The vast amount of data available over the distributed infrastructure of the Web has initiated the development of techniques for their representation, storage and usage. One of these techniques is the Linked Data paradigm, which aims to provide unified practices for publishing and contextually interlinking data on the Web, by using the World Wide Web Consortium (W3C) standards and the Semantic ...

Big data is a collection of massive and complex data sets that include the huge quantities of data, social media analytics, data management capabilities, real-time data. Big data analytics is the process of examining large amounts of data. Big Data is characterized by the dimensions volume, variety, and velocity, while there are some wellestablished methods for big data processing such as Hadoo...

Management and analysis of streaming data has become crucial with its applications in web, sensor data, network traffic data, and stock market. Data streams consist of mostly numeric data but what is more interesting is the events derived from the numerical data that need to be monitored. The events obtained from streaming data form event streams. Event streams have similar properties to data s...

BACKGROUND Little has been done to investigate the application of injury specific qualitative research methods in the field of burn injuries. The aim of this study was to use an analytical tool (Haddon's matrix) through qualitative research methods to better understand people's perceptions about burn injuries. METHODS This study applied Haddon's matrix as a framework and an analytical tool fo...

Public sector bodies hold a significant amount of data that might be of potential interest to citizens and businesses. However the re-use potential of this data is still largely untapped because the data is not always published in a way that would allow its easy discovery, understanding and re-use. Open Government Data (OGD) initiatives aim at increasing availability of machine-readable data pr...

In the process of production, some of the inputs are fixed and cannot easily be changed, such as work hours of workers and hours of administrative or work, these types of inputs are fixed and others are variables. In this paper, by considering some inputs or outputs which are limited, their amounts must be integrated; this concept for integer data is extended. We show the importance of subject ...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

Data Envelopment Analysis (DEA) is a nonparametric approach for measuring the relative efficiency of a decision making units consists of multiple inputs and outputs. In all standard DEA models semi positive real valued measures are assumed, while in some real cases inputs and outputs may take complex valued. The question is related to measuring efficiency in such cases. As far as we are aware, ...