Discrete-event Simulation and Optimization to Improve the Performance of a Healthcare System

Thesis (Ph.D.)--University of Washington, 2016-08

Evaluation of the JOSTLE mesh partitioning code for practical multiphysics applications

The use of unstructured mesh codes on parallel machines is one of the most effective ways to solve large computational mechanics problems. Completely general geometries and complex behaviour can be modelled and, in principle, the inherent sparsity of many such problems can be exploited to obtain excellent parallel efficiencies. However, unlike their structured counterparts, the problem of distributing the mesh across the memory of the machine, whilst minimising the amount of interprocessor communication, must be carefully addressed. This process is an overhead that is not incurred by a serial code, but is shown to rapidly computable at turn time and tailored for the machine being used.

Datasets, features, learning, and models in visual recognition

Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate different recognition algorithms, this dissertation develops an approach to collect object image datasets on web pages using an analysis of text around the image and of image appearance. This method exploits established online knowledge resources (Wikipedia pages for text; Flickr and Caltech data sets for images). The resources provide rich text and object appearance information. This dissertation describes results on two datasets. The first is Berg’s collection of 10 animal categories; on this dataset, we significantly outperform previous approaches. On an additional set of 5 categories, experimental results show the effectiveness of the method. Images are represented as features for visual recognition. This dissertation introduces a text-based image feature and demonstrates that it consistently improves performance on hard object classification problems. The feature is built using an auxiliary dataset of images annotated with tags, downloaded from the Internet. Image tags are noisy. The method obtains the text features of an unannotated image from the tags of its k-nearest neighbors in this auxiliary collection. A visual classifier presented with an object viewed under novel circumstances (say, a new viewing direction) must rely on its visual examples. This text feature may not change, because the auxiliary dataset likely contains a similar picture. While the tags associated with images are noisy, they are more stable when appearance changes. The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, computational cost becomes a bottleneck, especially when training sophisticated classifiers such as kernelized SVM. This dissertation proposes a fast training algorithm called Stochastic Intersection Kernel Machine (SIKMA). This proposed training method will be useful for many vision problems, as it can produce a kernel classifier that is more accurate than a linear classifier, and can be trained on tens of thousands of examples in two minutes. It processes training examples one by one in a sequence, so memory cost is no longer the bottleneck to process large scale datasets. This dissertation applies this approach to train classifiers of Flickr groups with many group training examples. The resulting Flickr group prediction scores can be used to measure image similarity between two images. Experimental results on the Corel dataset and a PASCAL VOC dataset show the learned Flickr features perform better on image matching, retrieval, and classification than conventional visual features. Visual models are usually trained to best separate positive and negative training examples. However, when recognizing a large number of object categories, there may not be enough training examples for most objects, due to the intrinsic long-tailed distribution of objects in the real world. This dissertation proposes an approach to use comparative object similarity. The key insight is that, given a set of object categories which are similar and a set of categories which are dissimilar, a good object model should respond more strongly to examples from similar categories than to examples from dissimilar categories. This dissertation develops a regularized kernel machine algorithm to use this category dependent similarity regularization. Experiments on hundreds of categories show that our method can make significant improvement for categories with few or even no positive examples.

Dopuszczalność i skutki potwierdzenia czynności dokonanej bez wymaganej przez umowę lub statut zgody organu spółki

W artykule autorzy podejmują się dokonania analizy zagadnienia dotyczącego możliwości naruszenia umowy spółki lub statutu przez członków zarządu oraz wpływu takiego naruszenia na ważność podjętej czynności prawnej. Zagadnienie to wywołuje liczne problemy praktyczne, chociażby z uwagi na obowiązek każdorazowej weryfikacji przed zawarciem umowy listy czynności, na dokonanie których statut lub umowa spółki zastrzega sobie taki wymóg. Nie ma tu znaczenia dobra czy zła wiara kontrahenta, który ma świadomość o istnieniu takiego zapisu dla ważności danej czynności prawnej. Zgoła odmienna jest sytuacja członka zarządu, dla którego uzyskanie takiej zgody jest ważne, z uwagi na naruszenia umowy spółki albo statutu, a w konsekwencji jego odpowiedzialność odszkodowawczą do dochodzenia ewentualnego odszkodowania za szkodę wyrządzoną działaniem lub zaniechaniem. Pamiętać jednak należy, że do istnienia odpowiedzialności niezbędne jest wykazanie szkody. Jednakże biorąc pod uwagę uwarunkowania biznesowe niekiedy trudno uzyskać zgodę rady nadzorczej lub walnego zgromadzenia wspólników na taką zgodę. Powstaje wtedy pytanie, czy można ją uzyskać następczo. Autorzy w artykule dokonują analizy stawiając tezę, iż możliwe jest następcze wyrażenie zgody na dokonaną bez uprzedniej zgody czynność prawną. Dokonując wnioskowania a maiori ad minus można w ocenie autorów dopuścić potwierdzenie takiej czynności następczo i to nie tylko w wymaganym dwumiesięcznym terminie, ale nawet późniejszym, co może mieć wpływ na ich ewentualne wyłączenie odpowiedzialności z tytułu naruszenia postanowień umowy spółki (statutu). Całość rozważań ściśle oscyluje wokół praktycznych problemów pojawiających się funkcjonowaniu spółki.

Phylogenetic inference's algorithms

Phylogenetic inference consist in the search of an evolutionary tree to explain the best way possible genealogical relationships of a set of species. Phylogenetic analysis has a large number of applications in areas such as biology, ecology, paleontology, etc. There are several criterias which has been defined in order to infer phylogenies, among which are the maximum parsimony and maximum likelihood. The first one tries to find the phylogenetic tree that minimizes the number of evolutionary steps needed to describe the evolutionary history among species, while the second tries to find the tree that has the highest probability of produce the observed data according to an evolutionary model. The search of a phylogenetic tree can be formulated as a multi-objective optimization problem, which aims to find trees which satisfy simultaneously (and as much as possible) both criteria of parsimony and likelihood. Due to the fact that these criteria are different there won't be a single optimal solution (a single tree), but a set of compromise solutions. The solutions of this set are called "Pareto Optimal". To find this solutions, evolutionary algorithms are being used with success nowadays.This algorithms are a family of techniques, which aren’t exact, inspired by the process of natural selection. They usually find great quality solutions in order to resolve convoluted optimization problems. The way this algorithms works is based on the handling of a set of trial solutions (trees in the phylogeny case) using operators, some of them exchanges information between solutions, simulating DNA crossing, and others apply aleatory modifications, simulating a mutation. The result of this algorithms is an approximation to the set of the “Pareto Optimal” which can be shown in a graph with in order that the expert in the problem (the biologist when we talk about inference) can choose the solution of the commitment which produces the higher interest. In the case of optimization multi-objective applied to phylogenetic inference, there is open source software tool, called MO-Phylogenetics, which is designed for the purpose of resolving inference problems with classic evolutionary algorithms and last generation algorithms. REFERENCES [1] C.A. Coello Coello, G.B. Lamont, D.A. van Veldhuizen. Evolutionary algorithms for solving multi-objective problems. Spring. Agosto 2007 [2] C. Zambrano-Vega, A.J. Nebro, J.F Aldana-Montes. MO-Phylogenetics: a phylogenetic inference software tool with multi-objective evolutionary metaheuristics. Methods in Ecology and Evolution. En prensa. Febrero 2016.

Equine exercise electrocardiogram : standardized lungeing test

Dissertação de Mestrado Integrado em Medicina Veterinária

Impacto da prevenção quaternária no envelhecimento bem sucedido

"Quaternary prevention is more than a Philosophy , it is a concrete answer and a solution to many complex problems that affect Medicine. In 1981, Illich recognized iatrogenic complications, as clinical, social and cultural. The first, gained such a dimension that has become the third leading cause of death in the U.S. , in 2000 as referred by Starfield. When you live more, much more, you want quality of life and not just life subject of increasing comorbidities, with all the parade of treatments, medications that we already know are not without riscs, far from it, we know that over five drugs per day represent the 50% probability of drug-drug interactions and seven drugs 100 %. In elderly attending the reduction of functional reserve, there is a greater risk of iatrogenic problems, adverse reactions and drug interactions, truly unpredictable , these highly medicalized societies in which are accounted diagnoses instead of investigating patterns of disease. So quaternary prevention reminds us that both preventive and curative care in excess behave as risk factors for health , reaching in the case of using preventive medications, millions of individuals who are confident in Medicine. The idea of extending the use of drugs to healthy populations, as preventive actions, expands the pharmaceutical market, which accounts simultaneously increasing profits and losses in economies around the world. Quaternary prevention itineraries in health and disease, may contribute to successful aging about witch many important authors have spoken on."

Distributed optimization in transportation and logistics networks

Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.

What to do when K-means clustering fails:a simple yet principled alternative algorithm

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism.

A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

Web-based application programming interface to solve nonlinear optimization problems

Nonlinear Optimization Problems are usual in many engineering fields. Due to its characteristics the objective function of some problems might not be differentiable or its derivatives have complex expressions. There are even cases where an analytical expression of the objective function might not be possible to determine either due to its complexity or its cost (monetary, computational, time, ...). In these cases Nonlinear Optimization methods must be used. An API, including several methods and algorithms to solve constrained and unconstrained optimization problems was implemented. This API can be accessed not only as traditionally, by installing it on the developer and/or user computer, but it can also be accessed remotely using Web Services. As long as there is a network connection to the server where the API is installed, applications always access to the latest API version. Also an Web-based application, using the proposed API, was developed. This application is to be used by users that do not want to integrate methods in applications, and simply want to have a tool to solve Nonlinear Optimization Problems.

Problems in the regulatory policy of the drug market

OBJECTIVE Analyze the implementation of drug price regulation policy by the Drug Market Regulation Chamber.METHODS This is an interview-based study, which was undertaken in 2012, using semi-structured questionnaires with social actors from the pharmaceutical market, the pharmaceuticals industry, consumers and the regulatory agency. In addition, drug prices were compiled based on surveys conducted in the state of Sao Paulo, at the point of sale, between February 2009 and May 2012.RESULTS The mean drug prices charged at the point of sale (pharmacies) were well below the maximum price to the consumer, compared with many drugs sold in Brazil. Between 2009 and 2012, 44 of the 129 prices, corresponding to 99 drugs listed in the database of compiled prices, showed a variation of more than 20.0% in the mean prices at the point of sale and the maximum price to the consumer. In addition, many laboratories have refused to apply the price adequacy coefficient in their sales to government agencies.CONCLUSIONS The regulation implemented by the pharmaceutical market regulator was unable to significantly control prices of marketed drugs, without succeeding to push them to levels lower than those determined by the pharmaceutical industry and failing, therefore, in its objective to promote pharmaceutical support for the public. It is necessary reconstruct the regulatory law to allow market prices to be reduced by the regulator as well as institutional strengthen this government body.

Measures in Sectorization Problems

Sectorization means dividing a whole into parts (sectors), a procedure that occurs in many contexts and applications, usually to achieve some goal or to facilitate an activity. The objective may be a better organization or simplification of a large problem into smaller sub-problems. Examples of applications are political districting and sales territory division. When designing/comparing sectors some characteristics such as contiguity, equilibrium and compactness are usually considered. This paper presents and describes new generic measures and proposes a new measure, desirability, connected with the idea of preference.

Heuristics and policies for online pickup and delivery problems

Master Thesis

Measurement Problems and Problem-Solving in Kraft Pulping

Tämän työn tarkoituksena on koota yhteen selluprosessin mittausongelmat ja mahdolliset mittaustekniikat ongelmien ratkaisemiseksi. Pääpaino on online-mittaustekniikoissa. Työ koostuu kolmesta osasta. Ensimmäinen osa on kirjallisuustyö, jossa esitellään nykyaikaisen selluprosessin perusmittaukset ja säätötarpeet. Mukana on koko kuitulinja puunkäsittelystä valkaisuun ja kemikaalikierto: haihduttamo, soodakattila, kaustistamo ja meesauuni. Toisessa osassa mittausongelmat ja mahdolliset mittaustekniikat on koottu yhteen ”tiekartaksi”. Tiedot on koottu vierailemalla kolmella suomalaisella sellutehtaalla ja haastattelemalla laitetekniikka- ja mittaustekniikka-asiantuntijoita. Prosessikemian paremmalle ymmärtämiselle näyttää haastattelun perusteella olevan tarvetta, minkä vuoksi konsentraatiomittaukset on valittu jatkotutkimuskohteeksi. Viimeisessä osassa esitellään mahdollisia mittaustekniikoita konsentraatiomittausten ratkaisemiseksi. Valitut tekniikat ovat lähi-infrapunatekniikka (NIR), fourier-muunnosinfrapunatekniikka (FTIR), online-kapillaarielektroforeesi (CE) ja laserindusoitu plasmaemissiospektroskopia (LIPS). Kaikkia tekniikoita voi käyttää online-kytkettyinä prosessikehitystyökaluina. Kehityskustannukset on arvioitu säätöön kytketylle online-laitteelle. Kehityskustannukset vaihtelevat nollasta miestyövuodesta FTIR-tekniikalle viiteen miestyövuoteen CE-laitteelle; kehityskustannukset riippuvat tekniikan kehitysasteesta ja valmiusasteesta tietyn ongelman ratkaisuun. Työn viimeisessä osassa arvioidaan myös yhden mittausongelman – pesuhäviömittauksen – ratkaisemisen teknis-taloudellista kannattavuutta. Ligniinipitoisuus kuvaisi nykyisiä mittauksia paremmin todellista pesuhäviötä. Nykyään mitataan joko natrium- tai COD-pesuhäviötä. Ligniinipitoisuutta voidaan mitata UV-absorptiotekniikalla. Myös CE-laitetta voitaisiin käyttää pesuhäviön mittauksessa ainakin prosessikehitysvaiheessa. Taloudellinen tarkastelu pohjautuu moniin yksinkertaistuksiin ja se ei sovellu suoraan investointipäätösten tueksi. Parempi mittaus- ja säätöjärjestelmä voisi vakauttaa pesemön ajoa. Investointi ajoa vakauttavaan järjestelmään on kannattavaa, jos todellinen ajotilanne on tarpeeksi kaukana kustannusminimistä tai jos pesurin ajo heilahtelee eli pesuhäviön keskihajonta on suuri. 50 000 € maksavalle mittaus- ja säätöjärjestelmälle saadaan alle 0,5 vuoden takaisinmaksuaika epävakaassa ajossa, jos COD-pesuhäviön vaihteluväli on 5,2 – 11,6 kg/odt asetusarvon ollessa 8,4 kg/odt. Laimennuskerroin vaihtelee tällöin välillä 1,7 – 3,6 m3/odt asetusarvon ollessa 2,5 m3/odt.