimization (PSO) algorithm has been successfully employed in a variety of practical applications in dealing with optimization problems. The PSO algorithm has exhibited more competitive performance than many popular evolutionary computation approaches because of its easy implementation, fast convergence and comprehensive ability of converging to a satisfactory solution. Nevertheless, there is still much room to improve the PSO algorithm in terms of both the convergence rate and the population diversity. To summarize, there are three challenging problems in developing new variant PSO algorithms with hope to further improve the convergence rate of the PSO algorithm and maintain the population diversity: 1) how to adjust the control parameters of the PSO algorithm; 2) how to achieve the balance between the local search and the global search during the evolution process; and 3) how to guarantee the search ability of the particles and avoid premature convergence. In this thesis, we address the above mentioned challenging problems and aim to design effective variant PSO algorithms with applications in intelligent data analysis. It should be pointed out that all the developed PSO algorithms in this thesis have been evaluated by comparing with some currently popular variant PSO algorithms. • With the aim to improve the convergence rate of the optimizer, an adaptive weighting PSO algorithm is put forward where a sigmoid-function-based weighting strategy is introduced to adjust the acceleration coefficients. With this weighting strategy, the distances from the particle to the global best position and from the particle to its personal best position are both taken into consideration, thereby having the distinguishing feature of enhancing the convergence rate. • As with other evolutionary computation approaches, the modification of parameters is an efficient method for improving the search ability of the algorithm. We present a randomised PSO algorithm where Gaussian white noise with adjustable intensity is utilized to randomly perturb the acceleration coefficients in order to explore and exploit the problem space thoroughly. • To further develop a novel PSO algorithm with promising search ability, we propose a randomly occurring distributedly delayed particle swarm optimization (RODDPSO) algorithm which demonstrates competitive performance in seeking the optimal solution. The randomly occurring distributed time delays not only contribute to a thorough exploration of the search space but also achieve a proper balance between the local exploitation and the global exploration. • To fully investigate the application potential of the developed PSO algorithms, we apply the RODDPSO algorithm to intelligent data analysis (including data clustering and classification problems). We optimize the initial cluster centroids of the K-means clustering algorithm and the hyperparameters of the deep neural network by using the RODDPSO algorithm. The developed PRODDPSO-based algorithms are successfully employed in patients’ triage categorization and patient attendance disposal problems with satisfactory performanc

A Climate Change Vulnerability Assessment among Small Farmers: A Case Study in Western Honduras

Climate change is now affecting every known society. Small farmers in Low Income Countries (LICs) are especially vulnerable to climate change patterns because they depend heavily on rain, seasonality patterns, and known temperature ranges. To help build climate change resilient communities among rural farmers, the first step is to understand the impact of climate change on the population. This dissertation aims to use information and communication technology (ICT) to assess climate change vulnerabilities among rural farmers. To achieve this overall goal, this dissertation first proposes a comprehensive Climate Change Vulnerability Assessment Framework (CCVAF) that integrates both community level and individual household level indicators. The CCVAF was instantiated into a GIS-based web application named THRIVE for different decision makers to better assess how climate change is affecting rural farmers in Western Honduras. Qualitative evaluation of the THRIVE showed that it is an innovative and useful tool. The CCVAF and its instantiation provides an important initial step towards building climate change resilience among rural farmers. It is the first attempt to provide a comprehensive set of the indicators with related measurements and data sources for climate change vulnerability assessment. The framework thus contributes to the knowledge base of the climate change vulnerability assessment. It also contributes to the design science literature by providing guidelines to design a class of climate change vulnerability assessment solutions. To the best of our knowledge, the CCVAF is the first generalizable artifact that can be used to build a group of ICT-based climate change vulnerability assessment solutions. Another knowledge contribution of this dissertation is its reproducibility by making the input and output data available to the research and practitioner community through a GeoHub. For practical contributions, the framework can be easily used by researchers and practitioners to consistently design a vulnerability assessment tool, starting with the set of indicators organized by the three-level determinants, and following specific spatial data analysis and models. Such an ICT-based tool adds practical values to tackle climate change challenges

A Hybrid Modelling Framework for Real-time Decision-support for Urgent and Emergency Healthcare

In healthcare, opportunities to use real-time data to support quick and effective decision-making are expanding rapidly, as data increases in volume, velocity and variety. In parallel, the need for short-term decision-support to improve system resilience is increasingly relevant, with the recent COVID-19 crisis underlining the pressure that our healthcare services are under to deliver safe, effective, quality care in the face of rapidly-shifting parameters. A real-time hybrid model (HM) which combines real-time data, predictions, and simulation, has the potential to support short-term decision-making in healthcare. Considering decision-making as a consequence of situation awareness focuses the HM on what information is needed where, when, how, and by whom with a view toward sustained implementation. However the articulation between real-time decision-support tools and a sociotechnical approach to their development and implementation is currently lacking in the literature. Having identified the need for a conceptual framework to support the development of real-time HMs for short-term decision-support, this research proposed and tested the Integrated Hybrid Analytics Framework (IHAF) through an examination of the stages of a Design Science methodology and insights from the literature examining decision-making in dynamic, sociotechnical systems, data analytics, and simulation. Informed by IHAF, a HM was developed using real-time Emergency Department data, time-series forecasting, and discrete-event simulation. The application started with patient questionnaires to support problem definition and to act as a formative evaluation, and was subsequently evaluated using staff interviews. Evaluation of the application found multiple examples where the objectives of people or sub-systems are not aligned, resulting in inefficiencies and other quality problems, which are characteristic of complex adaptive sociotechnical systems. Synthesis of the literature, the formative evaluation, and the final evaluation found significant themes which can act as antecedents or evaluation criteria for future real-time HM studies in sociotechnical systems, in particular in healthcare. The generic utility of IHAF is emphasised for supporting future applications in similar domains

Chaotic Lives: A Profile of Women in the Criminal Justice System in Lothian and Borders

This research, conducted on behalf of Lothian and Borders Community Justice Authority, aimed to profile the characteristics and needs of women offenders in the Lothian and Borders CJA through quantitative and qualitative data collection. The research made 20 recommendations, the key recommendations are outlined below: There is a need for more gender-specific interventions for women offenders within both the statutory and voluntary sector, including groupwork programmes, education and employment opportunities, health and counselling services and throughcare/aftercare provision. A one-stop shop approach should be investigated based on good practice in other areas of the UK. The development of legislation and funding would allow a greater use of structured deferred sentences and diversion schemes, possibly both of which could be available at the pre-sentence stage, with earlier social work assessment of risks and needs being provided to procurators fiscal to supplement their marking decisions. Greater consistency and coordination is required to ensure that all relevant agencies receive the necessary information at the referral stage, including the offence type and circumstances, in order to inform their assessment and subsequent intervention; There needs to be a greater focus on care/welfare rather than on control/surveillance and should be reflected in policy guidelines, additional practitioner training, and more flexible breach procedures

An Optimisation-based Framework for Complex Business Process: Healthcare Application

The Irish healthcare system is currently facing major pressures due to rising demand, caused by population growth, ageing and high expectations of service quality. This pressure on the Irish healthcare system creates a need for support from research institutions in dealing with decision areas such as resource allocation and performance measurement. While approaches such as modelling, simulation, multi-criteria decision analysis, performance management, and optimisation can – when applied skilfully – improve healthcare performance, they represent just one part of the solution. Accordingly, to achieve significant and sustainable performance, this research aims to develop a practical, yet effective, optimisation-based framework for managing complex processes in the healthcare domain. Through an extensive review of the literature on the aforementioned solution techniques, limitations of using each technique on its own are identified in order to define a practical integrated approach toward developing the proposed framework. During the framework validation phase, real-time strategies have to be optimised to solve Emergency Department performance issues in a major hospital. Results show a potential of significant reduction in patients average length of stay (i.e. 48% of average patient throughput time) whilst reducing the over-reliance on overstretched nursing resources, that resulted in an increase of staff utilisation between 7% and 10%. Given the high uncertainty in healthcare service demand, using the integrated framework allows decision makers to find optimal staff schedules that improve emergency department performance. The proposed optimum staff schedule reduces the average waiting time of patients by 57% and also contributes to reduce number of patients left without treatment to 8% instead of 17%. The developed framework has been implemented by the hospital partner with a high level of success

From medical relief to community health care: a case study of a non-governmental organisation (Frontier Primary Health Care) in North West Frontier Province, Pakistan

This case study is designed to answer the question whether refugees can make a positive contribution to host countries, not simply as individual participants in economic activity, but by contributing to welfare. The thesis provides a detailed study of an NGO originally established to provide medical relief for refugees but which now provides basic health care for local people. Since 1995 this NGO has adopted a policy of providing the same basic care to refugees and to people in local Pakistani villages, thus making no distinction between refugees and the residents of a specific geographical area. The case study also shows that an NGO can be an appropriate and effective provider of primary health care (PHC) as promoted by the 1978 Declaration of Alma Ata. The thesis uses several approaches to demonstrate why this happened and how it was achieved. Firstly, it narrates the history over the twenty-year period 1980-2000 of an international health project originally started for a group of Afghan refugees, and its transformation in 1995 into an indigenous Pakistani NGO called “Frontier Primary Health Care (FPHC)”. Secondly, the study explores the theoretical utility and limitations of the PHC strategy generally. Thirdly, the thesis provides an analysis of the extent to which the underlying principles or “pillars” of PHC, that is, participation, inter-sectoral collaboration and equity have affected the process and outcomes of the project. Locating the case study in the Pakistani context provides evidence of the persistent difficulties and shortcomings of official government basic health care in Pakistan, particularly for rural poor people, showing that the field is open for other providers of health care, such as NGOs. The thesis goes on to discuss strengths and weaknesses of NGOs in general, and particularly as health care providers. In investigating characteristics of the NGO sector in Pakistan, the study pays special attention to the discrete health care system for Afghan refugees created in the early 1980s, including its introduction of Community Health Workers. In order to assess the impact of the NGO on people’s health, the study uses data from mother/child health and family planning programmes (as far as available) demonstrating that this NGO is a more effective provider than the other two agencies i.e. the Government of Pakistan and the Afghan Refugee Health Programme. Placing the NGO in this context also shows that it has a better understanding of the underlying “pillars” and has made more determined and effective efforts to implement them, especially in regard to community involvement. It is unusual for a project initially refugee-oriented to have matured sufficiently to be making a contribution, as a matter of formal policy, to basic welfare in the host country, itself a developing country. The study concludes that the significant factors in its success are continuity of leadership; boundaries of population, geography and administration; dependable income and material resources; rigorous supervision; support, but not takeover, by experienced consultants; capacity to use learning to adapt and move on; and sensitivity to local cultural norms. All these have enabled the project to survive and develop as an indigenous autonomous organisation beyond the twenty years covered by the case study. FPHC is still operational in 2004

Senate journal, 20 April 2006.

Titles and imprints vary; Some volumes include miscellaneous state documents and reports; Rules of the Senat

Annual reports of the selectmen and other offices of the town of Bradford, New Hampshire for the year ending December 31, 2018 and vital statistics for the year ending December 31, 2018.

This is an annual report containing vital statistics for a town/city in the state of New Hampshire