There is a great demand for fast deliveries of improved and updated software in different software development areas, like Internet of Things, web, and cloud, in today’s digitalized world. Software developers and organizations must adapt to be able to deliver according to customers’ wishes, to be able to retain them, and remain competitive with other organizations. Continuous integration and continuous delivery (CI/CD) are methods used within the software development world, allowing developers to automate parts of their work to develop and deliver software faster and with better quality. Tools used for CI/CD come with different benefits and performances making it difficult for developers to choose a tool. There are numerous tools to choose from, and there is a lack of performance comparisons of them. This thesis aims to give developers a performance comparison between the two well-known CI/CD tools, GitHub Actions and Jenkins, to facilitate their choice of a CI/CD tool. The research was qualitative, inductive, and comparative. A literature study and practical tests were conducted to study the performance differences between the two wellknown CI/CD tools, GitHub Actions and Jenkins. The literature study was conducted f irst and gave the necessary knowledge to perform the practical tests, and the practical tests gave the actual results. The practical tests were performed on two different software projects ,and two different tests per projec, per server were conducted. The results from both projects indicated apparent differences in performance between GitHub Actions and Jenkins, as Jenkins ran faster than GitHub Actions while running on a Windows server, and GitHub Actions ran faster than Jenkins while running on an Ubuntu server. These findings indicate that the two well-known CI/CD tools perform differently depending on the server the developers would use these tools. It can not be concluded that one of the tools has better performance than the other; instead, one tool has better performance depending on the operating system the tool is running on. If the developers were to use the tools on an Ubuntu server, GitHub Actions would be the preferred tool, and if they were to use the tool on a Windows server, Jenkins would be the preferred tool. / Det finns en stor efterfrågan på snabba leveranser av förbättrad och uppdaterad mjukvara i olika mjukvaruutvecklings områden så som Sakernas Internet, webb och moln i dagens digitaliserade värld. Mjukvaruutvecklare och organisationer måste anpassa sig för att kunna leverera till kundernas önskemål för att kunna behålla dom och förbli konkurrenskraftiga med andra organisationer. Kontinuerlig integration och kontinuerlig leverans (CI/CD) är metoder som används inom mjukvaruutvecklings världen, så att utvecklare kan automatisera delar av sitt arbete för att utveckla och leverera mjukvara snabbare och med bättre kvalité. Verktyg som används för CI/CD kommer med olika fördelar och prestanda som gör det svårt för utvecklare att välja ett verktyg. Det finns många verktyg att välja mellan och det finns en brist på prestandajämförelser av dem. Detta examensarbete syftar till att ge utvecklare en prestandajämförelse mellan de två välkända CI/CD-verktygen GitHub Actions och Jenkins, för att underlätta utvecklarens val av ett CI/CD-verktyg. En kvalitativ, induktiv och komparativ forskningsmetod användes för att genomföra denna studie. En litteraturstudie och praktiska tester genomfördes för att studera prestandaskillnader mellan de två välkända CI/CD-verktygen GitHub Actions och Jenkins. Litteraturstudien genomfördes först och gav författarna nödvändiga kunskap för att utföra dem praktiska testerna, dem praktiska testerna gav de faktiska resultaten. Praktiska testerna utfördes på två olika mjukvaruprojekt och två olika tester per projekt, en per server genomfördes. Resultaten från båda projekten visade på uppenbara skillnader i prestanda mellan GitHub Actions och Jenkins. Då Jenkins kördes snabbare än GitHub Actions när körningen kördes på en Windows server och GitHub Actions kördes snabbare än Jenkins när de kördes på en Ubuntu server. Dessa resultat tyder på att de två välkända CI/CD-verktygen fungerar olika beroende på vilken server utvecklarna skulle använda dessa verktyg på. Det går inte att dra slutsatsen att ett verktyg är bättre över det andra, i stället har ett verktyg bättre prestanda beroende på vilket operativ system verktyget körs på. Om utvecklarna skulle använda verktygen på en Ubuntu server skulle GitHub Actions vara det föredragna verktyget och om utvecklarna skulle använda verktyget på en Window server skulle Jenkins vara det föredragna verktyget.

This thesis aims to provide an approach to real estate residential modeling and forecasting covering property types’ correlation, time series attributes within a region or a city, and socio-economic attributes of preferred real estate locations. The thesis covers residential estate markets and concentrates on property types, while previous studies that have considered country wide house price indices. There is a gap identified in the literature in the need to study correlations between property types within a region or a city and whether they will provide diversification benefits for real estate investors such as risk reduction per unit of returns. The thesis concentrates on property type seasonality in addition to modeling time series attributes within a region or city instead of real estate index seasonality. This thesis the first to combine modern information systems techniques such as geographic information systems (GIS) with socio-economic factors to help understanding causal relationships that can be used to forecast real estate prices. The results show that it is more achievable to forecast real estate prices within a city than for the real estate market of the entire country. The GIS and socio-economic modeling results show that higher property prices are awarded to real estate with more green spaces, residents with higher disposable incomes, lower council tax bands, fewer tax benefits claimants, and better health services. Previous studies have examined real estate price indices at the macro level (the general, all real estate house price indices). There has not been a study that examines real estate price forecasts by property types within a city. The contribution of this thesis is its focus on time series analysis as well as causal modeling within a city with the objective of providing a better understanding of the dynamics of real estate price changes.

無論是投資人和債權人之投資與授信決策或企業內部之規劃與控制，在其決策模式中 ，會計盈餘常是一項重要因素。因此，檢查盈餘的時間數列特性不僅可瞭解盈餘產生 過程的統計特性，並且可據以預測未來的盈餘，本論文之目的即在研究我國上市公司 季盈餘時間數列特性，建立其時間數列模式。資料來源是利用台灣證券六易所上市公 司財務資料簡報，搜集整理民國六十五年第三季至民國七十七年第三季計４１家上市 公司之４９期季盈餘資料作為研究分析對象。利用BOX和JENKINS二人之時間數列分析 ，即所謂自我迴歸整合移動平均模式，替我國上市公司季盈餘建立時間數列模式。由 於資料搜集之限制，無法進一步作預測比較分析。有關BOX-JENKINS 分析之計算，則 利用教育部電子計算機中心所提供之套裝軟體SCA-UTS。 研究結果發現：所認定４１個個別B-J 模式中，以自我迴歸模式及混合自我迴歸移動 平均模式較多；此外，模式中包含季節性因素，顯示季報表之發佈也有其重要性。

In this work we will describe methods for modeling multivariate financial time series. We will concentrate on both modeling expected value by multi- variate Box-Jenkins processes and primarily on modeling conditional corre- lations and volatility. Our main object will be DCC (Dynamic Conditional Correlation) model, estimation of its parameters and some other general- izations. Then we will programme DCC model in statistical software R and apply on real data. In applications we will concentrate on problem of high dimension of financial time series and on modeling conditional correlations data with outliers.

Title: Influence of errors to regression model Author: Bc. Vlasta Poliačková Department: Department of Probability and Mathematical Statistics Supervisor: doc. RNDr. Petr Lachout, CSc. Supervisor's e-mail address: Petr.Lachout@mff.cuni.cz Abstract: The submitted work deals with the regression model, and the influence of errors to regression. Thesis describes different types of violations of assumptions re- quired to the error term and their impact to the properties of the regression model. In the next part, there are discussed various statistical approaches applicable in the case of violation assumptions of regression model such as heteroscedasticity or autocor- relation of the residuals. In the application part, there is used mainly knowledge of Box - Jenkins methodology. In this section it is described in detail how to build a Box - Jenkins models and forecasts of future values for various real financial time series. In processing of the data are used models of ARMA, ARIMA and SARIMA. In an example, forecasts of the models are compared to real future values of the time series. Keywords: regression, violation of assumptions, error term, Box-Jenkins methodo- logy, time series

This is a biographical case study of Mexican industrialization, focusing on expatriate U.S. businessman William O. Jenkins (1878-1963). I trace Jenkins' career in textiles, land speculation, sugar, banking, and film, using it as a forum for themes that flesh out the economic and political history of modern Mexico. Chief among these themes are Mexico's substantial but socially unequal capitalistic development; interdependent relationships between business elites and the state; the role of the regions in Mexican development; and a tradition of viewing U.S. industrialists as enemies of national progress. I use Jenkins to illustrate the ability of Mexico's business elite to negotiate the hazards of the 1910-1920 Revolution and the property expropriations that followed. Industrialists, many of them immigrants, helped to forge rapid economic development between 1933 and 1981. However, their behavior was often characterized by monopolistic and rent-seeking practices, to the qualitative detriment of industries including film and textiles. I demonstrate how the success of industrialists owed much to their relations with politicians, and how the persistence of authoritarian regimes at regional and national levels owed much to industrialists' support. For Jenkins, this symbiosis involved loans to state governors, campaign contributions, and support for the federal government by channeling cheap entertainment to urban populations. Such links help explain why fifty years of development saw little electoral democracy or progressive distribution of wealth. I "de-center" Mexico's economic and political narrative by focusing on the state of Puebla, showing how alliances between industrialists and authorities often begin in provincial arenas and how they can impact national economic and political trends. I also address the underdevelopment of Puebla City, long Mexico's second metropolis, which after 1900 fell significantly behind Guadalajara and Monterrey. Finally, I trace how Jenkins functioned rhetorically as the epitome of the grasping U.S. capitalist. His controversial image afforded leftist politicians, business rivals, and labor leaders with an inflammatory object of protest. Such "gringophobia" in turn contributed to a polarization within Mexican society that proliferated after the 1959 Cuban Revolution. I complement this theme with intermittent commentary on rarely-remarked similarities between business practice in Mexico and the United States. / text

Dissertação (mestrado) - Pontifícia Universidade Católica do Paraná, Curitiba, 2010 / Bibliografia: p.99-109 / O panorama atual da economia globalizada mostra que o ambiente organizacional está muito competitivo e dinâmico. Os mecanismos e os aspectos de como as organizações desenvolvem, planejam e implementam uma estratégia organizacional podem representar ganhos / The current scenario of the globalized economy shows that the organizational environment is very competitive and dynamic. The mechanisms and aspects of how organizations develop, plan and implement an organizational strategy may represent gains or losses.

Made available in DSpace on 2014-06-11T19:22:32Z (GMT). No. of bitstreams: 0 Previous issue date: 2012-02-24Bitstream added on 2014-06-13T18:49:32Z : No. of bitstreams: 1 silva_taa_me_ilha.pdf: 370447 bytes, checksum: b861e5232da4742a12b7ae39aa142840 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Atualmente os sistemas elétricos de potência crescem em tamanho e complexidade e se faz necessário criar alternativas para minimizar o custo total de geração e operação. A previsão de cargas é uma tarefa importante para o planejamento e operação dos sistemas elétricos, pois dela dependem outras tarefas como despacho econômico, fluxo de potência, análise de estabilidade, entre outras. Para tanto esta tarefa deve ser precisa para que o sistema opere de forma segura e confiável. A precisão da previsão é de grande importância já que é através dela que é estabelecida quando e quanto de capacidade de geração e transmissão deve-se dispor para atender a carga prevista sem interrupções no fornecimento. O objetivo deste trabalho é desenvolver um modelo híbrido utilizando os modelos ARIMA de Box & Jenkins e Redes Neurais Artificiais com treinamento realizado pelo algoritmo de Levenberg-Marquartd. Este modelo será utilizado com a finalidade de melhorar a precisão dos resultados com relação à previsão de cargas elétricas a curto prazo. Os resultados obtidos através da metodologia proposta, modelo híbrido de regressão com redes neurais artificiais, foram comparados com demais trabalhos da literatura. É importante destacar que os resultados utilizados na comparação usam o mesmo banco de dados históricos (demanda de carga elétrica) de uma companhia do setor elétrico brasileiro, bem como o mesmo período de janelamento / Nowadays the electric power systems are increasing and becoming complexes and therefore it is necessary to provide alternatives to minimize the generation and operation costs. Load forecasting is a very important task for planning and operation of electric power systems of which other tasks are dependent, as for example, economic dispatch, power flow, and stability analysis, among others. Therefore, this task (load forecasting) must be precise for a secure and reliable operation of the power system. Forecasting precision is very important to set when and how much generation and transmission capacity is necessary to attend the load without interruptions. The objective of this work is to develop a hybrid model using ARIMA of Box & Jenkins and Neural Networks trained by Levenberg-Marquardt algorithm. This model is used aiming to improve the precision of the short term electrical load forecasting. The results obtained were compared with others available on the literature. It is emphasized that the data used is the same (from a Brazilian electric company) as well as the window period

This thesis deals about using models of neural networks like alternative of time series model based on Box-Jenkins methodology. The work is divided into two parts according to the model construction method. Each of the parts contains a theory that explains the individual processes and the progress of the model construction. This is followed by two experiments demonstrating the difference in approach to the design of a given model and creating a forecast by estimated values. for the following year. The last part expertly evaluates the quality of the predictions and considers the use of neural networks against prediction models as an alternative to Box-Jenkins methodology based models

This work concerns the creation of automatized procedure of ARIMA and SARIMA class model choice according to Box-Jenkins methodology and in this connection, also deals with force testing of unit roots and analysis of applying of informatics criteria when choosing a model. The goal of this work is to create an application in the environment R that can automatically choose a model of time array generating process. The procedure is verified by a simulation study. In this work an effect of values of generating ARMA (1,1) model processes parameters is examined, for his choice and power of KPSS test, augmented Dickey-Fuller and Phillips-Peron test of unit roots.