565 research outputs found

    Implementation and Extension of the Technical Documentation Testing Framework

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    Práca sa zaoberá automatizáciou testovania technickej dokumentácie napísanej v značkovacom jazyku AsciiDoc pomocou open-source frameworku testovania technickej dokumentácie Emender implementovaného na CI/CD platforme. Framework bol rozšírený o webovú aplikáciu emenderwebservice s REST API, ktorá poskytuje užívateľské grafické rozhranie s výsledkami testov a mechanizmom na odrieknutie falošne pozitívnych výsledkov testov. Webová aplikácia bola vytvorená pomocou WSGI frameworku na tvorbu webových aplikácií Flask s databázou ktorá umožňuje agregáciu výsledkov testov a ich unikátnu identifikáciu. Aplikácia uľahčuje prístup ku výsledkom testov vygenerovaných frameworkom Emender v CI/CD systémoch a poskytuje technical writer-om ucelené užívateľské prostredie.The thesis discusses automated testing of technical documentation written in AsciiDoc markup language using open-source documentation testing framework Emender implemented in CI/CD. The framework was extended with a RESTful web application emenderwebservice, providing a graphical user interface with test results and a mechanism to waive false positive test results. Web application was implemented with Flask WSGI web application framework along with a database enabling aggregation and unique test identification. The application simplifies access to test results generated by Emender in CI/CD and provides a concise graphical user interface for technical writers.

    Mixed-use Building in Brno, Sadova - Execution of Superstructure

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    Obsahom tejto bakalárskej práce je riešenie technologickej etapy hrubej vrchnej stavby polyfunkčnej budovy v Brne. Práca zahŕňa sprievodnú a súhrnnú technickú správu, technologické predpisy pre montáž prefabrikovaného skeletu a pre murované konštrukcie. Technologické predpisy sú doplnené návrhom zariadenia staveniska vrátane technickej správy, kontrolným a skúšobným plánom pre montáž prefabrikovaného skeletu, časovým plánom, návrhom strojnej zostavy a posúdením výberu zdvíhacieho mechanizmu.The subject of this bachelor thesis is the deal with technological stage of the rough superstructure of a mixed-use building in Brno. The thesis contains accompanying and summary technical reports, technological regulations for the assembly of the prefabricated skeleton and for masonry constructions. Technological regulations are attached to design of site equpiment including engineering report, checking and testing plans for the assembly of the prefabricated skeleton, time schedule, proposal of machine assemblies and assessment of lifting mechanism selection.

    Performance Introspection of Graph Databases

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    The explosion of graph data in social and biological networks, recommendation systems, provenance databases, etc. makes graph storage and processing of paramount importance. We present a performance introspection framework for graph databases, PIG, which provides both a toolset and methodology for understanding graph database performance. PIG consists of a hierarchical collection of benchmarks that compose to produce performance models; the models provide a way to illuminate the strengths and weaknesses of a particular implementation. The suite has three layers of benchmarks: primitive operations, composite access patterns, and graph algorithms. While the framework could be used to compare different graph database systems, its primary goal is to help explain the observed performance of a particular system. Such introspection allows one to evaluate the degree to which systems exploit their knowledge of graph access patterns. We present both the PIG methodology and infrastructure and then demonstrate its efficacy by analyzing the popular Neo4j and DEX graph databases.Engineering and Applied Science

    Assessing the Impact of a Supervised Classification Filter on Flow-based Hybrid Network Anomaly Detection

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    Constant evolution and the emergence of new cyberattacks require the development of advanced techniques for defense. This paper aims to measure the impact of a supervised filter (classifier) in network anomaly detection. We perform our experiments by employing a hybrid anomaly detection approach in network flow data. For this purpose, we extended a state-of-the-art autoencoder-based anomaly detection method by prepending a binary classifier acting as a prefilter for the anomaly detector. The method was evaluated on the publicly available real-world dataset UGR'16. Our empirical results indicate that the hybrid approach does offer a higher detection rate of known attacks than a standalone anomaly detector while still retaining the ability to detect zero-day attacks. Employing a supervised binary prefilter has increased the AUC metric by over 11%, detecting 30% more attacks while keeping the number of false positives approximately the same
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