Purpose of this work is show possibility of using grapichs cart for imaging a video signal. This work is particularly focused on technology CUDA and OpenCL. The solution is first focused on graphics cart and show how has been changed components and how has been changed performaces of graphics cart. Then show CUDA and OpenCL technology itself, and show samples of codes with explain, what which code do. Output of this work is some programs, witch defined for both technology and for both procesors unit. Contribution of this work is show differents between procesors unit, witch can be used to right choose for design your own algorithm.

Samhället blir allt mer digitaliserat för var dag som går och med denna utveckling har e-handeln under de senaste decennierna kontinuerligt vuxit sig större.   I den växande e-handeln existerar det dock ett problem som leder till stora monetära förluster för aktörer i detaljhandeln. Enligt aktuell statistik överger över två tredjedelar av alla kunder i e-handeln sina fyllda varukorgar utan att avsluta sina köp. Anledningarna bakom detta pekar i vissa fall på känslor som uppstår hos användare på grund av hur webbutiker är uppbyggda och fungerar.   Denna studie har med bakomliggande problemområde som anledning därför undersökt hur design skulle kunna tillämpas för att öka slutförandet av köp i webbutiker.   För att besvara denna fråga har en kvalitativ undersökning gjorts där intervjuer konstruerade efter tidigare forskning inom området och forskningsfrågan utfördes med personer som frekvent använder webbutiker och som även vid något tillfälle har lagt produkter i sin varukorg för att sedan lämna webbutiken utan att slutföra sitt köp.   Resultaten från dessa intervjuer och den efterföljande analysen hittade de två användningsområdena ”Navigationssystem” och ”Kassa och varukorg” och tillhörande designriktlinjer som ska tillämpas i användningsområdena för att öka slutförandet av köp i webbutiker. Slutligen gestaltades även designförslag för att visualisera dessa användningsområden och designriktlinjer. / Society is becoming increasingly more digitized and with this development e-commerce has seen continuous growth these past decades.   Within the growing e-commerce there is a however a big problem that has led to and continues to lead to significant monetary losses. According to current statistics over two thirds of customers online abandon their shopping carts without completing their purchases. In some cases, the reasons for this points to different emotions felt by customers which are created by how webshops are built and how they work.   Due to this problem this study has researched how one could apply design to increase the completion of purchases in online stores.   To answer this question a qualitative study was carried out in which interviews based on the research question and previous relevent research were conducted with people who frequently use online stores and who at some point have abandoned their shopping cart without completing their purchase.   The result of these interviews and the subsequent analysis was the finding of the two areas ”Navigation system” and ”Checkout and shopping cart” in which design can be used to increase the completion of purchases and design guidelines that are to be applied when designing these areas with the purpose of reducing shopping cart abandonment.    Lastly, design mockups where created to visualize these areas with the design guidelines applied.

La presente investigación hace mención al análisis en laboratorio con respecto a la colocación de asfalto a una temperatura menor a seis grados centígrados, teniendo en consideración que el Perú cuenta con diferentes tipos de climas a lo largo y ancho de su territorio, esto hace que la producción de asfalto y su colocación sea una dificultad para cualquier tipo de proyecto de carreteras, la cual nos dirige a una realidad en la producción de asfalto en caliente, ya que sabiendo las normas y manuales con las que actualmente contamos hace que la colocación sea imposible a una temperatura menor a seis grados centígrados. La investigación se focaliza en un análisis cualitativo – cuantitativo la cual debe cumplir con los parámetros de calidad (Ensayos), manual de carreteras (EG - 2013) y proceso constructivo (método Marshall) la realización de la propuesta de mezcla asfáltica va a variar en el porcentaje de diferentes tipos de filler que hemos considerado para la investigación (cal, cemento portland tipo I y sílice). Para los ensayos se realizaron probetas sin ningún tipo de aditivos, las probetas una vez preparadas a 140ºC se sometieron a congelamiento dando como resultado, de los tres tipos de filler, que la mezcla asfáltica en caliente con incorporación de cemento portland tipo I a un 5,90% de cemento asfáltico es el óptimo cumpliendo con los parámetros y especificaciones técnicas del manual de carreteras. / The present investigation mentions the laboratory analysis regarding the placement of asphalt at a temperature below six degrees centigrade, taking into account that Peru has different types of climates throughout its territory, this makes the asphalt production and its placement is a difficulty for any type of road project, which leads us to a reality in the production of hot asphalt, since knowing the standards we currently have, that makes placement impossible to a temperature below six degrees centigrade. The research is focused on a qualitative - quantitative analysis which must comply with the quality parameters (Tests), road manual (EG - 2013) and constructive process (Marshall method) the realization of the asphalt mix proposal will vary in the percentage of different types of filler that we have considered for the research (lime, portland cement type I and silica). For the tests, test tubes were carried out without any type of additives, once the test tubes were prepared at 140ºC, they were subjected to freezing, resulting, of the three types of filler, that the hot asphalt mix with incorporation of portland cement type I at a 5,90% asphalt cement is the optimal one complying with the parameters and technical specifications of the road manual. / Tesis

Given the rising demand for diverse cell types in regenerative and transfusion medicines, such as human induced pluripotent stem cell-derived neurons (iPSC-Ns), human T/chimeric antigen receptor (CAR) T cells, and human natural killer (NK) cells, the ability to cryopreserve cells has become increasingly important. In regenerative medicine, iPSC-Ns are powerful tools for treating and modelling neurodegenerative diseases. Moreover, transplants/transfusions of T/CAR T cells or NK cells offer promising treatment for numerous types of tumors, such as leukemia and multiple myeloma. Cryopreservation of cells at sub-zero temperatures (-80 to -196 °C) allows for the development of master cell banks that can be used for clinical applications. Conventional cryoprotective agents (CPAs), such as dimethylsulfoxide (DMSO) and glycerol, are utilized to protect cells from cryoinjuries associated with the freezing process. However, the use of high concentrations of DMSO (i.e., 10 to 20%) has been shown to be accompanied with toxic effects on patients receiving cell therapies if it is not removed or diluted prior to transfusion. Moreover, DMSO does not prevent the occurrence of the cryoinjury associated with ice recrystallization, which is one of the major causes of cell death/damage during cryopreservation. As a result, there is a surge of attention toward developing new non-toxic cryo-additives that inhibit ice recrystallization during cryopreservation to permit future advancement in regenerative and transfusion medicines. Moreover, the use of ice recrystallization inhibitors (IRIs) as novel CPAs has become a promising strategy to improve cell viability and function post-thaw. The Ben laboratory heavily invested in synthesizing several classes of carbohydrate-based small molecule IRIs (i.e., O-linked alkyl and aryl glycosides, and N-aryl-D-gluconamides), and studying the correlation between their IRI activity and molecular properties, such as polar surface area to molecular surface area (PSA/MSA) ratio. Moreover, compounds that belong to the O-linked aryl glycosides and N-aryl-D-gluconamides classes of IRIs have been shown to enhance the viability and functionality of red blood cells (RBCs), hematopoietic stem cells (HSCs), and induced pluripotent stem cells (iPSCs) after thawing. Part of the research presented throughout this thesis focuses on structure-activity relationship (SAR) studies of alkyl pyranoses with modified alkyl chain lengths to explore any correlations between the IRI activity and the net polarity (i.e., PSA/MSA ratio) of the IRI candidates. O- and C-linked alkyl pyranose derivatives with different alkyl chain lengths were synthesized and their IRI activity was assessed using the modified splat cooling assay. While the IRI activity of the O- and C-linked alkyl glucosides did differ as the length of the alkyl chain increased, no correlation between the PSA/MSA ratios and their IRI activity was observed. In addition, this work allowed for investigation into the effect of the type of the glycosidic bond (i.e., C-O and C-C bonds) at the anomeric position, on the IRI activity of the different compounds. The O-linked alkyl glucosides appeared to be more IRI active than the C-linked compounds, suggesting the nature of the glycosidic bond is important for IRI activity. The second part of the research presented in this thesis focuses on examining the potential for IRIs to cryopreserve iPSC-Ns, T/CAR T cells, and NK cells. 2-fluorophenyl-D-gluconamides (2FA), which is one of the most active IRIs from the N-aryl-Dgluconamides, has shown promising results in maintaining a high number of viable and functional HSCs and iPSCs post-thaw, and therefore it was employed in the cryopreservation protocol of iPSC-Ns, human-derived T/CAR T cells, and human-derived NK cells. The efficacy of the cryopreservation protocol being constructed was evaluated by assessing the post-thaw viability and recovery rate, as well as the functionality of iPSCNs, T/CAR T cells, and NK cells post-thaw. These studies showed that protecting against ice recrystallization during cryopreservation with IRIs increases the number of viable and functional iPSC-Ns, and T/CAR T cells. It was also observed that employing IRI technology in the cryopreservation protocol of NK cells does not compromise their functionality compared to fresh, non-frozen NK cells. Overall, inhibition of ice recrystallization using IRIs appeared to enhance the cryopreservation outcomes of the different cell types, which will allow for the development of off-the-shelf cell therapy products and improvement of the delivery of efficacious cell products to clinics and hospitals.

Unemployment at young age is a negative life event that has been found to have scarring effects for future life outcomes, especially when continuing long-term. Understanding precursors for long-term unemployment in early adulthood is important to be able to target policy interventions in critical junctures in the life course. Paths to unemployment are complex and a comprehensive outlook on the most important factors and mechanisms is difficult to obtain. This study proposes a data-driven, exploratory approach for studying individual and family level factors during ages 0-24, that predict long-term unemployment at the age of 25-30. A supervised machine learning approach was applied to understand associations deriving from longitudinal, individual-level administrative data from a full birth cohort in Finland. The data comprise information about physical and social wellbeing, life course events, as well as demographics, including the parents of the cohort members. Potential predictors were chosen from the data based on theories and previous research, and used to train a model aiming to correctly classify unemployed individuals. A CART algorithm was used to build a classification tree that reveals important variables, ranges of them as well as combinations of factors that together are predictive of long-term unemployment. A random forest algorithm was used to build several trees producing smoothed predictions that reduce overfitting of one tree. CARTs and random forest models were compared to each other to understand how they perform in a research task predicting life outcomes. Both individual and family level factors were found to be predictive of the outcome. Combinations of variables such as GPA lower than ~7.5, ego’s low education level, late work history start, depressive disorders and low parental education and income levels were found to be particularly predictive of unemployment. CART models correctly classified up to 87% of the unemployed, while misclassifying 70% of the employed and having 45% overall accuracy. Testing for CART model stability, finding consistency across several tree models improved robustness. Random forest correctly predicted up to 59% of the unemployed, while also correctly classifying 65% of the employed and producing robust results. The two algorithms together provided valuable insight for better understanding factors contributing to unemployment. The study shows promise for classification tree based methods in studying life course and life outcomes.

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Die Weltgesundheitsorganisation WHO schätzte die Zahl der an Malaria erkrankten Menschen im Jahr 2009 auf weltweit 225 Millionen. Auf dem afrikanischen Kontinent betrafen 85% der durch Malaria verursachten Todesfälle Kinder unter fünf Jahren. Obwohl die Inzidenzen der P. falciparum-Malaria in einigen Teilen des subsaharischen Afrika sinken und andere Erkrankungen mit ähnlichen Symptomen wie denen der Malaria an Bedeutung gewinnen, ist eine vorsorgliche medikamentöse Behandlung im Verdachtsfall weiterhin üblich. Ziel dieser Arbeit ist die Generierung eines auf das Lebensalter bezogenen klinischen Algorithmus, der mit einfachen klinischen Symptomen die Diagnose einer P. falciparum - Parasitämie ermöglicht. Die Studie wurde in einem ländlichen Krankenhaus in der Ashanti-Region in Ghana durchgeführt, welche über das ganze Jahr hinweg holoendemisch für Malaria ist. Insgesamt wurden 5447 ambulante Besuche von 3641 Patienten im Alter zwischen 2-60 Monaten analysiert. Alle Kinder wurden von einem Pädiater klinisch untersucht und es wurden ein kleines Blutbild sowie ein Malariaausstrich (‘Dicker Tropfen’) angefertigt. Mit Hilfe einesClassification and Regression Tree (CART) wurde ein klinischer Entscheidungsbaum für die Prädiktion einer Plasmodium-Parasitämie generiert und prädiktive Werte für alle erfassten Symptome berechnet. Eine Parasitämie wurde bei Kindern im Alter von 2-12 Monaten mit einer Prävalenz von 13.8% und bei Kindern im Alter zwischen 12 und 60 Monatenmit einer Prävalenz von 30.6% gefunden. Das CART-Modell ergab altersabhängige Unterschiede in der Fähigkeit der Variablen eine Parasitämie vorherzusagen. Während sich bei Kindern im Alter zwischen 2 und 12 Monaten die „palmare Blässe“ als das wichtigste Symptom herausstellte, gewannen die Variablen „Fieber in der Anamnese“ und „erhöhte Körpertemperatur ≥ 37.5°C“ bei Kindern im Alter zwischen 12 und 60 Monaten an Bedeutung. Die Variable „palmare Blässe“ war bei Kindern jedes Alters signifikant (p<0.001) mit niedrigeren Hämoglobinwerten assoziiert. Im Vergleich zum Algorithmus des Integrated Management of Childhood Illness (IMCI) hatte das CART-Modell eine deutlich höhere Spezifität sowie einen höheren positiven prädiktiven Wert für die Vorhersage einer Parasitämie. Die Anwendung von altersbezogenen Algorithmen erhöht die Spezifität der Vorhersage einer P. falciparum - Parasitämie. Selbst in einer Population mit einer hohen Prävalenz an Anämie ermöglicht der prädiktive Wert der „palmaren Blässe“ eine Erkennung von signifikant geringeren Hb-Werten. Die Bedeutung der „palmaren Blässe“ sollte daher in der Schulung von Gesundheitshelfern hervorgehoben werden. Mangels ausreichender Sensitivität kann allerdings weder auf Basis des besten Algorithmus noch mit „palmarer Blässe“ als einzelnem klinischem Zeichen eine Therapieentscheidung getroffen werden. Sie sind daher kein Ersatz für eine vorsorgliche medikamentöse Behandlung und einen Erregernachweis.

Cette étude vise à mettre en lumière les différences et similarités existant entre les principales crises économiques et financières ayant frappé un échantillon de 21 pays avancés depuis 1981. Nous analyserons plus particulièrement la crise des subprimes que nous rapprocherons avec des épisodes antérieurs. Nous étudierons à la fois les années du déclenchement des turbulences (analyse typologique) ainsi que celles les précédant (prévision). Cette analyse sera fondée sur l’utilisation de la méthode CART (Classification And Regression Trees). Cette technique non linéaire et non paramétrique permet de prendre en compte les effets de seuil et les interactions entre variables explicatives de façon à révéler plusieurs contextes distincts explicatifs d’un même événement. Dans le cadre d‘un modèle de prévision, l’analyse des années précédant les crises nous indique que les variables à surveiller sont : la variation et la volatilité du cours de l’once d’or, le déficit du compte courant en pourcentage du PIB et la variation de l’openness ratio et enfin la variation et la volatilité du taux de change. Dans le cadre de l’analyse typologique, l’étude des différentes variétés de crise (année du déclenchement de la crise) nous permettra d’identifier deux principaux types de turbulence d’un point de vue empirique. En premier lieu, nous retiendrons les crises globales caractérisées par un fort ralentissement ou une baisse de l’activité aux Etats-Unis et une faible croissance du PIB dans les pays touchés. D’autre part, nous mettrons en évidence des crises idiosyncratiques propres à un pays donné et caractérisées par une inflation et une volatilité du taux de change élevées. / The aim of this thesis is to analyze, from an empirical point of view, both the different varieties of economic and financial crises (typological analysis) and the context’s characteristics, which could be associated with a likely occurrence of such events. Consequently, we analyze both: years seeing a crisis occurring and years preceding such events (leading contexts analysis, forecasting). This study contributes to the empirical literature by focusing exclusively on the crises in advanced economies over the last 30 years, by considering several theoretical types of crises and by taking into account a large number of both economic and financial explanatory variables. As part of this research, we also analyze stylized facts related to the 2007/2008 subprimes turmoil and our ability to foresee crises from an epistemological perspective. Our empirical results are based on the use of binary classification trees through CART (Classification And Regression Trees) methodology. This nonparametric and nonlinear statistical technique allows us to manage large data set and is suitable to identify threshold effects and complex interactions among variables. Furthermore, this methodology leads to characterize crises (or context preceding a crisis) by several distinct sets of independent variables. Thus, we identify as leading indicators of economic and financial crises: variation and volatility of both gold prices and nominal exchange rates, as well as current account balance (as % of GDP) and change in openness ratio. Regarding the typological analysis, we figure out two main different empirical varieties of crises. First, we highlight « global type » crises characterized by a slowdown in US economic activity (stressing the role and influence of the USA in global economic conditions) and low GDP growth in the countries affected by the turmoil. Second, we find that country-specific high level of both inflation and exchange rates volatility could be considered as evidence of « idiosyncratic type » crises.

在我國正式加入WTO後，汽車產業面臨嚴重競爭，且相較於其他國家，台灣的汽車市場趨近於飽和現象，在供過於求情況下，製造與裝配過程附加價值低，附加價值存在於隨品牌所提供的產品服務。藉由商業智慧系統之建立，透過資料採礦、預測的功能，將不同消費習慣的客戶進行分類，達到準確的目標行銷。 　　本研究採用「決策樹C5.0」、「CART迴歸樹」與「羅吉斯迴歸」等方法建立模型於新車滿意度資料庫、車主購買滿意度資料庫及車主維修滿意度資料庫之資料。從三大資料庫中找出既有顧客群裡，較有可能會再次購買同品牌汽車的顧客特性，進一步整合行銷策略，提升顧客再次購買的機會。根據不同資料庫，本研究目的如下： 一、 分析於新車滿意度資料庫之資料，此資料包含2005年購買新車之車主資料，主要是建立客戶類型區隔模型及再購模型。 二、 分析於車主購買滿意度資料庫之資料，分別建立顧客是否會再次購買以及是否會向親朋好友推薦該品牌之模型。 三、 分析於車主維修滿意度資料庫之資料，分別建立顧客是否會再次購買、是否會推薦親朋好友以及是否會再次回廠維修之模型。

The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation models that has received increased attention in recent years is the calibration of these models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation models. The research develops a methodology to model CMVs using microscopic traffic simulation models and then utilizes the output of these models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.