Computação em nuvem é uma solução adequada para profissionais, empresas, centros de pesquisa e instituições que necessitam de acesso a recursos computacionais sob demanda. Atualmente, nuvens computacionais confiam no gerenciamento de sua estrutura para fornecer recursos computacionais com qualidade de serviço adequada as expectativas de seus clientes, tal qualidade de serviço é estabelecida através de acordos de nível de serviço. Nesse contexto, o monitoramento é uma função crítica de gerenciamento para se prover tal qualidade de serviço. Requisitos de monitoramento em nuvens computacionais são propriedades que um sistema de monitoramento de nuvem precisa reunir para executar suas funções de modo adequado e atualmente existem diversos requisitos definidos pela literatura, tais como: oportunidade, elasticidade e escalabilidade. Entretanto, tais requisitos geralmente possuem influência mútua entre eles, que pode ser positiva ou negativa, e isso impossibilita o desenvolvimento de soluções de monitoramento completas. Dado o cenario descrito acima, essa tese tem como objetivo investigar a influência mútua entre escalabilidade e oportunidade. Especificamente, essa tese propõe um modelo matemático para estimar a influência mútua entre tais requisitos de monitoramento. A metodologia utilizada por essa tese para construir tal modelo matemático baseia-se em parâmetros de monitoramento tais como: topologia de monitoramento, quantidade de dados de monitoramento e frequencia de amostragem. Além destes, a largura de banda de rede e o tempo de resposta também são importantes métricas do modelo matemático. A avaliação dos resultados obtidos foi realizada através da comparação entre os resultados do modelo matemático e de uma simulação. As maiores contribuições dessa tese são divididas em dois eixos, estes são denominados: Básico e Chave. As contribuições do eixo básico são: (i) a discussão a respeito da estrutura de monitoramento de nuvem e introdução do conceito de foco de monitoramento (ii) o exame do conceito de requisito de monitoramento e a proposição do conceito de abilidade de monitoramento (iii) a análise dos desafios e tendências a respeito de monitoramento de nuvens computacionais. As contribuições do eixo chave são: (i) a discussão a respeito de oportunidade e escalabilidade incluindo métodos para lidar com a mútua influência entre tais requisitos e a relação desses requisitos com parâmetros de monitoramento (ii) a identificação dos parâmetros de monitoramento que são essenciais na relação entre oportunidade e escalabilidade (iii) a proposição de um modelo matemático baseado em parâmetros de monitoramento que visa estimar a relação mútua entre oportunidade e escalabilidade. / Cloud computing is a suitable solution for professionals, companies, research centres, and institutions that need to have access to computational resources on demand. Nowadays, clouds have to rely on proper management of its structure to provide such computational resources with adequate quality of service, which is established by Service Level Agreements (SLAs), to customers. In this context, cloud monitoring is a critical management function to achieve it. Cloud monitoring requirements are properties that a cloud monitoring system need to meet to perform its functions properly, and currently there are several of them such as timeliness, elasticity and scalability. However, such requirements usually have mutual influence, which is either positive or negative, among themselves, and it has prevented the development of complete cloud monitoring solutions. From the above, this thesis investigates the mutual influence between timeliness and scalability. This thesis proposes a mathematical model to estimate such mutual influence to enhance cloud monitoring systems. The methodology used in this thesis is based on monitoring parameters such as monitoring topologies, the amount of monitoring data, and frequency sampling. Besides, it considers as important metrics network bandwidth and response time. Finally, the evaluation is based on a comparison of the mathematical model results and outcomes obtained via simulation. The main contributions of this thesis are divided into two axes, namely, basic and key. Basic contributions of this thesis are: (i) it discusses the cloud monitoring structure and introduced the concept of cloud monitoring focus (ii) it examines the concept of cloud monitoring requirement and proposed to divide them into two groups defined as cloud monitoring requirements and cloud monitoring abilities (iii) it analysed challenges and trends in cloud monitoring pointing research gaps that include the mutual influence between cloud monitoring requirements which is core to the key contributions. The key contributions of this thesis are: (i) it presents a discussion of timeliness and scalability that include: the methods currently used to cope with the mutual influence between them, and the relation between such requirements and monitoring parameters (ii) it identifies the monitoring parameters that are essential in the relation between timeliness and scalability (iii) it proposes a mathematical model based on monitoring parameters to estimate the mutual influence between timeliness and scalability.

In this thesis, we study if credit rating agencies (CRAs) are capable, through their rating process, of discover information that it is valued by the market. Additionally, we investigate if CRAs are able to propagate their findings to the market. if Specifically, we study the differences between issuer-paid and investor-paid credit rating agencies, and how those differences shape the characteristics of their credit ratings and ultimately, if investors can profit from credit rating announcements. For our research we use a large dataset of rating announcements from 1997 to 2012, which includes information of four credit rating agencies (CRAs), Egan-Jones Ratings Company (EJR), Fitch, Moody's and Standard and Poor's, which representing investor-paid and issuer-paid CRAs. This allows us to compare these two kind of agencies and its ratings. In the first essay we study what variables explain the rating coverage of an investor-paid credit rating agency. We show that probability of being covered by EJR is positively related with the size of the firm, the level of institutional ownership of the firm, stock analysts and issuer-paid CRAs level of coverage, while it is negatively related to the firm's corporate governance. We found that the likelihood of being covered by EJR augments after regulatory changes and most interestingly, since EJR received the NRSRO certification. In the second essay we compare the timeliness of rating changes produced by EJR and the issuer-paid CRAs representatives. We found that the lead effect of investor-paid over issuer-paid CRAs has weakened in recent years, while Granger causality is bidirectional and therefore a lead-lag relationship cannot be established. Finally, stock prices manifest statistically significant abnormal reactions to downgrades of all agencies; however, abnormal negative returns are significantly higher for EJR. Our results support the hypothesis that issuer-paid agencies improve the quality and timeliness of their ratings when they see their market power threatened by tighter regulations. Nevertheless, event studies illustrate that markets still price stocks under the assumption that investor-paid rating actions carry superior information. Finally, our third essay found that purchasing (selling short) stocks with positive (negative) rating announcements generates portfolios with positive annual abnormal returns when investors react immediately to rating announcements. Returns are higher for stronger announcements (i.e. rating changes over rating outlooks) and for an investor-paid agency rather than an issuer-paid agency. When we introduced transaction costs, only the investor-paid agencies' announcements lead to positive abnormal returns. Additionally, when we included a delay in the reaction of investors to rating announcements, all positive abnormal returns net of transaction costs disappeared. Finally, our results suggests that the differences between investor-paid and issuer-paid agencies are based on their dissimilar business models rather than their regulatory status.

This study investigates the effect of CFO gender on auditor turnover, audit fees, and financial reporting timeliness. Since investors value audit outcomes such as auditor turnover, audit fees, and reporting timeliness as important financial signals, differences in the probability of auditor turnovers, the amount of audit fees, and the speed of financial reporting between male CFO firms and female CFO firms can help investors make better informed financial decisions. Additionally, these audit outcome differences between male and female CFOs can also provide insights to executive hiring-decisions and audit budgeting. The results of this study suggest that firms with female CFOs take longer to report financial statements than their male counterparts. However, I do not find evidence for differences in the probability of auditor turnover between female CFO and male CFO firms. I also do not find significant differences in audit fees between firms with female and male CFOs. Overall, this study highlights how gender differences in risk-tolerance and confidence level can affect tangible audit outcomes.

We present a formally specified event specification language (Solicitor). Solicitor is suitable for real-time systems, since it results in resource-predictable and efficient event monitors. In event monitoring, event expressions defined in an event specification language control the monitoring by matching incoming streams of event occurrences against the event expressions. When an event expression has a complete set of matching event occurrences, the event type that this expression defines has occurred. Each event expression is specified by combining contributing event types with event operators such as sequence, conjunction, disjunction; contributing event types may be primitive, representing happenings of interest in a system, or composite, specified by event expressions. The formal specification of Solicitor is based on a formal schema that separates two important aspects of an event expression; these aspects are event operators and event contexts. The event operators aspect addresses the relative constraints between contributing event occurrences, whereas the event contexts aspect addresses the selection of event occurrences from an event stream with respect to event occurrences that are used or invalidated during event monitoring. The formal schema also contains an abstract model of event monitoring. Given this formal specification, we present realization issues of, a time complexity study of, as well as a proof of limited resource requirements of event monitoring. We propose an architecture for resource-predictable and efficient event monitoring. In particular, this architecture meets the requirements of realtime systems by defining how event monitoring and tasks are associated. A declarative way of specifying this association is proposed within our architecture. Moreover, an efficient memory management scheme for event composition is presented. This scheme meets the requirements of event monitoring in distributed systems. This architecture has been validated by implementing an executable component prototype that is part of the DeeDS prototype. The results of the time complexity study are validated by experiments. Our experiments corroborate the theory in terms of complexity classes of event composition in different event contexts. However, the experimental platform is not representative of operational real-time systems and, thus, the constants derived from our experiments cannot be used for such systems.

A problem when testing timeliness of event-triggered real-time systems is that response times depend on the execution order of concurrent tasks. Conventional testing methods ignore task interleaving and timing and thus do not help determine which execution orders need to be exercised to gain confidence in temporal correctness. This thesis presents and evaluates a framework for testing of timeliness that is based on mutation testing theory. The framework includes two complementary approaches for mutation-based test case generation, testing criteria for timeliness, and tools for automating the test case generation process. A scheme for automated test case execution is also defined. The testing framework assumes that a structured notation is used to model the real-time applications and their execution environment. This real-time system model is subsequently mutated by operators that mimic potential errors that may lead to timeliness failures. Each mutated model is automatically analyzed to generate test cases that target execution orders that are likely to lead to timeliness failures. The validation of the theory and methods in the proposed testing framework is done iteratively through case-studies, experiments and proof-of-concept implementations. This research indicates that an adapted form of mutation-based testing can be used for effective and automated testing of timeliness and, thus, for increasing the confidence level in real-time systems that are designed according to the event-triggered paradigm.

This dissertation concerns testability of event-triggered real-time systems. Real-time systems are known to be hard to test because they are required to function correct both with respect to what the system does and when it does it. An event-triggered real-time system is directly controlled by the events that occur in the environment, as opposed to a time-triggered system, which behavior with respect to when the system does something is constrained, and therefore more predictable. The focus in this dissertation is the behavior in the time domain and it is shown how testability is affected by some factors when the system is tested for timeliness. This dissertation presents a survey of research that focuses on software testability and testability of real-time systems. The survey motivates both the view of testability taken in this dissertation and the metric that is chosen to measure testability in an experiment. We define a method to generate sets of traces from a model by using a meta algorithm on top of a model checker. Defining such a method is a necessary step to perform the experiment. However, the trace sets generated by this method can also be used by test strategies that are based on orderings, for example execution orders. An experimental study is presented in detail. The experiment investigates how testability of an event-triggered real-time system is affected by some constraining properties of the execution environment. The experiment investigates the effect on testability from three different constraints regarding preemptions, observations and process instances. All of these constraints were claimed in previous work to be significant factors for the level of testability. Our results support the claim for the first two of the constraints while the third constraint shows no impact on the level of testability. Finally, this dissertation discusses the effect on the event-triggered semantics when the constraints are applied on the execution environment. The result from this discussion is that the first two constraints do not change the semantics while the third one does. This result indicates that a constraint on the number of process instances might be less useful for some event-triggered real-time systems.

<p>This work aims to investigate the state of the art in test case generation for real-time systems, to analyze existing methods, and to propose future research directions in this area. We believe that a combination of design for testability, automation, and sensible test case selection is the key for verifying modern real-time systems. Existing methods for system-level test case generation for real-time systems are presented, classified, and evaluated against a real-time system model. Significant for real-time systems is that timeliness is crucial for their correctness. Our system model of the testing target adopts the event-triggered design paradigm for maximum flexibility. This paradigm results in target systems that are harder to test than its time-triggered counterpart, but the model improves testability by adopting previously proposed constraints on application behavior. This work investigates how time constraints can be tested using current methods and reveals problems relating to test-case generation for verifying such constraints. Further, approaches for automating the test-case generation process are investigated, paying special attention to methods aimed for real-time systems. We also note a need for special test-coverage criteria for concurrent and real-time systems to select test cases that increase confidence in such systems. We analyze some existing criteria from the perspective of our target model. The results of this dissertation are a classification of methods for generating test cases for real-time systems, an identification of contradictory terminology, and an increased body of knowledge about problems and open issues in this area. We conclude that the test-case generation process often neglects the internal behavior of the tested system and the properties of its execution environment as well as the effects of these on timeliness. Further, we note that most of the surveyed articles on testing methods incorporate automatic test-case generation in some form, but few consider the issues of automated execution of test cases. Four high-level future research directions are proposed that aim to remedy one or more of the identified problems.</p>

Aim of the study. To estimate timeliness of diagnosis of 2-type diabetes and causes of complications in Prienai district. Methods. In January – December 2005, questionnaire survey of the residents of Prienai district, to whom 2-type diabetes (n=76) was diagnosed for the first time and patients suffering of 2-type diabetes (n=219), was conducted. Statistical analysis package SPSS (9.0) was used to analyse the data. Dependence of two symptoms was researched by the use of Chi-Square test (χ²). Zero hypothesis was rejected, when p<0,05. Results. Diabetes was untimely diagnosed for 62,7 % patients, because at the moment of diagnosis they already had chronic complications, and 37.3% patients had their illness diagnosed in time. In cases when patients visited a health care institution for preventive reasons, diabetes was diagnosed more frequently and in a lighter stage than in the cases when patients addressed health care institutions due to complaints. If a family doctor suspected diabetes, diagnosis was timely diagnosed more frequently than if suspected by any other specialist. According to statistics, complications were caused by duration of illness, insufficient use of self-control means. Timeliness of diagnosis and rise of complications of diabetes did not depend on the age, sex, place of residence, marital status, education or occupation of the respondents. Conclusions. Timeliness of diagnosis of diabetes was determined by timeliness of glycaemia test, reason of a visit... [to full text]

本研究旨在探討資訊揭露程度與盈餘管理間是否存有一反向關係，資訊揭露程度較高的公司是否就代表其盈餘管理程度較低。以92年上市資訊電子業為研究對象，實證結果如下： 1.在其他條件不變下，公司資訊揭露程度與盈餘管理兩者呈顯著的負相關，亦即當管理當局盈餘管理程度越高時，可能為保持其進行盈餘管理之彈性，公司資訊揭露程度會越低。 2.然而進一步加入公司目前表現的優劣加以分析，發現此一負向關係僅限於好消息年度獲得實證上的支持；於壞消息年度，揭露程度與盈餘管理間之關係則並不顯著。 3.從時效性的角度觀察發現：揭露程度低的公司，其盈餘反應好消息的時效性雖優於揭露程度高的公司，但兩者並無顯著的不同。揭露程度高的公司其盈餘反應壞消息的時效性則顯著高於揭露程度低的公司。 4.盈餘反應壞消息較好消息及時之關係僅限於資訊揭露程度較高的公司會成立；揭露程度較低的公司，此關係則並不成立。

Computação em nuvem é uma solução adequada para profissionais, empresas, centros de pesquisa e instituições que necessitam de acesso a recursos computacionais sob demanda. Atualmente, nuvens computacionais confiam no gerenciamento de sua estrutura para fornecer recursos computacionais com qualidade de serviço adequada as expectativas de seus clientes, tal qualidade de serviço é estabelecida através de acordos de nível de serviço. Nesse contexto, o monitoramento é uma função crítica de gerenciamento para se prover tal qualidade de serviço. Requisitos de monitoramento em nuvens computacionais são propriedades que um sistema de monitoramento de nuvem precisa reunir para executar suas funções de modo adequado e atualmente existem diversos requisitos definidos pela literatura, tais como: oportunidade, elasticidade e escalabilidade. Entretanto, tais requisitos geralmente possuem influência mútua entre eles, que pode ser positiva ou negativa, e isso impossibilita o desenvolvimento de soluções de monitoramento completas. Dado o cenario descrito acima, essa tese tem como objetivo investigar a influência mútua entre escalabilidade e oportunidade. Especificamente, essa tese propõe um modelo matemático para estimar a influência mútua entre tais requisitos de monitoramento. A metodologia utilizada por essa tese para construir tal modelo matemático baseia-se em parâmetros de monitoramento tais como: topologia de monitoramento, quantidade de dados de monitoramento e frequencia de amostragem. Além destes, a largura de banda de rede e o tempo de resposta também são importantes métricas do modelo matemático. A avaliação dos resultados obtidos foi realizada através da comparação entre os resultados do modelo matemático e de uma simulação. As maiores contribuições dessa tese são divididas em dois eixos, estes são denominados: Básico e Chave. As contribuições do eixo básico são: (i) a discussão a respeito da estrutura de monitoramento de nuvem e introdução do conceito de foco de monitoramento (ii) o exame do conceito de requisito de monitoramento e a proposição do conceito de abilidade de monitoramento (iii) a análise dos desafios e tendências a respeito de monitoramento de nuvens computacionais. As contribuições do eixo chave são: (i) a discussão a respeito de oportunidade e escalabilidade incluindo métodos para lidar com a mútua influência entre tais requisitos e a relação desses requisitos com parâmetros de monitoramento (ii) a identificação dos parâmetros de monitoramento que são essenciais na relação entre oportunidade e escalabilidade (iii) a proposição de um modelo matemático baseado em parâmetros de monitoramento que visa estimar a relação mútua entre oportunidade e escalabilidade. / Cloud computing is a suitable solution for professionals, companies, research centres, and institutions that need to have access to computational resources on demand. Nowadays, clouds have to rely on proper management of its structure to provide such computational resources with adequate quality of service, which is established by Service Level Agreements (SLAs), to customers. In this context, cloud monitoring is a critical management function to achieve it. Cloud monitoring requirements are properties that a cloud monitoring system need to meet to perform its functions properly, and currently there are several of them such as timeliness, elasticity and scalability. However, such requirements usually have mutual influence, which is either positive or negative, among themselves, and it has prevented the development of complete cloud monitoring solutions. From the above, this thesis investigates the mutual influence between timeliness and scalability. This thesis proposes a mathematical model to estimate such mutual influence to enhance cloud monitoring systems. The methodology used in this thesis is based on monitoring parameters such as monitoring topologies, the amount of monitoring data, and frequency sampling. Besides, it considers as important metrics network bandwidth and response time. Finally, the evaluation is based on a comparison of the mathematical model results and outcomes obtained via simulation. The main contributions of this thesis are divided into two axes, namely, basic and key. Basic contributions of this thesis are: (i) it discusses the cloud monitoring structure and introduced the concept of cloud monitoring focus (ii) it examines the concept of cloud monitoring requirement and proposed to divide them into two groups defined as cloud monitoring requirements and cloud monitoring abilities (iii) it analysed challenges and trends in cloud monitoring pointing research gaps that include the mutual influence between cloud monitoring requirements which is core to the key contributions. The key contributions of this thesis are: (i) it presents a discussion of timeliness and scalability that include: the methods currently used to cope with the mutual influence between them, and the relation between such requirements and monitoring parameters (ii) it identifies the monitoring parameters that are essential in the relation between timeliness and scalability (iii) it proposes a mathematical model based on monitoring parameters to estimate the mutual influence between timeliness and scalability.