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Traffic monitoring is an essential task for network operators since it allows evaluating network performance. Monitoring data from origin-destination (OD) traffic in core virtual network topologies can be collected from packet nodes and stored in a repository for further analysis, e.g., to detect anomalies or to create predicted traffic matrices for the near future. In this paper we propose a set...
Traffic anomalies can create network congestion, so its prompt and accurate detection would allow network operators to make decisions to guarantee the network performance avoiding services to experience any perturbation. In this paper, we focus on origin-destination (OD) traffic anomalies; to efficiently detect those, we study two different anomaly detection methods based on data analytics and combine...
Large-scale power failures induced by severe weather have become frequent and damaging in recent years, causing millions of people to be without electricity service for days. Although the power industry has been battling weather-induced failures for years, it is largely unknown how resilient the energy infrastructure and services really are to severe weather disruptions. What fundamental issues govern...
Modeling human mobility paerns from CDR(Call Detail Record)data is an ecient way to understand the eects of human movementson transportation, society and the environment. Previoushuman mobility models are focused on single cellphone networkCDR data. In the poster, we present a framework to model humanmobility paerns on CDR data from multiple cellphone networks.Based on data analysis from multiple...
Near-infrared spectroscopy (NIRS) is a rapid, chemical-free, easy to use, and non-destructive analytical technique that has been widely applied to a diverse range of fields. NIRS analyzes the investigated samples through their NIR spectra. However, NIR spectral data are complex and multivariate, so multivariate data analysis methods (chemometrics) are used to interpret and predict the spectra's chemical...
Curriculum design and implementation in higher medical education can be a great challenge. Although there are well-defined standards, such as the Curriculum Inventory and Competency Framework by MedBiquitous Consortium, existing systems are incapable of a visual representation of the various components, attributes, and relations. In this paper, we present the MEDCIN platform, a pilot tool which uses...
Data query comparison of large data should process a large number of datasets, which is the core for basic research projects. In the selection of analysis factors, how to choose a better way to provide data analysis library can be very helpful for quickly analysis and search comparison. In this study, we try to design and study, improve the speed of data query and comparison in big datasets, and find...
The aim of this paper is to examine possibilities for the initial data analyses of the failure data from industrial production process. To perform the initial data analysis of the data from production process we have used graphical statistical method and also data mining methods like drill-down analysis and cluster analysis. Before applying mentioned techniques and methods it was necessary to know...
This paper proposes a framework for assessing the sensitivity of the performance of a hypothetical demand response (DR) program to consumers' preferences, should they enable DR and become prosumers. The proposed framework contains a data analytics module and a DR simulation module. The data analytics module, processes the historical data to select informative subsets and define simulation scenarios...
Over time, software development organizations have been interested into the implementation of best practices that facilitate the improvement of its software processes with the firm purpose of improving products quality. One of the best approaches to improve software processes is to adopt a Software Process Improvement (SPI) initiative, which evaluates current practices and the way software products...
The most widely adopted approach for knowledge extraction from raw data generated at the edges of the Internet (e.g., by IoT or personal mobile devices) is through global cloud platforms, where data is collected from devices, and analysed. However, with the increasing number of devices spread in the physical environment, this approach rises several concerns. The data gravity concept, one of the basis...
This paper addresses detecting taint-style vulnerabilities in PHP code. It extends classical taint-style model with an element called “cleans”, which is used to specify sanitation routines. Based on the new model, a static backward taint data analysis method is proposed to detecting taint-style vulnerabilities. This method includes four key steps, first of which is collecting sinks and constructing...
The OLAP (Online Analytical Processing) system built on data warehouse is the main tool for massive data analysis. With the development of information technology, multidimensional data grows rapidly and data structure becomes more and more complicated, so the performance of OLAP system has dopped severely, failing to satisfy the demand of data analysis. The paper proposes a new method to store large-scale...
Recent technological advancements in typical domains (e.g. internet, financial companies, health care, user generated data, supply chain systems etc.) have directed to inundate of data from these domains. Data outburst trend gave the insight meaning to the buzz word ‘Bigdata’. If we compare with traditional data, Bigdata exhibits some unique characteristics like it is commonly enormous and unstructured...
Today, there is a steep rise in the amount of data being collected from diverse applications. Consequently, data analytic workloads are gaining popularity to gain insight that can benefit the application, e.g., financial trading, social media analysis. To study the architectural behavior of the workloads, architectural simulation is one of the most common approaches. However, because of the long-running...
Data privacy is a key challenge that is exacerbated by Big Data storage and analytics processing requirements. Big Data and Cloud Computing are related and allow the users to access data from any device, making data privacy essential as the data sets are exposed through the web. Organizations care about data privacy as it directly affects the confidence that clients have that their personal data are...
Film data analysis is important for website to find relationship between film data. Other than normal relational database, a novel and popular graph database, Neo4j uses graph related concepts to describe data models, the data can easily be nodes, edges and their associated attributes. By focusing on film data, Neo4j-based analysis is conducted in this paper. Firstly, Neo4j and Cypher Query Language...
In recent years Internet of Things has been among the hot topics of research in the field of computing and information technology. It has enabled thousands of connected devices including sensors, cell phones and daily home appliances to store data for various useful purposes. The amount of data generated by IoT devices is huge, and there is a need to analyze IoT data for prospective uses. Heterogeneity...
Multi-step scientific workflows have become prominent and powerful tools of data-driven scientific discovery. Run-time analytic techniques are now commonly used to mitigate the performance effects of using parallel file systems as staging areas during workflow execution. However, workflow construction and deployment for extreme-scale computing is still largely an ad hoc process with uneven support...
The avionics system is an important part of modern fighters, and the analysis and processing of large data generated by the avionics system can provide some guidance for the pilot's decision-making. After analyzing the existing distributed framework, a multi-platform avionics data system is designed and implemented to solve the problem that heterogeneous real-time data generated by a large number...
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