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Quantum measurement and feedback control of nano-mechanical systems and atomic spin-ensembles
Get PDFIn recent years, considerable developments have been made in controlling quantum systems through a combination of measurement and feedback. All measurements naturallydisturb the system in question, as they necessitate some level of interaction in order to extract information. However, if we can characterise the resulting disturbance and correctly interpret the information - especially in the case of weak measurements - then we can determine how to feed back the measurement in such a way as to drive desired evolution, preparing potentially highly non-classical states. In this thesis, we investigate using feedback to prepare and manipulate quantum states of motion of levitated nano-particles, as well as for the preparation of many-body squeezed states in atomic ensembles. We first consider a possible route to ground state cooling with a levitated nanoparticle, magnetically trapped by a strong permanent magnet. Thetrap frequency of this system is much lower than those involving trapped ions or in many other nano-mechanical resonators. Minimisation of environmental heating is therefore challenging as it requires control of the system on a timescale comparable to the inverse of the trap frequency. We show that these traps are an excellent platform for performing optimal feedback control via real-time state estimation, and that they may also be an ideal testing ground for quantum collapse models when operating in the free particle limit. We go on to explore a separate system, considering applications of feedback for preparing collective pseudo-spin states in a dilute cloud of atoms. We model how information in typically discarded measurement channels can be used to stabilise noise in order to produce enhanced levels of spin squeezing.In these projects we make use of quantum trajectory techniques alongside analytical models, to explore and simulate realistic parameter regimes for current or near-future experiments.Throughout, we develop ideas for creating non-classical states in a new generation of quantum technologies.In recent years, considerable developments have been made in controlling quantum systems through a combination of measurement and feedback. All measurements naturallydisturb the system in question, as they necessitate some level of interaction in order to extract information. However, if we can characterise the resulting disturbance and correctly interpret the information - especially in the case of weak measurements - then we can determine how to feed back the measurement in such a way as to drive desired evolution, preparing potentially highly non-classical states. In this thesis, we investigate using feedback to prepare and manipulate quantum states of motion of levitated nano-particles, as well as for the preparation of many-body squeezed states in atomic ensembles. We first consider a possible route to ground state cooling with a levitated nanoparticle, magnetically trapped by a strong permanent magnet. Thetrap frequency of this system is much lower than those involving trapped ions or in many other nano-mechanical resonators. Minimisation of environmental heating is therefore challenging as it requires control of the system on a timescale comparable to the inverse of the trap frequency. We show that these traps are an excellent platform for performing optimal feedback control via real-time state estimation, and that they may also be an ideal testing ground for quantum collapse models when operating in the free particle limit. We go on to explore a separate system, considering applications of feedback for preparing collective pseudo-spin states in a dilute cloud of atoms. We model how information in typically discarded measurement channels can be used to stabilise noise in order to produce enhanced levels of spin squeezing.In these projects we make use of quantum trajectory techniques alongside analytical models, to explore and simulate realistic parameter regimes for current or near-future experiments.Throughout, we develop ideas for creating non-classical states in a new generation of quantum technologies
Applications of multivariate statistics in honey bee research, analysis of metabolomics data from samples of honey bee propolis
Get PDFThis thesis was previously held under moratorium from 20/04/2020 to 20/04/2022Honey bees play a significant role both ecologically and economically, through the pollination of flowering plants and crops. Additionally, honey is an ancient food source that is highly valued by different religions and cultures and has been shown to possess a wide range of beneficial uses, including cosmetic treatment, eye disease, bronchial asthma and hiccups. In addition to honey, honey bees also produce beeswax, pollen, royal jelly and propolis. In this thesis, data is studied which comes from samples of propolis from various geographical locations.Propolis is a resinous product, which consists of a combination of beeswax, saliva and resins that have been gathered by honey bees from the exudates of various surrounding plants. It is used by the bees to seal small gaps and maintain the hives, but is also an anti-microbial substance that may protect them against disease. The appearance and consistency of propolis changes depending on the temperature; it becomes elastic and sticky when warm, but hard and brittle when cold. Furthermore, its composition and colour varies from yellowish-green to dark brown, depending on its age and the sources of resin from the environment. Propolis is a highly biochemically active substance with many potential benefits in health care, which have attracted much attention.Biochemical analysis of propolis leads to highly multivariate metabolomics data. The main benefit of metabolomics is to generate a spectrum, in which peaks correspond to different chemical components, making possible the detection of multiple substances simultaneously. Relevant spectral features may be used for pattern recognition. The purpose of this research is to study methods used for statistical analysis of biochemical data arising from propolis samples.We investigate the use of different statistical methods for metabolomics data from chemical analysis of propolis samples using Mass Spectrometry (MS). Methods studied will include pre-treatment methods and multivariate analysis techniques including principal component analysis (PCA), multidimensional scaling (MDS), and clustering methods including hierarchical cluster analysis (HCA), k-means clustering and self organising maps (SOMs). Background material and results of data analysis will be presented from samples of propolis from beehives in Scotland, Libya and Europe. Conclusions are drawn in terms of the data sets themselves as well as the properties of the different methods studied for analysing such metabolomics data.Honey bees play a significant role both ecologically and economically, through the pollination of flowering plants and crops. Additionally, honey is an ancient food source that is highly valued by different religions and cultures and has been shown to possess a wide range of beneficial uses, including cosmetic treatment, eye disease, bronchial asthma and hiccups. In addition to honey, honey bees also produce beeswax, pollen, royal jelly and propolis. In this thesis, data is studied which comes from samples of propolis from various geographical locations.Propolis is a resinous product, which consists of a combination of beeswax, saliva and resins that have been gathered by honey bees from the exudates of various surrounding plants. It is used by the bees to seal small gaps and maintain the hives, but is also an anti-microbial substance that may protect them against disease. The appearance and consistency of propolis changes depending on the temperature; it becomes elastic and sticky when warm, but hard and brittle when cold. Furthermore, its composition and colour varies from yellowish-green to dark brown, depending on its age and the sources of resin from the environment. Propolis is a highly biochemically active substance with many potential benefits in health care, which have attracted much attention.Biochemical analysis of propolis leads to highly multivariate metabolomics data. The main benefit of metabolomics is to generate a spectrum, in which peaks correspond to different chemical components, making possible the detection of multiple substances simultaneously. Relevant spectral features may be used for pattern recognition. The purpose of this research is to study methods used for statistical analysis of biochemical data arising from propolis samples.We investigate the use of different statistical methods for metabolomics data from chemical analysis of propolis samples using Mass Spectrometry (MS). Methods studied will include pre-treatment methods and multivariate analysis techniques including principal component analysis (PCA), multidimensional scaling (MDS), and clustering methods including hierarchical cluster analysis (HCA), k-means clustering and self organising maps (SOMs). Background material and results of data analysis will be presented from samples of propolis from beehives in Scotland, Libya and Europe. Conclusions are drawn in terms of the data sets themselves as well as the properties of the different methods studied for analysing such metabolomics data
The effect of sterol and surfactant substitution on the ability of non-ionic surfactant vesicles to reduce IL-6 production by murine macrophages stimulated with LPS
No full textIntro: Non-ionic surfactant vesicles (NISV) have previously been used widely in drug delivery and vaccines, with NISV containing mono palmitoyl glycerol (MPG) and cholesterol conferring an anti-inflammatory effect when delivered without a payload in vivo. This formulation was able to reduce production of pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumour necrosis factor α (TNFα), which are commonly involved in pathology of sepsis and toxoplasma gondii infection. Methods: new NISV formulations based on those containing MPG and cholesterol were produced with the surfactant component replaced (hexadecanoylglyceroyl (HG) instead of MPG), or the sterol component replaced (ergosterol or stigmasterol instead of cholesterol) at the same molar ratio as previous NISV. Macrophages were stimulated with NISV formulations alone or with NISV and LPS for 24hrs and cellular viability assessed with alamarblue assay. ELISA for IL-6 was performed on supernatants from these cells to determine degree of anti-inflammatory effect after 24hr stimulation. RESULTS: Individual components contributed to cellular toxicity but had no anti-inflammatory effect when not formulated into vesicles. A reduction in IL-6 was found in NISV irrespective of whether the sterol was cholesterol or ergosterol. NISV containing HG instead of MPG retained the anti-inflammatory effect but exhibited greater toxicity at higher concentrations. Conclusions: Our findings widen the possible range of NISV formulations to include ergosterol or hexadecanoyl glycerol that could be used as an adjuvant treatment for inflammatory diseases like sepsis.Intro: Non-ionic surfactant vesicles (NISV) have previously been used widely in drug delivery and vaccines, with NISV containing mono palmitoyl glycerol (MPG) and cholesterol conferring an anti-inflammatory effect when delivered without a payload in vivo. This formulation was able to reduce production of pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumour necrosis factor α (TNFα), which are commonly involved in pathology of sepsis and toxoplasma gondii infection. Methods: new NISV formulations based on those containing MPG and cholesterol were produced with the surfactant component replaced (hexadecanoylglyceroyl (HG) instead of MPG), or the sterol component replaced (ergosterol or stigmasterol instead of cholesterol) at the same molar ratio as previous NISV. Macrophages were stimulated with NISV formulations alone or with NISV and LPS for 24hrs and cellular viability assessed with alamarblue assay. ELISA for IL-6 was performed on supernatants from these cells to determine degree of anti-inflammatory effect after 24hr stimulation. RESULTS: Individual components contributed to cellular toxicity but had no anti-inflammatory effect when not formulated into vesicles. A reduction in IL-6 was found in NISV irrespective of whether the sterol was cholesterol or ergosterol. NISV containing HG instead of MPG retained the anti-inflammatory effect but exhibited greater toxicity at higher concentrations. Conclusions: Our findings widen the possible range of NISV formulations to include ergosterol or hexadecanoyl glycerol that could be used as an adjuvant treatment for inflammatory diseases like sepsis
"Narratives of redemption" : consumers' identity re-construction after having overcome a spell of poverty
No full textPreviously held under moratorium from 16th October 2020 until 16th October 2025.This study illustrates how consumers produce different culturally constituted accounts
of assigning meaning to a past traumatic event, such as slipping into poverty.
Positioned in Consumer Culture Theory’s (CCT) consuming identity stream of
research, it adresses a gap in the literature on tracing long-termed identity formation
following disruption. As such, the study’s originality stems from offering a focus on
the temporary nature of relative income poverty and its implications on consumers’
identity (re)-construction. Both a narrative theoretical lens and methodology were
deployed to explore the cumulative impact of such multiple transitions over time
(downward and upward) on identity re-construction. Following others who have
drawn consumption insights from autobiographic work (Hirschman, 1990; Turley and
O’Donohoe, 2012; O’Donohoe, 2015), published autobiographies from German
poverty survivors were analysed and informed subsequent long (narrative) interviews
with 14 transient poor informants, including book authors.
Findings obtained from analysis of both autobiographical work and interviews make
three broad contributions to consumer research. Firstly, the study reveals that
consumers having undergone major disruptions in their assumptive worlds make use
of different past selves by, for example, rejecting or revisiting them in order to
construct their present and future post-trauma consuming identities. Secondly, the
findings shift the perspective on traumatised consumers from restoring what was lost
during a disconcerting life event (Caldwell and Henry, 2017; Thompson, Henry and
Bardhi, 2018) to transformative identity construction in terms of enduringly leaving
behind pre-crisis selves. Thirdly, this study demonstrates that (transient) low-income
consumers form an important part of voluntary simplicity theorisations.This study illustrates how consumers produce different culturally constituted accounts
of assigning meaning to a past traumatic event, such as slipping into poverty.
Positioned in Consumer Culture Theory’s (CCT) consuming identity stream of
research, it adresses a gap in the literature on tracing long-termed identity formation
following disruption. As such, the study’s originality stems from offering a focus on
the temporary nature of relative income poverty and its implications on consumers’
identity (re)-construction. Both a narrative theoretical lens and methodology were
deployed to explore the cumulative impact of such multiple transitions over time
(downward and upward) on identity re-construction. Following others who have
drawn consumption insights from autobiographic work (Hirschman, 1990; Turley and
O’Donohoe, 2012; O’Donohoe, 2015), published autobiographies from German
poverty survivors were analysed and informed subsequent long (narrative) interviews
with 14 transient poor informants, including book authors.
Findings obtained from analysis of both autobiographical work and interviews make
three broad contributions to consumer research. Firstly, the study reveals that
consumers having undergone major disruptions in their assumptive worlds make use
of different past selves by, for example, rejecting or revisiting them in order to
construct their present and future post-trauma consuming identities. Secondly, the
findings shift the perspective on traumatised consumers from restoring what was lost
during a disconcerting life event (Caldwell and Henry, 2017; Thompson, Henry and
Bardhi, 2018) to transformative identity construction in terms of enduringly leaving
behind pre-crisis selves. Thirdly, this study demonstrates that (transient) low-income
consumers form an important part of voluntary simplicity theorisations
Study of the effect of RF synthesis parameters on the superinsulating properties of xerogel composite blankets
No full textControl of nonlinear laser pulse propagation in plasma with strong magnetic fields
Get PDFWe examine nonlinear laser pulse dynamics in plasma, encompassing both transverse and longitudinal envelope effects, in isolation and when coupled by the plasma. This is underpinned by an interest in how strong magnetic fields, aligned along the laser axis, modify these processes.In the presence of a strong magnetic field, such that the electron cyclotron frequency is on the order of the laser frequency, there is dramatic modification to the laser-plasma interactions,with the electron motion under left circularly polarised light remaining weakly-relativistic-like at laser intensities typically associated with fully-relativistic behaviour. Conversely right circularly polarised light sees the opposite effect, with the laser-plasma interactions becoming nonlinear at much lower light intensities. This affects all processes underpinned by relativistic motion of the electrons, chiefly self-focusing and self-compression. Such processes are studied in detail for both unmagnetised and magnetised plasma, and the results are compared. We find that not only does an external field alter the relativistic response of the electrons, but it also modifies the laser group and phase velocities, making the pulse shape of interest to the envelope dynamics. We apply this to study spherical compression of a laser pulse, wherein the pulse dimensions reduce symmetrically towards a single cycle. This process results in greatly amplified single-cycle pulses in the lambda-cubic regime, which may peak at over 100 times the initial laser intensity. Finally, the process by which a fully relativistic pulse may amplify an existing magnetic field is examined. We find that while this effect is known of for Laguerre-Gaussian light, it can also occur for linearly polarised light. The pondero motive effect of the laser, and the external field trapping particles which would otherwise escape, bends their trajectories such that a self-sustaining azimuthal current forms. This current scales with both laser intensity and plasma density, and may produce fields of up to 10 kilotesla. We offer that this work may be of interest for the manipulation of low-power or long-wavelength lasers in underdense plasma, the generation of single-cycle pulses for high-harmonic generation and the generation of localised,quasistatic ultra-intense magnetic fields.We examine nonlinear laser pulse dynamics in plasma, encompassing both transverse and longitudinal envelope effects, in isolation and when coupled by the plasma. This is underpinned by an interest in how strong magnetic fields, aligned along the laser axis, modify these processes.In the presence of a strong magnetic field, such that the electron cyclotron frequency is on the order of the laser frequency, there is dramatic modification to the laser-plasma interactions,with the electron motion under left circularly polarised light remaining weakly-relativistic-like at laser intensities typically associated with fully-relativistic behaviour. Conversely right circularly polarised light sees the opposite effect, with the laser-plasma interactions becoming nonlinear at much lower light intensities. This affects all processes underpinned by relativistic motion of the electrons, chiefly self-focusing and self-compression. Such processes are studied in detail for both unmagnetised and magnetised plasma, and the results are compared. We find that not only does an external field alter the relativistic response of the electrons, but it also modifies the laser group and phase velocities, making the pulse shape of interest to the envelope dynamics. We apply this to study spherical compression of a laser pulse, wherein the pulse dimensions reduce symmetrically towards a single cycle. This process results in greatly amplified single-cycle pulses in the lambda-cubic regime, which may peak at over 100 times the initial laser intensity. Finally, the process by which a fully relativistic pulse may amplify an existing magnetic field is examined. We find that while this effect is known of for Laguerre-Gaussian light, it can also occur for linearly polarised light. The pondero motive effect of the laser, and the external field trapping particles which would otherwise escape, bends their trajectories such that a self-sustaining azimuthal current forms. This current scales with both laser intensity and plasma density, and may produce fields of up to 10 kilotesla. We offer that this work may be of interest for the manipulation of low-power or long-wavelength lasers in underdense plasma, the generation of single-cycle pulses for high-harmonic generation and the generation of localised,quasistatic ultra-intense magnetic fields
End-to-end integrated activity planning and scheduling framework
No full textStrathclyde theses - ask staff. Thesis no. : T1583
Investigation of computer vision techniques for automatic detection of mild cognitive impairment in the elderly
Get PDFThere are huge amounts of elderly people who suffer from cognitive impairment worldwide. Cognitive impairment can be divided into different stages such as mild cognitive impairment (MCI) and severe cognitive impairment like dementia. Its early detection can be of great importance. However, it is challenging to detect the cognitive impairment in the early stage with high accuracy and low cost, when most of the symptoms may not be fully expressed.;Although there have been some big changes and progresses in the field of detecting and diagnosing the cognitive impairment in recent years, all these existing techniques have their own weaknesses. Regarding the weaknesses of the existing techniques, both the traditional face to face cognitive tests and computer-based cognitive tests have the problems with diagnosing the mild cognitive impairment. More specifically, some personal information like age, education and personality will influence the test results and need to be taken into consideration carefully.;While the neuroimaging techniques are widely used in clinics, their major weakness is the high expenses required in the screening stage. Besides, the neuroimaging techniques are often used to diagnose the cognitive impairment only when the patients are found to have serious cognitive problems.;As a result, there is a pressing need to find alternative methods to detect the cognitive impairment in the early stage with high accuracy and low cost. In fact, some research works suggest that automatic facial expression recognition is promising in mental health care systems, as facial expressions can reflect people's mental state. Whilst viewing videos, studies have shown that the facial expressions of people with cognitive impairment exhibit abnormal corrugator activities compared to those without cognitive impairment. As a result, analysis of the facial expressions has the potential to detect the cognitive impairment.;In this thesis, a novel strategy for cognitive impairment detection is proposed, which is significantly different from the traditional methods like cognitive tests and neuroimaging techniques. The proposed strategy takes advantages of visual stimuli in the experiment and it mainly uses facial expressions and responses to detect the cognitive impairment when the participants are presentenced with the visual stimuli. As a result, this novel strategy for cognitive impairment detection with acceptable accuracy and low cost is achieved.;I present a novel deep convolution network-based system to detect the cognitive impairment in the early stage and support mental state diagnosis and detection. In the system, there are three important units in the proposed cognitive impairment detection system including the interface to arouse the facial expression, the proposed facial expression recognition algorithm and the algorithm to detect the cognitive impairment through the evolution of emotions. Among the cognitive impairment detection system, facial expression analysis is an important part. For facial expression analysis, this research presents a new solution in which the deep features are extracted from the Fully Connected Layer 6 of the AlexNet, with a standard Linear Discriminant Analysis Classifier exploited to train these deep features more efficiently.;The proposed algorithms are tested in 5 benchmarking databases: databases with limited images such as JAFFE, KDEF and CK+, and databases with images 'in the wild' such as FER2013 and AffectNet. Compared with the traditional methods and state-of-the-art methods proposed by other researchers, the algorithms have overall higher facial expression recognition accuracy. Also, in comparison to the state-of-the-art deep learning algorithms such as VGG16, GoogleNet, ResNet and AlexNet, the proposed method also has good recognition accuracy, much shorter operating time and lower device requirements.;In order to verify the system, I first made an experiment design. Then, clinical experiments were carried out in Shanghai, under the support from Dr Xia Li who is the chief physician in Mental Health Centre in Shanghai. After the recruitment procedure, a group of elderly people including cognitively impaired people and cognitively healthy people were invited to take part in the experiments. After the experiments in Shanghai, I classified the experiment data and used the proposed system to process the data.;I compared the major differences in the emotion evolution, including angry, happy, neutral and sad, between the cognitively impaired people and cognitively healthy people when they were watching the same video stimuli. In the selected testing group, the system had an overall cognitive impairment recognition accuracy of 66.7% using KNN classifier based on their evolutions of emotions.There are huge amounts of elderly people who suffer from cognitive impairment worldwide. Cognitive impairment can be divided into different stages such as mild cognitive impairment (MCI) and severe cognitive impairment like dementia. Its early detection can be of great importance. However, it is challenging to detect the cognitive impairment in the early stage with high accuracy and low cost, when most of the symptoms may not be fully expressed.;Although there have been some big changes and progresses in the field of detecting and diagnosing the cognitive impairment in recent years, all these existing techniques have their own weaknesses. Regarding the weaknesses of the existing techniques, both the traditional face to face cognitive tests and computer-based cognitive tests have the problems with diagnosing the mild cognitive impairment. More specifically, some personal information like age, education and personality will influence the test results and need to be taken into consideration carefully.;While the neuroimaging techniques are widely used in clinics, their major weakness is the high expenses required in the screening stage. Besides, the neuroimaging techniques are often used to diagnose the cognitive impairment only when the patients are found to have serious cognitive problems.;As a result, there is a pressing need to find alternative methods to detect the cognitive impairment in the early stage with high accuracy and low cost. In fact, some research works suggest that automatic facial expression recognition is promising in mental health care systems, as facial expressions can reflect people's mental state. Whilst viewing videos, studies have shown that the facial expressions of people with cognitive impairment exhibit abnormal corrugator activities compared to those without cognitive impairment. As a result, analysis of the facial expressions has the potential to detect the cognitive impairment.;In this thesis, a novel strategy for cognitive impairment detection is proposed, which is significantly different from the traditional methods like cognitive tests and neuroimaging techniques. The proposed strategy takes advantages of visual stimuli in the experiment and it mainly uses facial expressions and responses to detect the cognitive impairment when the participants are presentenced with the visual stimuli. As a result, this novel strategy for cognitive impairment detection with acceptable accuracy and low cost is achieved.;I present a novel deep convolution network-based system to detect the cognitive impairment in the early stage and support mental state diagnosis and detection. In the system, there are three important units in the proposed cognitive impairment detection system including the interface to arouse the facial expression, the proposed facial expression recognition algorithm and the algorithm to detect the cognitive impairment through the evolution of emotions. Among the cognitive impairment detection system, facial expression analysis is an important part. For facial expression analysis, this research presents a new solution in which the deep features are extracted from the Fully Connected Layer 6 of the AlexNet, with a standard Linear Discriminant Analysis Classifier exploited to train these deep features more efficiently.;The proposed algorithms are tested in 5 benchmarking databases: databases with limited images such as JAFFE, KDEF and CK+, and databases with images 'in the wild' such as FER2013 and AffectNet. Compared with the traditional methods and state-of-the-art methods proposed by other researchers, the algorithms have overall higher facial expression recognition accuracy. Also, in comparison to the state-of-the-art deep learning algorithms such as VGG16, GoogleNet, ResNet and AlexNet, the proposed method also has good recognition accuracy, much shorter operating time and lower device requirements.;In order to verify the system, I first made an experiment design. Then, clinical experiments were carried out in Shanghai, under the support from Dr Xia Li who is the chief physician in Mental Health Centre in Shanghai. After the recruitment procedure, a group of elderly people including cognitively impaired people and cognitively healthy people were invited to take part in the experiments. After the experiments in Shanghai, I classified the experiment data and used the proposed system to process the data.;I compared the major differences in the emotion evolution, including angry, happy, neutral and sad, between the cognitively impaired people and cognitively healthy people when they were watching the same video stimuli. In the selected testing group, the system had an overall cognitive impairment recognition accuracy of 66.7% using KNN classifier based on their evolutions of emotions
A comparative analysis of algorithms for satellite operations scheduling
Get PDFScheduling is employed in everyday life, ranging from meetings to manufacturing and operations among other activities. One instance of scheduling in a complex real-life setting is space mission operations scheduling, i.e. instructing a satellite to perform fitting tasks during predefined time periods with a varied frequency to achieve its mission goals. Mission operations scheduling is pivotal to the success of any space mission, choreographing every task carefully, accounting for technological and environmental limitations and constraints along with mission goals.;It remains standard practice to this day, to generate operations schedules manually ,i.e. to collect requirements from individual stakeholders, collate them into a timeline, compare against feasibility and available satellite resources, and find potential conflicts. Conflict resolution is done by hand, checked by a simulator and uplinked to the satellite weekly. This process is time consuming, bears risks and can be considered sub-optimal.;A pertinent question arises: can we automate the process of satellite mission operations scheduling? And if we can, what method should be used to generate the schedules? In an attempt to address this question, a comparison of algorithms was deemed suitable in order to explore their suitability for this particular application.;The problem of mission operations scheduling was initially studied through literature and numerous interviews with experts. A framework was developed to approximate a generic Low Earth Orbit satellite, its environment and its mission requirements. Optimisation algorithms were chosen from different categories such as single-point stochastic without memory (Simulated Annealing, Random Search), multi-point stochastic with memory (Genetic Algorithm, Ant Colony System, Differential Evolution) and were run both with and without Local Search.;The aforementioned algorithmic set was initially tuned using a single 89-minute Low Earth Orbit of a scientific mission to Mars. It was then applied to scheduling operations during one high altitude Low Earth Orbit (2.4hrs) of an experimental mission.;It was then applied to a realistic test-case inspired by the European Space Agency PROBA-2 mission, comprising a 1 day schedule and subsequently a 7 day schedule - equal to a Short Term Plan as defined by the European Space Agency.;The schedule fitness - corresponding to the Hamming distance between mission requirements and generated schedule - are presented along with the execution time of each run. Algorithmic performance is discussed and put at the disposal of mission operations experts for consideration.Scheduling is employed in everyday life, ranging from meetings to manufacturing and operations among other activities. One instance of scheduling in a complex real-life setting is space mission operations scheduling, i.e. instructing a satellite to perform fitting tasks during predefined time periods with a varied frequency to achieve its mission goals. Mission operations scheduling is pivotal to the success of any space mission, choreographing every task carefully, accounting for technological and environmental limitations and constraints along with mission goals.;It remains standard practice to this day, to generate operations schedules manually ,i.e. to collect requirements from individual stakeholders, collate them into a timeline, compare against feasibility and available satellite resources, and find potential conflicts. Conflict resolution is done by hand, checked by a simulator and uplinked to the satellite weekly. This process is time consuming, bears risks and can be considered sub-optimal.;A pertinent question arises: can we automate the process of satellite mission operations scheduling? And if we can, what method should be used to generate the schedules? In an attempt to address this question, a comparison of algorithms was deemed suitable in order to explore their suitability for this particular application.;The problem of mission operations scheduling was initially studied through literature and numerous interviews with experts. A framework was developed to approximate a generic Low Earth Orbit satellite, its environment and its mission requirements. Optimisation algorithms were chosen from different categories such as single-point stochastic without memory (Simulated Annealing, Random Search), multi-point stochastic with memory (Genetic Algorithm, Ant Colony System, Differential Evolution) and were run both with and without Local Search.;The aforementioned algorithmic set was initially tuned using a single 89-minute Low Earth Orbit of a scientific mission to Mars. It was then applied to scheduling operations during one high altitude Low Earth Orbit (2.4hrs) of an experimental mission.;It was then applied to a realistic test-case inspired by the European Space Agency PROBA-2 mission, comprising a 1 day schedule and subsequently a 7 day schedule - equal to a Short Term Plan as defined by the European Space Agency.;The schedule fitness - corresponding to the Hamming distance between mission requirements and generated schedule - are presented along with the execution time of each run. Algorithmic performance is discussed and put at the disposal of mission operations experts for consideration
How efficient were state and non-state actors in providing humanitarian relief to persons displaced as a result of Nazi concentration camps c.1944-1948?
No full textThere is a considerable lack of literature in the scholarship surrounding the aftermath of the Holocaust, particularly from a humanitarian perspective. As humanitarianism and humanitarian relief are currently such important topics in the fields of history and International Relations as demonstrated by Jacqueline des Forges, Daniel Cohen and Mary Kaldor, this dissertation will investigate humanitarian relief. There is an interdisciplinary approach to this dissertation as it will regard international relations theories applied to the historical context of the aftermath of the Holocaust. The focus will be on humanitarian relief and the question of whether states have a duty to provide it and who will provide it if a state is not able to or chooses not to. This dissertation is set within the contextual historical background of the Holocaust which occurred between 1941 and 1945, affecting much of the European continent. Throughout this dissertation, the main state actors consist of France and Great Britain, as this was a defining point in UK-French history and diplomacy, with the occupation of France changing not only France's position in the international community, but deeply affecting its relationship with Britain.;Much of the literature regarding this transitional phase often focuses on the Second World War or the year leading up to enactment of the Marshall Plan in 1948. Therefore, the focus will be on the period in between but including the latter part of the war to provide more context (1944 to 1948). This will address this lacuna in the field. It was discovered during the research for this dissertation that Britain and France contributed little to the humanitarian efforts of concentration camp survivors, with international organisations such as the UNRRA and the ICRC contributing the largest relief efforts. Britain and France became more active during the reconstruction of their respective countries, although International Relations theories, such as neo-realism, suggest that there is often a second motive behind charitable actions. The lack of state-supported integration, along with the psychological difficulties of survivors and those who were non repatriable, shows that there are many difficult factors that make it a challenge to conclude whether Britain and France were efficient in providing humanitarian relief to persons displaced as a result of Nazi concentration camps between 1944 and 1948.There is a considerable lack of literature in the scholarship surrounding the aftermath of the Holocaust, particularly from a humanitarian perspective. As humanitarianism and humanitarian relief are currently such important topics in the fields of history and International Relations as demonstrated by Jacqueline des Forges, Daniel Cohen and Mary Kaldor, this dissertation will investigate humanitarian relief. There is an interdisciplinary approach to this dissertation as it will regard international relations theories applied to the historical context of the aftermath of the Holocaust. The focus will be on humanitarian relief and the question of whether states have a duty to provide it and who will provide it if a state is not able to or chooses not to. This dissertation is set within the contextual historical background of the Holocaust which occurred between 1941 and 1945, affecting much of the European continent. Throughout this dissertation, the main state actors consist of France and Great Britain, as this was a defining point in UK-French history and diplomacy, with the occupation of France changing not only France's position in the international community, but deeply affecting its relationship with Britain.;Much of the literature regarding this transitional phase often focuses on the Second World War or the year leading up to enactment of the Marshall Plan in 1948. Therefore, the focus will be on the period in between but including the latter part of the war to provide more context (1944 to 1948). This will address this lacuna in the field. It was discovered during the research for this dissertation that Britain and France contributed little to the humanitarian efforts of concentration camp survivors, with international organisations such as the UNRRA and the ICRC contributing the largest relief efforts. Britain and France became more active during the reconstruction of their respective countries, although International Relations theories, such as neo-realism, suggest that there is often a second motive behind charitable actions. The lack of state-supported integration, along with the psychological difficulties of survivors and those who were non repatriable, shows that there are many difficult factors that make it a challenge to conclude whether Britain and France were efficient in providing humanitarian relief to persons displaced as a result of Nazi concentration camps between 1944 and 1948
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