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Role and Support of Image Processing in Big Data
Published in Ankur Dumka, Alaknanda Ashok, Parag Verma, Poonam Verma, Advanced Digital Image Processing and Its Applications in Big Data, 2020
Ankur Dumka, Alaknanda Ashok, Parag Verma, Poonam Verma
In the relational database, a relation is a set of tuples with the same attributes or fields. Thus, a tuple defines an object and its information, whereas a domain is a set of possible values for given attributes and hence can be considered as a constraint on values of attributes. Relational algebra consists of a set of tuples with five sets of operations, that is, as union, intersection, joining, projection, and selection, where union combines the tuples of two relations by removing the redundant tuples from the relation while intersection produces a combined result of tuples that share some relationship in common. The joint operation is the Cartesian product of two relations restricted by the same join criteria, whereas the projection operation is used for extracting useful information or attributes from tuples. Selection operation is used for selecting some tuples from the relation or table by limiting the results which fulfill the criteria. A mathematical space can be defined as a set assigned with added structure.
Remote Sensing
Published in Julio Sanchez, Maria P. Canton, William Perrizo, Space Image Processing, 2018
Julio Sanchez, Maria P. Canton
An important feature of a GIS query system is that it supports numerical or discrete operations. For example, the imaginary GIS that produced the layered images in Figure 1.5 could answer questions such as: how many miles of paved county roads are in the image area? or how many acres are planted to corn and how many to wheat? One limitation of this type of query is that the query tools that have been developed for raster databases do not compare to those available for their relational counterpart. In this sense there is no raster algebra equivalent to the well-defined relational algebra used in conventional databases, and no structured query language (SQL) has been defined for operating on a raster database. Virtually every vendor of a GIS product creates its own methods for manipulating and processing raster data and for query processing in this environment. Nevertheless, data analysis facilities are available, to varying degrees of power and refinement, in all mature GIS products. The description of analytical methods and operations presented in the sections that follow refer to those most generally used in PC-based GIS.
Multimodal Route Planning
Published in Hassan A. Karimi, Advanced Location-Based Technologies and Services, 2016
For a mode graph G1 ∈ GM, V1′ is the set of plug vertices in G1 if V1′ = {v|v ∈ σmf=m1 (Γ).vf}, and the set of socket vertices if V1′ = {v|v ∈ σmf=m1 (Γ).vf}, where σ is the selection operation in relational algebra. A graph with plug–socket vertices is illustrated in Figure 4.5. It should be noted that the analogy between plug–socket and the vertex pair within a switch point implies that the connection from a plug to a socket vertex is directional.
Development of a worldwide ferry safety database utilizing relational database approach
Published in Journal of Transportation Safety & Security, 2019
Siyu Xu, Hao Hu, Roberta Weisbrod
The relational database, first defined by Codd (1970), has been the predominant type of database for many years. The fundamental concept behind relational databases is that they break up data sets into individual pieces or subsets of data. Each subset of the data will have a theme that logically binds the data records and that subset together, that is, organizing the data set into smaller themed tables that correlate with each other. In mathematical terms, the relational database technology takes advantage of the set theory and the relational algebra that help it provide better data storage solution, including easy retrieval, easy updating, data consistency, space efficiency, and so on.
Interactive Visual Exploration of Big Relational Datasets
Published in International Journal of Human–Computer Interaction, 2023
Katerina Vitsaxaki, Stavroula Ntoa, George Margetis, Nicolas Spyratos
We can query a context using one of two types of queries, namely simple queries, and analytic queries. Their definition relies on the functional algebra defined earlier. These two types of queries are the counterparts of relational algebra expressions and group-by queries of SQL, respectively.
Bi-Objective Optimization Method for Horizontal Fragmentation Problem in Relational Data Warehouses as a Linear Programming Problem
Published in Applied Artificial Intelligence, 2018
Mohamed Barr, Kamel Boukhalfa, Karima Bouibede
In our case regarding the optimization of a workload based on the relational algebra, using the properties of sets allowed us to transform decisional queries in linear forms depending on the decision variables expressing the simple predicates of selection.