5 research outputs found

    A configuration-based domain-specific rule generation framework for process model customization

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    In today’s changing world, there is an ever-increasing demand and need for software reuse in applications, where the process model needs to be reused in different applications in a domain-specific environment. The process model is required to adapt and implement changes promptly at run-time, in response of the end-user configuration requirements. Furthermore, reusability is emerging strongly as a necessary underlying capability, particularly for customization of business in a dynamic environment where end-users can select their requirements to achieve a specific goal. Such adaptations are in general, performed by non-technical end-users which can lead to losing a significant number of person-days and which can also open up possibilities to introduce errors into the system. These scenarios call for - indeed cry out for - a system with a configurable and customizable business process, operable by users with limited technical expertise. Research aims to provide a framework for generating the rule language and configuring domain constraints. This framework builds upon the core idea of Software Product Lines Engineering (SPLE) and Model-Driven Architecture (MDA). The SPLE provides a platform that includes the variability model. Variability models offer features where end-users can select features and customize possible changes in the domain template, which is the container for domain and process models. The user selects their requirements as a feature from feature models and generates rules from domain models using MDA. Then, the generated rules are translated from a high-level domain model, based on the requirements of the end-user. On the other hand, the weaving model is responsible for reflecting activation and de-activation of features of variabilities in the domain template. The usability of the proposed framework is evaluated with a user study in the area of Digital Content Technology. The results demonstrate that usability improvements can be achieved by using the proposed techniques. The framework can be used to support semi-automatic configuration that is efficient, effective and satisfactory

    Development of a read mapping analysis software and computational pan genome analysis of 20 Pseudomonas aeruginosa strains

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    Hilker R. Development of a read mapping analysis software and computational pan genome analysis of 20 Pseudomonas aeruginosa strains. Bielefeld: Bielefeld University; 2015.In times of multi-resistant pathogenic bacteria, their detailed study is of utmost importance. Their comparative analysis can even aid the emerging field of personalized medicine by enabling optimized treatment depending on the presence of virulence factors and antibiotic resistances in the infection concerned. The weaknesses and functionality of these pathogenic bacteria can be investigated using modern computer science and novel sequencing technologies. One of these methods is the bioinformatics evaluation of high-throughput sequencing data. A pathogenic bacterium posing severe health care issues is the ubiquitous Pseudomonas aeruginosa. It is involved in a wide range of infections mainly affecting the pulmonary or urinary tract, open wounds and burns. The prevalence of chronic obstructive pulmonary disease cases with P. aeruginosa in Germany alone is ~600,000 per year. Within the framework of this dissertation, computational comparative genomics experiments were conducted with a panel of 20 of the most abundant Pseudomonas aeruginosa strains. 15 of these strains were isolated from clinical cases, while the remaining 5 were strains without a known infection history isolated from the environment. This division was chosen to enable direct comparison of the pathogenic potential of clinical and environmental strains and identification of their possible characteristic differences. When designing the bioinformatics experiments and searching for an efficient visualization and automatic analysis platform for read alignment (mapping) data, it became evident that no adequate solution was available that included all required functionalities. On these grounds, the decision was made to define two main subjects for this dissertation. Besides the P. aeruginosa pan genome analysis, a novel read mapping visualization and analysis software was developed and published in the journal Bioinformatics. This software - ReadXplorer - is partly based upon a prototype, which was developed during a preceding master's thesis at the Center for Biotechnology of the Bielefeld University under the name VAMP. The software was developed into a comprehensive user-friendly platform augmented with several newly developed and implemented automatic bioinformatics read mapping analyses. Two examples of these are the transcription start site detection and the single nucleotide polymorphism detection. Moreover, new intuitive visualizations were added to the existent ones and existing visualizations were greatly enhanced. ReadXplorer is designed to support not only DNA-seq data as accrued in the P. aeruginosa experiments, but also any kind of standard read mapping data as obtained from RNA-seq or ChIP-seq experiments. The data management was designed to comply with the latest performance and efficiency needs emerging from the large next generation sequencing data sets. Finally, ReadXplorer was empowered to deal with eukaryotic read mapping data as well. Amongst other software, ReadXplorer was then used to analyze different comparative genomics aspects of P. aeruginosa and to draw conclusions regarding the development of their pathogenicity. The list of conducted experiments includes phylogeny and gene set determination, analysis of regions of genomic plasticity and identification of single nucleotide polymorphisms. The achieved results were published in the journal Environmental Biology

    Semantic search and composition in unstructured peer-to-peer networks

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    This dissertation focuses on several research questions in the area of semantic search and composition in unstructured peer-to-peer (P2P) networks. Going beyond the state of the art, the proposed semantic-based search strategy S2P2P offers a novel path-suggestion based query routing mechanism, providing a reasonable tradeoff between search performance and network traffic overhead. In addition, the first semantic-based data replication scheme DSDR is proposed. It enables peers to use semantic information to select replica numbers and target peers to address predicted future demands. With DSDR, k-random search can achieve better precision and recall than it can with a near-optimal non-semantic replication strategy. Further, this thesis introduces a functional automatic semantic service composition method, SPSC. Distinctively, it enables peers to jointly compose complex workflows with high cumulative recall but low network traffic overhead, using heuristic-based bidirectional haining and service memorization mechanisms. Its query branching method helps to handle dead-ends in a pruned search space. SPSC is proved to be sound and a lower bound of is completeness is given. Finally, this thesis presents iRep3D for semantic-index based 3D scene selection in P2P search. Its efficient retrieval scales to answer hybrid queries involving conceptual, functional and geometric aspects. iRep3D outperforms previous representative efforts in terms of search precision and efficiency.Diese Dissertation bearbeitet Forschungsfragen zur semantischen Suche und Komposition in unstrukturierten Peer-to-Peer Netzen(P2P). Die semantische Suchstrategie S2P2P verwendet eine neuartige Methode zur Anfrageweiterleitung basierend auf Pfadvorschlägen, welche den Stand der Wissenschaft übertrifft. Sie bietet angemessene Balance zwischen Suchleistung und Kommunikationsbelastung im Netzwerk. Außerdem wird das erste semantische System zur Datenreplikation genannt DSDR vorgestellt, welche semantische Informationen berücksichtigt vorhergesagten zukünftigen Bedarf optimal im P2P zu decken. Hierdurch erzielt k-random-Suche bessere Präzision und Ausbeute als mit nahezu optimaler nicht-semantischer Replikation. SPSC, ein automatisches Verfahren zur funktional korrekten Komposition semantischer Dienste, ermöglicht es Peers, gemeinsam komplexe Ablaufpläne zu komponieren. Mechanismen zur heuristischen bidirektionalen Verkettung und Rückstellung von Diensten ermöglichen hohe Ausbeute bei geringer Belastung des Netzes. Eine Methode zur Anfrageverzweigung vermeidet das Feststecken in Sackgassen im beschnittenen Suchraum. Beweise zur Korrektheit und unteren Schranke der Vollständigkeit von SPSC sind gegeben. iRep3D ist ein neuer semantischer Selektionsmechanismus für 3D-Modelle in P2P. iRep3D beantwortet effizient hybride Anfragen unter Berücksichtigung konzeptioneller, funktionaler und geometrischer Aspekte. Der Ansatz übertrifft vorherige Arbeiten bezüglich Präzision und Effizienz

    Semantic search and composition in unstructured peer-to-peer networks

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    This dissertation focuses on several research questions in the area of semantic search and composition in unstructured peer-to-peer (P2P) networks. Going beyond the state of the art, the proposed semantic-based search strategy S2P2P offers a novel path-suggestion based query routing mechanism, providing a reasonable tradeoff between search performance and network traffic overhead. In addition, the first semantic-based data replication scheme DSDR is proposed. It enables peers to use semantic information to select replica numbers and target peers to address predicted future demands. With DSDR, k-random search can achieve better precision and recall than it can with a near-optimal non-semantic replication strategy. Further, this thesis introduces a functional automatic semantic service composition method, SPSC. Distinctively, it enables peers to jointly compose complex workflows with high cumulative recall but low network traffic overhead, using heuristic-based bidirectional haining and service memorization mechanisms. Its query branching method helps to handle dead-ends in a pruned search space. SPSC is proved to be sound and a lower bound of is completeness is given. Finally, this thesis presents iRep3D for semantic-index based 3D scene selection in P2P search. Its efficient retrieval scales to answer hybrid queries involving conceptual, functional and geometric aspects. iRep3D outperforms previous representative efforts in terms of search precision and efficiency.Diese Dissertation bearbeitet Forschungsfragen zur semantischen Suche und Komposition in unstrukturierten Peer-to-Peer Netzen(P2P). Die semantische Suchstrategie S2P2P verwendet eine neuartige Methode zur Anfrageweiterleitung basierend auf Pfadvorschlägen, welche den Stand der Wissenschaft übertrifft. Sie bietet angemessene Balance zwischen Suchleistung und Kommunikationsbelastung im Netzwerk. Außerdem wird das erste semantische System zur Datenreplikation genannt DSDR vorgestellt, welche semantische Informationen berücksichtigt vorhergesagten zukünftigen Bedarf optimal im P2P zu decken. Hierdurch erzielt k-random-Suche bessere Präzision und Ausbeute als mit nahezu optimaler nicht-semantischer Replikation. SPSC, ein automatisches Verfahren zur funktional korrekten Komposition semantischer Dienste, ermöglicht es Peers, gemeinsam komplexe Ablaufpläne zu komponieren. Mechanismen zur heuristischen bidirektionalen Verkettung und Rückstellung von Diensten ermöglichen hohe Ausbeute bei geringer Belastung des Netzes. Eine Methode zur Anfrageverzweigung vermeidet das Feststecken in Sackgassen im beschnittenen Suchraum. Beweise zur Korrektheit und unteren Schranke der Vollständigkeit von SPSC sind gegeben. iRep3D ist ein neuer semantischer Selektionsmechanismus für 3D-Modelle in P2P. iRep3D beantwortet effizient hybride Anfragen unter Berücksichtigung konzeptioneller, funktionaler und geometrischer Aspekte. Der Ansatz übertrifft vorherige Arbeiten bezüglich Präzision und Effizienz

    A Unified RGPS-Based Approach Supporting Service-Oriented Process Customization

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    Service-oriented process customization is a key issue in SaaS. In this chapter, based on the RGPS meta-model framework, we propose a service-oriented process customization approach that can help end-users configure a personalized mashup in design time. Corresponding visualization prototypes are introduced, and a case study illustrates how to follow our approach to customize a shipping mashup. Our approach depends on the quality of domain models to a large extent. If users’ requirements cannot be satisfied, their unmatched goals will be recorded, which will in turn contribute to the evolution of domain models. So our approach is an iterative method in essence
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