Global state predicates in rough real-time

Distributed systems are characterized by the fact that the constituent processes have neither common memory nor a common system clock. These processes communicate solely via message passing. While providing a number of benefits such as increased reliability, increased computational power, and geographic dispersion, this architecture significantly complicates many of the tasks of software development and verification, including evaluation of the program state. In the case of distributed systems, the program state is comprised of the local states of the constituent processes, as well as the state of the channels between processes, and is called the global state.;With no common system clock, many distributed system protocols rely on the global ordering of local process events imposed by the message passing that occurs between processes. This leads to a partial global ordering of local process events, which can then be used to determine which process states could (or could not) have occurred simultaneously.;Traditional predicate evaluation protocols evaluate predicates on the global state of a distributed computation using consistent global states. This evaluation is complicated by the fact that the event ordering imposed by message passing is only partial. A complete history of the global states that occurred during an execution cannot always be constructed. This introduces inefficiency into predicate detection protocols and prohibits detection of certain predicates.;This dissertation explores the use of this rough global time base for global state predicate evaluation within distributed systems. By structuring the evaluation on the assumption that a global time base exists, we can develop simple and efficient protocols for both stable and unstable predicate evaluation. Further, we can evaluate certain predicates which are not easily evaluated using consistent global states. We demonstrate these advantages by developing protocols for detection of distributed termination, distributed deadlock detection, and detection of certain unstable predicates as they occur. as the global time base is rough, we can only detect unstable predicates which remain true for a sufficient duration. We additionally develop several formalizations which assist the protocol developer in dealing with the fact that the global time base is not perfect. We demonstrate the application of these formalizations within the protocols that we develop

Advances in Data Mining Knowledge Discovery and Applications

Advances in Data Mining Knowledge Discovery and Applications aims to help data miners, researchers, scholars, and PhD students who wish to apply data mining techniques. The primary contribution of this book is highlighting frontier fields and implementations of the knowledge discovery and data mining. It seems to be same things are repeated again. But in general, same approach and techniques may help us in different fields and expertise areas. This book presents knowledge discovery and data mining applications in two different sections. As known that, data mining covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, and other areas. In this book, most of the areas are covered with different data mining applications. The eighteen chapters have been classified in two parts: Knowledge Discovery and Data Mining Applications

Tacit Web: Entrepreneurial Discovery, Institutional Complexity and Internet Diffusion

This dissertation investigates how institutional frameworks and entrepreneurial discovery processes condition internet diffusion. While internet and internet-based technologies have received considerable scholarly attention, the dissertation emphasizes tacit elements in understanding internet diffusion. In order to do so, it incorporates perspectives on insttitutional complexity stemming from interactions of formal and informal institutions and different institutional logics. Empiral part consists both macro level comparisons of Estonia and Slovenia as well as micro level analysis of internet diffusion processes within Estonia. Estonia and Slovenia are selected for comparison because of considerable variance in insitutional frameworks. At the same time, both countries are relatively small and members of the European Union. This allows to focus on specific institutional configurations and path-dependencies in constraining and enabling the diffusion of internet. I find that internet is diffused more extensively and intensively in Estonia. Different socio-economic groups use more sophisticated online services in Estonia than in Slovenia. Once specific institutional configurations in general and in the telecom sector in particular are considered then it emerges that insitutional frameworks in Estonia have been more facilitative of entrepreneurial discovery processes over time. As a result, supply and demand for innovative online services in Estonia is greater than in Slovenia. After comparative perspective on two countries, the dissertation proceeds to analyze specific cases of online initiatives in Estonia such as internet banking and internet voting. Examination of outcomes shows how some of these initiatives have been successful and created reasons for adoption and use of internet on the individual level leading to a greater diffusion on macro level. My analysis demonstrates that positive outcomes have often been unintended result of experimentation through the process of entrepreneurial discovery within the context of institutions and path-dependencies. Evidence for this finding is bolstered by study of heterogeneous cases of various ICT initiatives. By emphazing institutional complexity and policy heterogeneity, the dissertation illuminates and explains the tacit nature of internet diffusion in a specific context of Estonia. This implies that Estonia has followed a unique developmental trajectory which cannot be generalized and transferred to other countries

Biological investigation and predictive modelling of foaming in anaerobic digester

Anaerobic digestion (AD) of waste has been identified as a leading technology for greener renewable energy generation as an alternative to fossil fuel. AD will reduce waste through biochemical processes, converting it to biogas which could be used as a source of renewable energy and the residue bio-solids utilised in enriching the soil. A problem with AD though is with its foaming and the associated biogas loss. Tackling this problem effectively requires identifying and effectively controlling factors that trigger and promote foaming. In this research, laboratory experiments were initially carried out to differentiate foaming causal and exacerbating factors. Then the impact of the identified causal factors (organic loading rate-OLR and volatile fatty acid-VFA) on foaming occurrence were monitored and recorded. Further analysis of foaming and nonfoaming sludge samples by metabolomics techniques confirmed that the OLR and VFA are the prime causes of foaming occurrence in AD. In addition, the metagenomics analysis showed that the phylum bacteroidetes and proteobacteria were found to be predominant with a higher relative abundance of 30% and 29% respectively while the phylum actinobacteria representing the most prominent filamentous foam causing bacteria such as Norcadia amarae and Microthrix Parvicella had a very low and consistent relative abundance of 0.9% indicating that the foaming occurrence in the AD studied was not triggered by the presence of filamentous bacteria. Consequently, data driven models to predict foam formation were developed based on experimental data with inputs (OLR and VFA in the feed) and output (foaming occurrence). The models were extensively validated and assessed based on the mean squared error (MSE), root mean squared error (RMSE), R2 and mean absolute error (MAE). Levenberg Marquadt neural network model proved to be the best model for foaming prediction in AD, with RMSE = 5.49, MSE = 30.19 and R2 = 0.9435. The significance of this study is the development of a parsimonious and effective modelling tool that enable AD operators to proactively avert foaming occurrence, as the two model input variables (OLR and VFA) can be easily adjustable through simple programmable logic controller

Indigenous Firm Performance in a Small Late Developing State : A Case-study of the Role and Contribution of Public Venture Capital in Ireland.

Domestic market size constraints in small late developing states are expected to influence the economic growth process in general and indigenous firm performance in particular. The role and contribution of policy-makers in overcoming these constraints can therefore be significant. This thesis evaluates the role and contribution of public venture capital - as a significant industrial policy initiative - to shareholder value creation in growth-oriented indigenous firms in Ireland. Three main themes are investigated. Firstly the rationale and context for micro-level industrial policy interventions in Ireland is considered. Secondly, the role and contribution of public venture capital to indigenous firm performance and thirdly the factors differentiating between performing and non-performing firms are explored. Using mixed methods research this study finds that in a small late developing state such as Ireland, 'job creation' has been elevated from an industrial policy perspective to the de facto national objective. Enterprise policy development for indigenous industry however remains largely emergent and fluid, fifty-four years on from the advent of the national export-oriented industrial policy. In the absence of a deliberately-stated enterprise policy, this emergent micro-level approach has led the states' economic development agency into areas outside its originally intended remit. This goes some way to explaining the plethora of micro-level policy instruments available in Ireland to growth-oriented indigenous firms. Further, this study also finds no conclusive evidence that an 'equity gap' existed in the analysis period. However, as a consequence of attempting to close this perceived gap, the Irish state now finds itself with an investment portfolio of over nine hundred direct share investments in indigenous firms. The Irish State, through its economic development agency, has thus become the largest venture capital company in Europe. The portfolio of state-selected firms in the analysis (n = 51) for public venture capital investment are found not to perform as anticipated by the theory of change mapped out in the study. A quantitative model developed for the study also finds that there is no statistically significant association between firm performance as measured in the study and the value of the public venture capital invested in each firm. The crosscase and contribution analysis in the study further confirm that the contribution of public venture capital to indigenous firm performance in Ireland was marginal at best. The primary barrier to profitable growth for the indigenous firms receiving public venture capital support in the analysis period was the firms 'Limited endowments of managerial resources' (Penrose, 1959) to manage the growth process and not a lack of risk capital as perceived by agents of the State. Policy implications of the findings are also considered in the study

Strategic Innovation Capacity: A Mixed Method Study on Deliberate Strategic Learning Mechanisms

Several management scholars have come to propound strategic innovation as an effective means to create new and substantially superior customer value, and to combat firms’ inclination towards strategic convergence. Research on strategic innovation is however still in its infancy, tends to lack scientific rigor and has so far proven unable to provide managers with well-founded insights into the specifics of strategic innovation creation. This research therefore aims to study mechanisms that managers can deliberately establish to foster their business unit’s strategic innovation capacity. A thorough review of the literature on strategic innovation and on related concepts enables us to develop a definition of strategic innovation capacity. Our quest for managerial mechanisms essentially rests on a theoretical integration of the concepts of dynamic capabilities, absorptive capacity and strategic innovation. A further study of contributions on sensemaking and routines enables us to finally identify semi-structured mechanisms managers can deliberately establish to foster their firms’ strategic innovation capacity. Relying on a sequential qualitative-quantitative mixed method design, we study these ‘deliberate strategic learning mechanisms’ empirically. Our findings of Dutch industrial business units suggest the usefulness of these mechanisms to stimulate strategic innovation capacity, and show how different mechanisms work in concert. The empirical results furthermore identify relevant path breaking areas that these mechanisms target, and link their effectiveness to specific organizational and supply chain characteristics.Verschillende managementauteurs beschouwen strategische innovatie als een effectief middel om fundamenteel nieuwe en meer waarde voor klanten te creëren, en om strategie-convergentie te bestrijden. Echter, onderzoek rond strategische innovatie staat nog in zijn kinderschoenen en vertoont weinig wetenschappelijke nauwkeurigheid en diepgang. Bovendien is men er nog niet in geslaagd om managers degelijk gefundeerde inzichten te verschaffen in de manieren waarop strategische innovatie kan worden gecreëerd. Deze studie heeft dan ook tot doel om mechanismen te onderzoeken die managers doelbewust kunnen inzetten om de strategische-innovatiecapaciteit van hun business unit te verhogen. Een diepgaande literatuurstudie van bijdragen rond strategische innovatie en aanverwante concepten stelt ons in staat om een definitie van strategische-innovatiecapaciteit te ontwikkelen. Onze eigenlijke zoektocht naar managementmechanismen steunt op de theoretische integratie van de concepten dynamische vaardigheden, absorptievermogen en strategische innovatie. Recente inzichten rond routines helpen ons om semi-gestructureerde mechanismen te achterhalen die bedrijven kunnen inzetten ter verhoging van hun strategische-innovatiecapaciteit. Op basis van een sequentiële kwalitatieve-kwantitatieve studie bestuderen we deze ‘doelbewust opgezette mechanismen voor strategisch leren’ ook empirisch. Onze onderzoeksresultaten van Nederlandse industriële business units tonen de effectiviteit van deze mechanismen aan. De bevindingen wijzen bovendien op een aantal kernaspecten die deze mechanismen stimuleren, en relateren hun effectiviteit aan specifieke eigenschappen van de business unit en van de bedrijfsketen waarin deze actief is