Comparison Structure Analysis

This study presents an automatic, computer-aided analytical method called Comparison Structure Analysis (CSA), which can be applied to different dimensions of music. The aim of CSA is first and foremost practical: to produce dynamic and understandable representations of musical properties by evaluating the prevalence of a chosen musical data structure through a musical piece. Such a comparison structure may refer to a mathematical vector, a set, a matrix or another type of data structure and even a combination of data structures. CSA depends on an abstract systematic segmentation that allows for a statistical or mathematical survey of the data. To choose a comparison structure is to tune the apparatus to be sensitive to an exclusive set of musical properties. CSA settles somewhere between traditional music analysis and computer aided music information retrieval (MIR). Theoretically defined musical entities, such as pitch-class sets, set-classes and particular rhythm patterns are detected in compositions using pattern extraction and pattern comparison algorithms that are typical within the field of MIR. In principle, the idea of comparison structure analysis can be applied to any time-series type data and, in the music analytical context, to polyphonic as well as homophonic music. Tonal trends, set-class similarities, invertible counterpoints, voice-leading similarities, short-term modulations, rhythmic similarities and multiparametric changes in musical texture were studied. Since CSA allows for a highly accurate classification of compositions, its methods may be applicable to symbolic music information retrieval as well. The strength of CSA relies especially on the possibility to make comparisons between the observations concerning different musical parameters and to combine it with statistical and perhaps other music analytical methods. The results of CSA are dependent on the competence of the similarity measure. New similarity measures for tonal stability, rhythmic and set-class similarity measurements were proposed. The most advanced results were attained by employing the automated function generation – comparable with the so-called genetic programming – to search for an optimal model for set-class similarity measurements. However, the results of CSA seem to agree strongly, independent of the type of similarity function employed in the analysis.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

A systematic mapping study on open data

This thesis presented the overview of Open Data research area, quantity of evidence and establishes the research evidence based on the Systematic Mapping Study (SMS). There are 621 such publications were identified published between years 2005 and 2014, but only 243 were selected in the review process. This thesis highlights the implications of Open Data principals’ proliferation in the emerging era of the accessibility, reusability and sustainability of data transparency. The findings of mapping study are described in quantitative and qualitative measurement based on the organization affiliation, countries, year of publications, research method, star rating and units of analysis identified. Furthermore, units of analysis were categorized by development lifecycle, linked open data, type of data, technical platforms, organizations, ontology and semantic, adoption and awareness, intermediaries, security and privacy and supply of data which are important component to provide a quality open data applications and services. The results of the mapping study help the organizations (such as academia, government and industries), re-searchers and software developers to understand the existing trend of open data, latest research development and the demand of future research. In addition, the proposed conceptual framework of Open Data research can be adopted and expanded to strengthen and improved current open data applications.

Systematic mapping study on integration of B2B customers in ERP

Business-to-business terminology is relatively new as a business concept, so is the enterprise resource planning system in information technology. Research, implementation and integration of these two concept has been observed for last two decades in this paper. One of the major success point for growth in business-to-business environment is the availability of internal and partner data. Enterprise resource planning system facilitates storing, analysis of such data and enables different business process automation, forecasting and numerous value creating activity. In order to achieve such functionality for B2B customers, integrating them within ERP is very useful. This paper aims at understanding and suggesting such integration through investigating related documentation of similar integration scenarios, infrastructure, models and architectures. The investigation of the topic of this paper has been made using systematic mapping study of related papers and listing and suggesting necessary ingredients that enables such integration. Furthermore, this paper also suggests possibilities to overcome challenges integration experts might face during the integration phase and opens doors to future research scope in the related fields.

What is the current state of cloud service research and its promise for the future? A systematic literature review

The information technology (IT) industry has recently witnessed the proliferation of cloud services, which have allowed IT service providers to deliver on-demand resources to customers over the Internet. This frees both service providers and consumers from traditional IT-related burdens such as capital and operating expenses and allows them to respond rapidly to new opportunities in the market. Due to the popularity and growth of cloud services, numerous researchers have conducted studies on various aspects of cloud services, both positive and negative. However, none of those studies have connected all relevant information to provide a holistic picture of the current state of cloud service research. This study aims to investigate that current situation and propose the most promising future directions. In order to determine achieve these goals, a systematic literature review was conducted on studies with a primary focus on cloud services. Based on carefully crafted inclusion criteria, 52 articles from highly credible online sources were selected for the review. To define the main focus of the review and facilitate the analysis of literature, a conceptual framework with five main factors was proposed. The selected articles were organized under the factors of the proposed framework and then synthesized using a narrative technique. The results of this systematic review indicate that the impacts of cloud services on enterprises were the factor best covered by contemporary research. Researchers were able to present valuable findings about how cloud services impact various aspects of enterprises such as governance, performance, and security. By contrast, the role of service provider sub-contractors in the cloud service market remains largely uninvestigated, as do cloud-based enterprise software and cloud-based office systems for consumers. Moreover, the results also show that researchers should pay more attention to the integration of cloud services into legacy IT systems to facilitate the adoption of cloud services by enterprise users. After the literature synthesis, the present study proposed several promising directions for cloud service research by outlining research questions for the underexplored areas of cloud services, in order to facilitate the development of cloud service markets in the future.