14,154 research outputs found
Bayesian networks for disease diagnosis: What are they, who has used them and how?
A Bayesian network (BN) is a probabilistic graph based on Bayes' theorem,
used to show dependencies or cause-and-effect relationships between variables.
They are widely applied in diagnostic processes since they allow the
incorporation of medical knowledge to the model while expressing uncertainty in
terms of probability. This systematic review presents the state of the art in
the applications of BNs in medicine in general and in the diagnosis and
prognosis of diseases in particular. Indexed articles from the last 40 years
were included. The studies generally used the typical measures of diagnostic
and prognostic accuracy: sensitivity, specificity, accuracy, precision, and the
area under the ROC curve. Overall, we found that disease diagnosis and
prognosis based on BNs can be successfully used to model complex medical
problems that require reasoning under conditions of uncertainty.Comment: 22 pages, 5 figures, 1 table, Student PhD first pape
Preferentialism and the conditionality of trade agreements. An application of the gravity model
Modern economic growth is driven by international trade, and the preferential trade agreement constitutes the primary fit-for-purpose mechanism of choice for establishing, facilitating, and governing its flows. However, too little attention has been afforded to the differences in content and conditionality associated with different trade agreements. This has led to an under-considered mischaracterisation of the design-flow relationship. Similarly, while the relationship between trade facilitation and trade is clear, the way trade facilitation affects other areas of economic activity, with respect to preferential trade agreements, has received considerably less attention. Particularly, in light of an increasingly globalised and interdependent trading system, the interplay between trade facilitation and foreign direct investment is of particular importance.
Accordingly, this thesis explores the bilateral trade and investment effects of specific conditionality sets, as established within Preferential Trade Agreements (PTAs).
Chapter one utilises recent content condition-indexes for depth, flexibility, and constraints on flexibility, established by DĂŒr et al. (2014) and Baccini et al. (2015), within a gravity framework to estimate the average treatment effect of trade agreement characteristics across bilateral trade relationships in the Association of Southeast Asian Nations (ASEAN) from 1948-2015. This chapter finds that the composition of a given ASEAN trade agreementâs characteristic set has significantly determined the concomitant bilateral trade flows. Conditions determining the classification of a trade agreements depth are positively associated with an increase to bilateral trade; hereby representing the furthered removal of trade barriers and frictions as facilitated by deeper trade agreements. Flexibility conditions, and constraint on flexibility conditions, are also identified as significant determiners for a given trade agreementâs treatment effect of subsequent bilateral trade flows. Given the political nature of their inclusion (i.e., the appropriate address to short term domestic discontent) this influence is negative as regards trade flows. These results highlight the longer implementation and time frame requirements for trade impediments to be removed in a market with higher domestic uncertainty.
Chapter two explores the incorporation of non-trade issue (NTI) conditions in PTAs. Such conditions are increasing both at the intensive and extensive margins. There is a concern from developing nations that this growth of NTI inclusions serves as a way for high-income (HI) nations to dictate the trade agenda, such that developing nations are subject to âprincipled protectionismâ. There is evidence that NTI provisions are partly driven by protectionist motives but the effect on trade flows remains largely undiscussed. Utilising the Gravity Model for trade, I test Lechnerâs (2016) comprehensive NTI dataset for 202 bilateral country pairs across a 32-year timeframe and find that, on average, NTIs are associated with an increase to bilateral trade. Primarily this boost can be associated with the market access that a PTA utilising NTIs facilitates. In addition, these results are aligned theoretically with the discussions on market harmonisation, shared values, and the erosion of artificial production advantages. Instead of inhibiting trade through burdensome cost, NTIs are acting to support a more stable production and trading environment, motivated by enhanced market access. Employing a novel classification to capture the power supremacy associated with shaping NTIs, this chapter highlights that the positive impact of NTIs is largely driven by the relationship between HI nations and middle-to-low-income (MTLI) counterparts.
Chapter Three employs the gravity model, theoretically augmented for foreign direct investment (FDI), to estimate the effects of trade facilitation conditions utilising indexes established by Neufeld (2014) and the bilateral FDI data curated by UNCTAD (2014). The resultant dataset covers 104 countries, covering a period of 12 years (2001â2012), containing 23,640 observations. The results highlight the bilateral-FDI enhancing effects of trade facilitation conditions in the ASEAN context, aligning itself with the theoretical branch of FDI-PTA literature that has outlined how the ratification of a trade agreement results in increased and positive economic prospect between partners (Medvedev, 2012) resulting from the interrelation between trade and investment as set within an improving regulatory environment. The results align with the expectation that an enhanced trade facilitation landscape (one in which such formalities, procedures, information, and expectations around trade facilitation are conditioned for) is expected to incentivise and attract FDI
Multiscale structural optimisation with concurrent coupling between scales
A robust three-dimensional multiscale topology optimisation framework with concurrent coupling between scales is presented. Concurrent coupling ensures that only the microscale data required to evaluate the macroscale model during each iteration of optimisation is collected and results in considerable computational savings. This represents the principal novelty of the framework and permits a previously intractable number of design variables to be used in the parametrisation of the microscale geometry, which in turn enables accessibility to a greater range of mechanical point properties during optimisation. Additionally, the microscale data collected during optimisation is stored in a re-usable database, further reducing the computational expense of subsequent iterations or entirely new optimisation problems. Application of this methodology enables structures with precise functionally-graded mechanical properties over two-scales to be derived, which satisfy one or multiple functional objectives. For all applications of the framework presented within this thesis, only a small fraction of the microstructure database is required to derive the optimised multiscale solutions, which demonstrates a significant reduction in the computational expense of optimisation in comparison to contemporary sequential frameworks.
The derivation and integration of novel additive manufacturing constraints for open-walled microstructures within the concurrently coupled multiscale topology optimisation framework is also presented. Problematic fabrication features are discouraged through the application of an augmented projection filter and two relaxed binary integral constraints, which prohibit the formation of unsupported members, isolated assemblies of overhanging members and slender members during optimisation. Through the application of these constraints, it is possible to derive self-supporting, hierarchical structures with varying topology, suitable for fabrication through additive manufacturing processes.Open Acces
Modelling and Solving the Single-Airport Slot Allocation Problem
Currently, there are about 200 overly congested airports where airport capacity does not suffice to accommodate airline demand. These airports play a critical role in the global air transport system since they concern 40% of global passenger demand and act as a bottleneck for the entire air transport system. This imbalance between airport capacity and airline demand leads to excessive delays, as well as multi-billion economic, and huge environmental and societal costs. Concurrently, the implementation of airport capacity expansion projects requires time, space and is subject to significant resistance from local communities. As a short to medium-term response, Airport Slot Allocation (ASA) has been used as the main demand management mechanism. The main goal of this thesis is to improve ASA decision-making through the proposition of models and algorithms that provide enhanced ASA decision support. In doing so, this thesis is organised into three distinct chapters that shed light on the following questions (IâV), which remain untapped by the existing literature. In parentheses, we identify the chapters of this thesis that relate to each research question. I. How to improve the modelling of airline demand flexibility and the utility that each airline assigns to each available airport slot? (Chapters 2 and 4) II. How can one model the dynamic and endogenous adaptation of the airportâs landside and airside infrastructure to the characteristics of airline demand? (Chapter 2) III. How to consider operational delays in strategic ASA decision-making? (Chapter 3) IV. How to involve the pertinent stakeholders into the ASA decision-making process to select a commonly agreed schedule; and how can one reduce the inherent decision-complexity without compromising the quality and diversity of the schedules presented to the decision-makers? (Chapter 3) V. Given that the ASA process involves airlines (submitting requests for slots) and coordinators (assigning slots to requests based on a set of rules and priorities), how can one jointly consider the interactions between these two sides to improve ASA decision-making? (Chapter 4) With regards to research questions (I) and (II), the thesis proposes a Mixed Integer Programming (MIP) model that considers airlinesâ timing flexibility (research question I) and constraints that enable the dynamic and endogenous allocation of the airportâs resources (research question II). The proposed modelling variant addresses several additional problem characteristics and policy rules, and considers multiple efficiency objectives, while integrating all constraints that may affect airport slot scheduling decisions, including the asynchronous use of the different airport resources (runway, aprons, passenger terminal) and the endogenous consideration of the capabilities of the airportâs infrastructure to adapt to the airline demandâs characteristics and the aircraft/flight type associated with each request. The proposed model is integrated into a two-stage solution approach that considers all primary and several secondary policy rules of ASA. New combinatorial results and valid tightening inequalities that facilitate the solution of the problem are proposed and implemented. An extension of the above MIP model that considers the trade-offs among schedule displacement, maximum displacement, and the number of displaced requests, is integrated into a multi-objective solution framework. The proposed framework holistically considers the preferences of all ASA stakeholder groups (research question IV) concerning multiple performance metrics and models the operational delays associated with each airport schedule (research question III). The delays of each schedule/solution are macroscopically estimated, and a subtractive clustering algorithm and a parameter tuning routine reduce the inherent decision complexity by pruning non-dominated solutions without compromising the representativeness of the alternatives offered to the decision-makers (research question IV). Following the determination of the representative set, the expected delay estimates of each schedule are further refined by considering the whole airfieldâs operations, the landside, and the airside infrastructure. The representative schedules are ranked based on the preferences of all ASA stakeholder groups concerning each scheduleâs displacement-related and operational-delay performance. Finally, in considering the interactions between airlinesâ timing flexibility and utility, and the policy-based priorities assigned by the coordinator to each request (research question V), the thesis models the ASA problem as a two-sided matching game and provides guarantees on the stability of the proposed schedules. A Stable Airport Slot Allocation Model (SASAM) capitalises on the flexibility considerations introduced for addressing research question (I) through the exploitation of data submitted by the airlines during the ASA process and provides functions that proxy each requestâs value considering both the airlinesâ timing flexibility for each submitted request and the requestsâ prioritisation by the coordinators when considering the policy rules defining the ASA process. The thesis argues on the compliance of the proposed functions with the primary regulatory requirements of the ASA process and demonstrates their applicability for different types of slot requests. SASAM guarantees stability through sets of inequalities that prune allocations blocking the formation of stable schedules. A multi-objective Deferred-Acceptance (DA) algorithm guaranteeing the stability of each generated schedule is developed. The algorithm can generate all stable non-dominated points by considering the trade-off between the spilled airline and passenger demand and maximum displacement. The work conducted in this thesis addresses several problem characteristics and sheds light on their implications for ASA decision-making, hence having the potential to improve ASA decision-making. Our findings suggest that the consideration of airlinesâ timing flexibility (research question I) results in improved capacity utilisation and scheduling efficiency. The endogenous consideration of the ability of the airportâs infrastructure to adapt to the characteristics of airline demand (research question II) enables a more efficient representation of airport declared capacity that results in the scheduling of additional requests. The concurrent consideration of airlinesâ timing flexibility and the endogenous adaptation of airport resources to airline demand achieves an improved alignment between the airport infrastructure and the characteristics of airline demand, ergo proposing schedules of improved efficiency. The modelling and evaluation of the peak operational delays associated with the different airport schedules (research question III) provides allows the study of the implications of strategic ASA decision-making for operations and quantifies the impact of the airportâs declared capacity on each scheduleâs operational performance. In considering the preferences of the relevant ASA stakeholders (airlines, coordinators, airport, and air traffic authorities) concerning multiple operational and strategic ASA efficiency metrics (research question IV) the thesis assesses the impact of alternative preference considerations and indicates a commonly preferred schedule that balances the stakeholdersâ preferences. The proposition of representative subsets of alternative schedules reduces decision-complexity without significantly compromising the quality of the alternatives offered to the decision-making process (research question IV). The modelling of the ASA as a two-sided matching game (research question V), results in stable schedules consisting of request-to-slot assignments that provide no incentive to airlines and coordinators to reject or alter the proposed timings. Furthermore, the proposition of stable schedules results in more intensive use of airport capacity, while simultaneously improving scheduling efficiency. The models and algorithms developed as part of this thesis are tested using airline requests and airport capacity data from coordinated airports. Computational results that are relevant to the context of the considered airport instances provide evidence on the potential improvements for the current ASA process and facilitate data-driven policy and decision-making. In particular, with regards to the alignment of airline demand with the capabilities of the airportâs infrastructure (questions I and II), computational results report improved slot allocation efficiency and airport capacity utilisation, which for the considered airport instance translate to improvements ranging between 5-24% for various schedule performance metrics. In reducing the difficulty associated with the assessment of multiple ASA solutions by the stakeholders (question IV), instance-specific results suggest reductions to the number of alternative schedules by 87%, while maintaining the quality of the solutions presented to the stakeholders above 70% (expressed in relation to the initially considered set of schedules). Meanwhile, computational results suggest that the concurrent consideration of ASA stakeholdersâ preferences (research question IV) with regards to both operational (research question III) and strategic performance metrics leads to alternative airport slot scheduling solutions that inform on the trade-offs between the schedulesâ operational and strategic performance and the stakeholdersâ preferences. Concerning research question (V), the application of SASAM and the DA algorithm suggest improvements to the number of unaccommodated flights and passengers (13 and 40% improvements) at the expense of requests concerning fewer passengers and days of operations (increasing the number of rejected requests by 1.2% in relation to the total number of submitted requests). The research conducted in this thesis aids in the identification of limitations that should be addressed by future studies to further improve ASA decision-making. First, the thesis focuses on exact solution approaches that consider the landside and airside infrastructure of the airport and generate multiple schedules. The proposition of pre-processing techniques that identify the bottleneck of the airportâs capacity, i.e., landside and/or airside, can be used to reduce the size of the proposed formulations and improve the required computational times. Meanwhile, the development of multi-objective heuristic algorithms that consider several problem characteristics and generate multiple efficient schedules in reasonable computational times, could extend the capabilities of the models propositioned in this thesis and provide decision support for some of the worldâs most congested airports. Furthermore, the thesis models and evaluates the operational implications of strategic airport slot scheduling decisions. The explicit consideration of operational delays as an objective in ASA optimisation models and algorithms is an issue that merits investigation since it may further improve the operational performance of the generated schedules. In accordance with current practice, the models proposed in this work have considered deterministic capacity parameters. Perhaps, future research could propose formulations that consider stochastic representations of airport declared capacity and improve strategic ASA decision-making through the anticipation of operational uncertainty and weather-induced capacity reductions. Finally, in modelling airlinesâ utility for each submitted request and available time slot the thesis proposes time-dependent functions that utilise available data to approximate airlinesâ scheduling preferences. Future studies wishing to improve the accuracy of the proposed functions could utilise commercial data sources that provide route-specific information; or in cases that such data is unavailable, employ data mining and machine learning methodologies to extract airlinesâ time-dependent utility and preferences
Networks: A study in Analysis and Design
In this dissertation, we will look at two fundamental aspects of Networks: Network Analysis and Network Design. In part A, we look at Network Analysis area of the dissertation which involves finding the densest subgraph in each graph. The densest subgraph extraction problem is fundamentally a non-linear optimization problem. Nevertheless, it can be solved in polynomial time by an exact algorithm based on the iterative solution of a series of max-flow sub-problems. To approach graphs with millions of vertices and edges, one must resort to heuristic algorithms. We provide an efficient implementation of a greedy heuristic from the literature that is extremely fast and has some nice theoretical properties. An extensive computational analysis shows that the proposed heuristic algorithm proved very effective on many test instances, often providing either the optimal solution or near-optimal solution within short computing times. In part-B, we discuss Network design, which is a cornerstone of mathematical optimization, is about defining the main characteristics of a network satisfying requirements on connectivity, capacity, and level-of-service. In multi-commodity network design, one is required to design a network minimizing the installation cost of its arcs and the operational cost to serve a set of point-to-point connections. This prototypical problem was recently enriched by additional constraints imposing that each origin-destination of a connection is served by a single path satisfying one or more level-of-service requirements, thus defining the Network Design with Service Requirements. These constraints are crucial, e.g., in telecommunications and computer networks, in order to ensure reliable and low-latency communication. We provide a new formulation for the problem, where variables are associated with paths satisfying the end-to-end service requirements. A fast algorithm for enumerating all the exponentially-many feasible paths and, when this is not viable, a column generation scheme that is embedded into a branch-and-cut-and-price algorithm is provided
Foundations for programming and implementing effect handlers
First-class control operators provide programmers with an expressive and efficient
means for manipulating control through reification of the current control state as a first-class object, enabling programmers to implement their own computational effects and
control idioms as shareable libraries. Effect handlers provide a particularly structured
approach to programming with first-class control by naming control reifying operations
and separating from their handling.
This thesis is composed of three strands of work in which I develop operational
foundations for programming and implementing effect handlers as well as exploring
the expressive power of effect handlers.
The first strand develops a fine-grain call-by-value core calculus of a statically
typed programming language with a structural notion of effect types, as opposed to the
nominal notion of effect types that dominates the literature. With the structural approach,
effects need not be declared before use. The usual safety properties of statically typed
programming are retained by making crucial use of row polymorphism to build and
track effect signatures. The calculus features three forms of handlers: deep, shallow,
and parameterised. They each offer a different approach to manipulate the control state
of programs. Traditional deep handlers are defined by folds over computation trees,
and are the original con-struct proposed by Plotkin and Pretnar. Shallow handlers are
defined by case splits (rather than folds) over computation trees. Parameterised handlers
are deep handlers extended with a state value that is threaded through the folds over
computation trees. To demonstrate the usefulness of effects and handlers as a practical
programming abstraction I implement the essence of a small UNIX-style operating
system complete with multi-user environment, time-sharing, and file I/O.
The second strand studies continuation passing style (CPS) and abstract machine
semantics, which are foundational techniques that admit a unified basis for implementing deep, shallow, and parameterised effect handlers in the same environment. The
CPS translation is obtained through a series of refinements of a basic first-order CPS
translation for a fine-grain call-by-value language into an untyped language. Each refinement moves toward a more intensional representation of continuations eventually
arriving at the notion of generalised continuation, which admit simultaneous support for
deep, shallow, and parameterised handlers. The initial refinement adds support for deep
handlers by representing stacks of continuations and handlers as a curried sequence of
arguments. The image of the resulting translation is not properly tail-recursive, meaning some function application terms do not appear in tail position. To rectify this the
CPS translation is refined once more to obtain an uncurried representation of stacks
of continuations and handlers. Finally, the translation is made higher-order in order to
contract administrative redexes at translation time. The generalised continuation representation is used to construct an abstract machine that provide simultaneous support for
deep, shallow, and parameterised effect handlers. kinds of effect handlers.
The third strand explores the expressiveness of effect handlers. First, I show that
deep, shallow, and parameterised notions of handlers are interdefinable by way of typed
macro-expressiveness, which provides a syntactic notion of expressiveness that affirms
the existence of encodings between handlers, but it provides no information about the
computational content of the encodings. Second, using the semantic notion of expressiveness I show that for a class of programs a programming language with first-class
control (e.g. effect handlers) admits asymptotically faster implementations than possible in a language without first-class control
FiabilitĂ© de lâunderfill et estimation de la durĂ©e de vie dâassemblages microĂ©lectroniques
Abstract : In order to protect the interconnections in flip-chip packages, an underfill material layer
is used to fill the volumes and provide mechanical support between the silicon chip and
the substrate. Due to the chip corner geometry and the mismatch of coefficient of thermal
expansion (CTE), the underfill suffers from a stress concentration at the chip corners when
the temperature is lower than the curing temperature. This stress concentration leads
to subsequent mechanical failures in flip-chip packages, such as chip-underfill interfacial
delamination and underfill cracking. Local stresses and strains are the most important
parameters for understanding the mechanism of underfill failures. As a result, the industry
currently relies on the finite element method (FEM) to calculate the stress components, but
the FEM may not be accurate enough compared to the actual stresses in underfill. FEM
simulations require a careful consideration of important geometrical details and material
properties. This thesis proposes a modeling approach that can accurately estimate the underfill delamination
areas and crack trajectories, with the following three objectives. The first
objective was to develop an experimental technique capable of measuring underfill deformations
around the chip corner region. This technique combined confocal microscopy and
the digital image correlation (DIC) method to enable tri-dimensional strain measurements
at different temperatures, and was named the confocal-DIC technique. This techique was
first validated by a theoretical analysis on thermal strains. In a test component similar
to a flip-chip package, the strain distribution obtained by the FEM model was in good
agreement with the results measured by the confocal-DIC technique, with relative errors
less than 20% at chip corners. Then, the second objective was to measure the strain near
a crack in underfills. Artificial cracks with lengths of 160 ÎŒm and 640 ÎŒm were fabricated
from the chip corner along the 45° diagonal direction. The confocal-DIC-measured
maximum hoop strains and first principal strains were located at the crack front area for
both the 160 ÎŒm and 640 ÎŒm cracks. A crack model was developed using the extended
finite element method (XFEM), and the strain distribution in the simulation had the same
trend as the experimental results. The distribution of hoop strains were in good agreement
with the measured values, when the model element size was smaller than 22 ÎŒm to
capture the strong strain gradient near the crack tip. The third objective was to propose
a modeling approach for underfill delamination and cracking with the effects of manufacturing
variables. A deep thermal cycling test was performed on 13 test cells to obtain the
reference chip-underfill delamination areas and crack profiles. An artificial neural network
(ANN) was trained to relate the effects of manufacturing variables and the number of
cycles to first delamination of each cell. The predicted numbers of cycles for all 6 cells in
the test dataset were located in the intervals of experimental observations. The growth
of delamination was carried out on FEM by evaluating the strain energy amplitude at
the interface elements between the chip and underfill. For 5 out of 6 cells in validation,
the delamination growth model was consistent with the experimental observations. The
cracks in bulk underfill were modelled by XFEM without predefined paths. The directions of edge cracks were in good agreement with the experimental observations, with an error
of less than 2.5°. This approach met the goal of the thesis of estimating the underfill
initial delamination, areas of delamination and crack paths in actual industrial flip-chip
assemblies.Afin de protĂ©ger les interconnexions dans les assemblages, une couche de matĂ©riau dâunderfill est utilisĂ©e pour remplir le volume et fournir un support mĂ©canique entre la puce de silicium et le substrat. En raison de la gĂ©omĂ©trie du coin de puce et de lâĂ©cart du coefficient de dilatation thermique (CTE), lâunderfill souffre dâune concentration de contraintes dans les coins lorsque la tempĂ©rature est infĂ©rieure Ă la tempĂ©rature de cuisson. Cette concentration de contraintes conduit Ă des dĂ©faillances mĂ©caniques dans les encapsulations de flip-chip, telles que la dĂ©lamination interfaciale puce-underfill et la fissuration dâunderfill. Les contraintes et dĂ©formations locales sont les paramĂštres les plus importants pour comprendre le mĂ©canisme des ruptures de lâunderfill. En consĂ©quent, lâindustrie utilise actuellement la mĂ©thode des Ă©lĂ©ments finis (EF) pour calculer les composantes de la contrainte, qui ne sont pas assez prĂ©cises par rapport aux contraintes actuelles dans lâunderfill. Ces simulations nĂ©cessitent un examen minutieux de dĂ©tails gĂ©omĂ©triques importants et des propriĂ©tĂ©s des matĂ©riaux. Cette thĂšse vise Ă proposer une approche de modĂ©lisation permettant dâestimer avec prĂ©cision les zones de dĂ©lamination et les trajectoires des fissures dans lâunderfill, avec les trois objectifs suivants. Le premier objectif est de mettre au point une technique expĂ©rimentale capable de mesurer la dĂ©formation de lâunderfill dans la rĂ©gion du coin de puce. Cette technique, combine la microscopie confocale et la mĂ©thode de corrĂ©lation des images numĂ©riques (DIC) pour permettre des mesures tridimensionnelles des dĂ©formations Ă diffĂ©rentes tempĂ©ratures, et a Ă©tĂ© nommĂ©e le technique confocale-DIC. Cette technique a dâabord Ă©tĂ© validĂ©e par une analyse thĂ©orique en dĂ©formation thermique. Dans un Ă©chantillon similaire Ă un flip-chip, la distribution de la dĂ©formation obtenues par le modĂšle EF Ă©tait en bon accord avec les rĂ©sultats de la technique confocal-DIC, avec des erreurs relatives infĂ©rieures Ă 20% au coin de puce. Ensuite, le second objectif est de mesurer la dĂ©formation autour dâune fissure dans lâunderfill. Des fissures artificielles dâune longueuer de 160 ÎŒm et 640 ÎŒm ont Ă©tĂ© fabriquĂ©es dans lâunderfill vers la direction diagonale de 45°. Les dĂ©formations circonfĂ©rentielles maximales et principale maximale Ă©taient situĂ©es aux pointes des fissures correspondantes. Un modĂšle de fissure a Ă©tĂ© dĂ©veloppĂ© en utilisant la mĂ©thode des Ă©lĂ©ments finis Ă©tendue (XFEM), et la distribution des contraintes dans la simuation a montrĂ© la mĂȘme tendance que les rĂ©sultats expĂ©rimentaux. La distribution des dĂ©formations circonfĂ©rentielles maximales Ă©tait en bon accord avec les valeurs mesurĂ©es lorsque la taille des Ă©lĂ©ments Ă©tait plus petite que 22 ÎŒm, assez petit pour capturer le grand gradient de dĂ©formation prĂšs de la pointe de fissure. Le troisiĂšme objectif Ă©tait dâapporter une approche de modĂ©lisation de la dĂ©lamination et de la fissuration de lâunderfill avec les effets des variables de fabrication. Un test de cyclage thermique a dâabord Ă©tĂ© effectuĂ© sur 13 cellules pour obtenir les zones dĂ©laminĂ©es entre la puce et lâunderfill, et les profils de fissures dans lâunderfill, comme rĂ©fĂ©rence. Un rĂ©seau neuronal artificiel (ANN) a Ă©tĂ© formĂ© pour Ă©tablir une liaison entre les effets des variables de fabrication et le nombre de cycles Ă la dĂ©lamination pour chaque cellule. Les nombres de cycles prĂ©dits pour les 6 cellules de lâensemble de test Ă©taient situĂ©s dans les intervalles dâobservations expĂ©rimentaux. La croissance de la dĂ©lamination a Ă©tĂ© rĂ©alisĂ©e par lâEF en Ă©valuant lâĂ©nergie de la dĂ©formation au niveau des Ă©lĂ©ments interfaciaux entre la puce et lâunderfill. Pour 5 des 6 cellules de la validation, le modĂšle de croissance du dĂ©laminage Ă©tait conforme aux observations expĂ©rimentales. Les fissures dans lâunderfill ont Ă©tĂ© modĂ©lisĂ©es par XFEM sans chemins prĂ©dĂ©finis. Les directions des fissures de bord Ă©taient en bon accord avec les observations expĂ©rimentales, avec une erreur infĂ©rieure Ă 2,5°. Cette approche a rĂ©pondu Ă la problĂ©matique qui consiste Ă estimer lâinitiation des dĂ©lamination, les zones de dĂ©lamination et les trajectoires de fissures dans lâunderfill pour des flip-chips industriels
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Mixture Models in Machine Learning
Modeling with mixtures is a powerful method in the statistical toolkit that can be used for representing the presence of sub-populations within an overall population. In many applications ranging from financial models to genetics, a mixture model is used to fit the data. The primary difficulty in learning mixture models is that the observed data set does not identify the sub-population to which an individual observation belongs. Despite being studied for more than a century, the theoretical guarantees of mixture models remain unknown for several important settings.
In this thesis, we look at three groups of problems. The first part is aimed at estimating the parameters of a mixture of simple distributions. We ask the following question: How many samples are necessary and sufficient to learn the latent parameters? We propose several approaches for this problem that include complex analytic tools to connect statistical distances between pairs of mixtures with the characteristic function. We show sufficient sample complexity guarantees for mixtures of popular distributions (including Gaussian, Poisson and Geometric). For many distributions, our results provide the first sample complexity guarantees for parameter estimation in the corresponding mixture. Using these techniques, we also provide improved lower bounds on the Total Variation distance between Gaussian mixtures with two components and demonstrate new results in some sequence reconstruction problems.
In the second part, we study Mixtures of Sparse Linear Regressions where the goal is to learn the best set of linear relationships between the scalar responses (i.e., labels) and the explanatory variables (i.e., features). We focus on a scenario where a learner is able to choose the features to get the labels. To tackle the high dimensionality of data, we further assume that the linear maps are also sparse , i.e., have only few prominent features among many. For this setting, we devise algorithms with sub-linear (as a function of the dimension) sample complexity guarantees that are also robust to noise.
In the final part, we study Mixtures of Sparse Linear Classifiers in the same setting as above. Given a set of features and the binary labels, the objective of this task is to find a set of hyperplanes in the space of features such that for any (feature, label) pair, there exists a hyperplane in the set that justifies the mapping. We devise efficient algorithms with sub-linear sample complexity guarantees for learning the unknown hyperplanes under similar sparsity assumptions as above. To that end, we propose several novel techniques that include tensor decomposition methods and combinatorial designs
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MODELING CHAIN PACKING IN COMPLEX PHASES OF SELF-ASSEMBLED BLOCK COPOLYMERS
Block copolymer (BCP) melts undergo microphase seperation and form ordered soft matter crystals with varying domain shapes and symmetries. We study the con- nection between diblock copolymer molecular designs and thermodynamic selection of ordered crystals by modeling features of variable sub-domain geometry filled with individual blocks within non-canonical sphere-like and network phases that together with layered, cylindrical and canonical spherical phases forms ânatural formsâ of self- assembled amphiphilic soft matter at large. First, we present a model to revise our understanding of optimal Frank-Kasper sphere-like morphologies by advancing the- ory to account for varying domain volumes. We then develop generic approaches to quantify local changes to domain thickness or packing frustration using medial sets and show its application to morphologies with arbitrary domain topologies and sym- metries in both theoretical models and experimental data. We further use medial sets as a proxy for terminal boundaries of blocks within different domains and revise thermodynamic models of BCP assembly in the strong segregation limit. Finally, we use this revised model to study effect of elastic stiffness asymmetry on relaxing packing frustration experienced by BCPs in tubular and matrix domains leading to equilibrium double gyroid network morphology in diblock copolymers
Product Lotteries and Loss Aversion
Product lotteries are a sales strategy where companies hide features of differentiated products from consumers until the purchase is complete. I identify loss aversion as an important factor explaining the existence of vertical product lotteries. I consider a profit-maximizing monopolist serving loss-averse consumers with rational expectations about the lottery. I find that the optimal strategy consists of offering a premium product with high and deterministic quality and a lottery with stochastic and lower expected quality. When consumers are reasonably loss averse, I show that the profit increase from adding a quality lottery exceeds 10% compared to the case without a lottery
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