This thesis develops a methodology for the construction of generalized families of probability distributions in the quantile statistical universe, that is, distributions specified in terms of their quantile functions. The main benefit of the proposed methodology is that it generates quantile-based distributions with skewness-invariant measures of kurtosis. The skewness and kurtosis can therefore be identified and analyzed separately. The key contribution of this thesis is the development of a new type of the generalized lambda distribution (GLD), using the quantile function of the generalized Pareto distribution as the basic building block (in the literature each different type of the GLD is incorrectly referred to as a parameterization of the GLD – in this thesis the term type is used). The parameters of this new type can, contrary to existing types, easily be estimated with method of L-moments estimation, since closed-form expressions are available for the estimators as well as for their asymptotic standard errors. The parameter space and the shape properties of the new type are discussed in detail, including its characterization through L-moments. A simple estimation algorithm is presented and utilization of the new type in terms of data fitting and approximation of probability distributions is illustrated. / Thesis (PhD)--University of Pretoria, 2013. / gm2014 / Statistics / unrestricted

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2019 / The proliferation of data from sources like social media, and sensor devices has become overwhelming for traditional data storage and analysis technologies to handle. This has prompted a radical improvement in data management techniques, tools and technologies to meet the increasing demand for effective collection, storage and curation of large data set. Most of the technologies are open-source. Big data is usually described as very large dataset. However, a major feature of big data is its velocity. Data flow in as continuous stream and require to be actioned in real-time to enable meaningful, relevant value. Although there is an explosion of technologies to handle big data, they are usually targeted at processing large dataset (historic) and real-time big data independently. Thus, the need for a unified framework to handle high volume dataset and real-time big data. This resulted in the development of models such as the Lambda architecture. Effective decision-making requires processing of historic data as well as real-time data. Some decision-making involves complex processes, depending on the likelihood of events. To handle uncertainty, probabilistic systems were designed. Probabilistic systems use probabilistic models developed with probability theories such as hidden Markov models with inference algorithms to process data and produce probabilistic scores. However, development of these models requires extensive knowledge of statistics and machine learning, making it an uphill task to model real-life circumstances. A new research area called probabilistic programming has been introduced to alleviate this bottleneck. This research proposes the combination of modern open-source big data technologies with probabilistic programming and Lambda architecture on easy-to-get hardware to develop a highly fault-tolerant, and scalable processing tool to process both historic and real-time big data in real-time; a common solution. This system will empower decision makers with the capacity to make better informed resolutions especially in the face of uncertainty. The outcome of this research will be a technology product, built and assessed using experimental evaluation methods. This research will utilize the Design Science Research (DSR) methodology as it describes guidelines for the effective and rigorous construction and evaluation of an artefact. Probabilistic programming in the big data domain is still at its infancy, however, the developed artefact demonstrated an important potential of probabilistic programming combined with Lambda architecture in the processing of big data.

In der vorliegenden Arbeit werden Methoden aus der Theorie der dynamischen Systeme verwendet, um das qualitative Verhalten von Lösungen der semiklassischen Einsteingleichung für Friedmann-Lamaître-Robertson-Walker Raumzeiten zu untersuchen. Es werden ausschließlich masselose und konform gekoppelte Quantenfelder betrachtet. Bei der Renormierung des Energie-Impuls-Tensors solcher Quantenfelder treten Ambiguitäten auf, die sich als freie Parameter in der semiklassischen Einsteingleichung manifestieren. Mit Hilfe der Theorie der dynamischen Systeme ist es möglich, Lösungen nach ihren qualitativen Verhalten zu klassifizieren und dadurch Argumente für oder gegen bestimmte Werte der Renormierungskonstanten herauszuarbeiten. Befindet sich das Quantenfeld im konformen Vakuumzustand, erhält man ein zweidimensionales dynamisches System. Für dieses dynamische System werden die strukturell stabilen Fälle und Bifurkationsdiagramme herausgearbeitet, sowie das globale Stabilitätsverhalten der Minkowski und De-Sitter Gleichgewichtspunkte. Mittels dieser Analyse wird das qualitative Verhalten der semiklassischenLösungen mit dem qualitativen Verhalten der Lösungen des Lambda-CDM Modells der Kosmologie verglichen. Es zeigt sich, dass das semiklassische Modell in der Lage ist das qualitative Verhalten von Lösungen des klassischen Lambda-CDM Modells wiederzugeben. Weiterhin wird gezeigt, das im Vakuumfall Lösungen existieren, welche sich, im Gegensatz zu Lösungen des klassischen Lambda-CDM Modells, im Allgemeinen nicht eindeutig durch ihre Anfangsdaten bestimmen lassen. Um dieses atypische Verhalten aufzulösen müssen die Trajektorien dieser Lösungen in einem dreidimensionalen Phasenraum betrachtet werden.Das entsprechende dreidimensionale dynamische System beschreibt das dynamische Verhalten der Lösungen für beliebige Quantenzustände. Für allgemeine Quantenzustände wird die lokale (Lyapunov-) Stabilität der Gleichgewichtspunkte untersucht und für eine spezielle Wahl der Renormierungskonstanten und des Quantenzustandes neue Lösungen gefunden und mit Lösungen des klassischen Lambda-CDM Modells verglichen. Auch hier besteht eine qualitative Äquivalenz.

Resistence population of pollen beattle on selected locations of Moravia and Silesia were observed during the 2017. Beattles were taked off in the field during spring and their sensitivity to insecticides active substances indoxacarb, chlorpyrifos, thiacloprid, tau-fluvalinate, cypermethrin and lambda-cyhalothrin were tested in laboratory. Tested using methods of IRAC – 11, 21, 25 and 27. Mortality of beattles at various concentrations of active substances was evaluated after 24 hours. Levels of resistance were changed for individual location.

Cloud computing is the current need and the futuristic strategy of many businesses. Economy and scalability are inevitable because they impact the flourishing of all online businesses. The objective of this study is to distinguish the differences between Amazon Lambda versus EKS and ECS using EC2 instances from the Economy and scalability perspectives. The study aims to give programmers without prior knowledge about the services an overall picture of their billing models, scalability,  and the goal each service is meant to deliver. A literature review was used to identify the related studies done earlier in this area of research. The data captured from the literature studies were enriched with an empirical study, namely, survey research  with semi-structured interviews. Snowballing was used to identify more interviewees with the help of the earlier selected respondents. After conducting the semi-structured online interviews with five participants, the recordings were transcribed. Finally, the Thematic Analysis approach was used to analyze the collected qualitative data from the transcripts. It was concluded that Lambda was useful for infrequent and minor workloads without long processing tasks, with a  free automatic and managed scalability. For websites doing massive processing or getting large requests constantly, EKS or ECS would be a better choice. However, ECS and EKS cost more than Lambda when working with smaller workloads. EKS has multi-direction scalability, making it more flexible than Lambda and ECS. However, this comes with additional costs and complexity, but it is cost-effective for bigger businesses. Ultimately, in real-world cloud architecture, it is relatively common to rely on a combination of cloud services to fulfill the economic or auto scalability objectives of a business instead of a single one.

Datahantering är en aspekt av systemlösningar som inte ska försummas. Svarstider är en lika viktig aspekt i den moderna onlinetjänsten. När molntjänster har nått en popularitet högre än någonsin är det viktigt att veta hur man använder dem effektivt för att kunna få bästa resultat. Kunden, Axis Communications, utvecklar för närvarande en IoT-plattform (Internet of Things) som tros leverera ytterligare mjukvarufunktionalitet och information i realtid till slutanvändaren. Ett moment i denna tjänst är händelsehantering och behandling. Detta kräver att händelser tas emot och bearbetas med hjälp av AWS-komponenter innan de skickas vidare. I denna rapport har vi jämfört prestandan mellan att berika en händelseström med information via externa tjänster och att berika samma händelseström via lokala tjänster. För att bestämma vilka lösningar som ger en snabbare responstid för vår klient, Axis Communications, har vi utvecklat en ny prototyp. Utvecklingsprocessen som vi har valt gör det möjligt att iterera och utvärdera prototypen under utvecklingsprocessen. Utvärderingen bör endast användas som riktlinje vid bedömning av händelsehanteringstjänster, eftersom antalet parametrar kan skilja sig och ge ändrade resultat. Resultaten visar att vår metod för denna lösningen presterade upp till 5,16 gånger bättre än den externa tjänsten. Molntjänsten presterade även bättre under hög belastning tack vare skalbarheten hos AWS Lambda. / Data processing is an aspect of system solutions which cannot be neglected. Response times is an equally important aspect in the modern online service. With cloud services reaching an all-time peak in popularity, it is important to know how to use them efficiently by providing the best results. The client, Axis Communications, is currently developing an IoT (Internet of Things) platform which is thought to deliver further software functionality and information in real-time to the end user. One of the elements of this service is event handling and processing. It requires events to be received and processed using AWS components before sending them through. In this thesis we aim to compare the performance between decorating an event stream using external services to decorating the same event stream with local services. In order to determine which of the solutions offer a better result for our client, we had to develop a new prototype of said solution. The process of development makes it possible to iterate and evaluate the prototype during the time of development. The evaluation should only be used as a guideline when considering event handling services as the number of parameters may differ and yield altered results. The results prove that our method for this solution had up to 5,16 times faster response time. The cloud-based solution also performed better when under heavy load by processing all of the requests simoultanously due to the scaling of AWS Lambda.

This thesis was compiled during the solution of the project MA NAZV QJ1230077 and it is focuses on monitoring of pollen beetle (Brassicogethes aeneus, Fab., 1775) populations resistence to selected insecticides, in particular lambda-cyhalotrin, cypermetrin, tau-fluvalinate, Biscaya 240 OD and chlorpyrifos-ethyl in South Moravia. Beetles were collected during the spring 2016. Their sensitivity to these insecticides active ingredients was tested in laboratory. Various concentrations of active substances and beetles´ mortality after 24 hours was evaluated according to methodology IRAC (adult-vial-test met. 11, 21, 25, www.irac-online.org). Beetles´ sensitivity depends on the dose of the active substance and the location where the beetles were taken from.

Two major applications of lambda calculi in computer science are functional programming languages and mechanized reasoning systems (or, proof assistants). According to the Curry--Howard correspondence, it is possible, in principle, to design a unified language based on a typed lambda calculus for both logical reasoning and programming. However, the different requirements of programming languages and reasoning systems make it difficult to design such a unified language that provides both. Programming languages usually extend lambda calculi with programming-friendly features (e.g., recursive datatypes, general recursion) for supporting the flexibility to model various computations, while sacrificing logical consistency. Logical reasoning systems usually extend lambda calculi with logic-friendly features (e.g., induction principles, dependent types) for paradox-free inference over fine-grained properties, while being more restrictive in modeling computations. In this dissertation, we design and implement a language called Nax that embraces benefits of both. Nax accepts all recursive datatypes, thus, allowing the same flexibility of defining recursive datatypes as in functional languages. Nax supports a number of Mendler-style recursion schemes that can express various kinds of recursive computations and also guarantee termination. Nax supports term-indexed types to support specifications of fine-grained properties. In addition, Nax supports a conservative extension of Hindley--Milner type inference. The theoretical contributions of this dissertation include theories for Mendler-style recursion schemes and term-indexed types, which we developed to establish strong normalization and logical consistency of Nax.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第18095号 / 理博第3973号 / 新制||理||1573(附属図書館) / 30953 / 京都大学大学院理学研究科化学専攻 / (主査)教授 三木 邦夫, 教授 杉山 弘, 教授 秋山 芳展 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

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