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Large-scale graph analysis or also called network analysis of networks is supported by different algorithms, among the most relevant are PageRank (Web page ranking), Betweenness centrality (centrality in a graph) and Community Detection, these by of their complexity and the large amount of data that process diverse applications, increasingly need to use computational resources such as processor, memory...
Based on the analysis and summary of the features of existing STL (Stereolithography) model slicing algorithms, the STL model slicing algorithm that based on dynamic adjacent edge is proposed. According to the Z-max and Z-min of the Z-coordinate projection in the slice direction and the thickness of the every layer, achieving slicing the whole STL model, and the topological relation of the adjacent...
Applications in computer network security, social media analysis, and other areas rely on analyzing a changing environment. The data is rich in relationships and lends itself to graph analysis. Traditional static graph analysis cannot keep pace with network security applications analyzing nearly one million events per second and social networks like Facebook collecting 500 thousand comments per second...
The research methodology of mathematical support of computer-aided design systems has been formulated based on the algebra of algorithms and the mathematical induction. The methodology has been illustrated on the example of the research of the known but slightly complicated Euclidean algorithm.
The code behind dynamic webpages often includes calls to database libraries, with queries formed using a combination of static text and values computed at runtime. In this paper, we describe our work on a program analysis for extracting models of database queries that can compactly represent all queries that could be used in a specific database library call. We also describe our work on parsing partial...
Species distribution modeling (SDM) calculates a species’ probabilistic distribution by combining Environmental raster layers with species datasets. Such models can help to answer complex questions in Ecology/Biology/Health, e.g., by calculating impacts of climate changes in Biodiversity, or the potential for a disease spread (vectors’ modeling). Machine learning is largely applied in SDM, being the...
GPUs are commonly used as coprocessors to accelerate a compute-intensive task, thanks to their massively parallel architecture. There is study into different abstract parallel models, which allow researchers to design and analyse parallel algorithms. However, most work on analysing GPU algorithms has been software based tools for profiling a GPU algorithm. Recently, some abstract GPU models have been...
The maximum power available from a photovoltaic (PV) generator in many grid connected systems is extracted using a dc-dc step up converter that implements a maximum power point tracking (MPPT) algorithm. Traditional MPPT algorithms are iterative, continuously searching for the maximum power point (MPP) under varying weather conditions. Due to the nonlinear time-varying nature of commonly used MPPT...
Software fault prediction models are employed to optimize testing resource allocation by identifying fault-prone classes before testing phases. We apply three different ensemble methods to develop a model for predicting fault proneness. We propose a framework to validate the source code metrics and select the right set of metrics with the objective to improve the performance of the fault prediction...
Social networks have become one of the most important research platforms in the big data era. Modelling social networks enables researchers and engineers to understand and analyze their intrinsic properties thereby implementing their real applications. A number of studies on social network modelling focus on a few characteristics, such as the number of edges (i.e., two-star motifs), scale-free degree...
Fault localization defines information models from raw runtime information as the input, depicting program behaviors for supporting localization algorithms. It is natural that an elaborate information model is desirable and likely to improve the effectiveness of fault localization, because it typically depicts subtle and more program runtime behaviors. In fact, much work on fault localization assumes...
Negotiation diagrams are a model of concurrent computation akin to workflow Petri nets. Deterministic negotiation diagrams, equivalent to the much studied and used free-choice workflow Petri nets, are surprisingly amenable to verification. Soundness (a property close to deadlock-freedom) can be decided in PTIME. Further, other fundamental questions like computing summaries or the expected cost, can...
Development problems of the information systems analysis and design for monitoring the status of large-scale infrastructural objects in the categorical models systems have been considered at this article. The formal apparatus of a multilevel knowledge representation on the basis of the categorical approach, the theory of computational models, knowledge representation production systems was described...
There has been increasing interests in processing large-scale real-world graphs, and recently many graph systems have been proposed. Vertex-centric GAS (Gather-Apply-Scatter) and Edge-centric GAS are two graph computation models being widely adopted, and existing graph analytics systems commonly follow only one computation model, which is not the best choice for real-world graph processing. In fact,...
With the emerging vehicular network and the possible diverse applications, Intelligent Transportation Systems (ITS) have been evolving to Cooperative ITS (C-ITS, CITS) with connected intelligent vehicles, and the topics in this domain also raise more and more research interesting recently. However, subjecting to the immaturity of V2X communication technology and the deployment of intelligent vehicles...
In the past decade, online news consumption has been steadily growing. New articles are published every few minutes, and user preferences are also constantly changing. Traditional recommender systems update model at regular intervals, which cannot adjust recommendation list dynamically according to the changes of user preferences. In this paper, we propose a hybrid recommendation model which contains...
We present an in situ visualization framework to capture comprehensive details of vortex dynamics in superconductor simulations. Vortices, which determine all electromagnetic properties of type-II superconductors, are extracted and tracked at the same time with GPU-based time-dependent Ginzburg-Landau superconductor simulations. The in situ workflow involves three parts: (1) a tightly coupled GPU-accelerated...
SkillsRec recommender (Skills based Recommender) is a novel Latent Semantic Analysis model driven recommendation system for online Personal Learning Environments that develops skill-similarity based user-user recommendations through semantically analyzing teacher-competencies and learner-interests. The recommender provides a solution to the inherent, massive and exponentially increasing information-overload...
Scalability is a major challenge for existing behavioral log analysis algorithms, which extract finite-state automaton models or temporal properties from logs generated by running systems. In this paper we present statistical log analysis, which addresses scalability using statistical tools. The key to our approach is to consider behavioral log analysis as a statistical experiment.Rather than analyzing...
Analyzing performance and understanding the potential best-case, worst-case and distribution of program execution times are very important software engineering tasks. There have been model-based and program analysis-based approaches for performance analysis. Model-based approaches rely on analytical or design models derived from mathematical theories or software architecture abstraction, which are...
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