Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in comparison with existing SVM algorithms.
The graphic privacy feature is one of the most important specifications for the existence of any type of design achievements alike, which is one of the graphic products with its multiple data, and from here the current research investigates the graphic privacy of vector graphics design with all its technical descriptions and concepts associated with it and the possibility of achieving it to the best that it should be from Where its formal structure in children's publications, where the structural structure of the current research came from the first chapter, which contained the research problem, which came according to the following question: What is the graphic privacy in the design of vector graphics in children's publ
... Show MoreBig data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
... Show MoreThis work presents an approach to deal with modelling a decision support system framework to introduce an application for decisions in medical knowledge system analysis. First aid is extremely important worldwide and, hence, a decision support framework, know as First Aid Decision Support System (FADSS), was designed and implemented to access experimental cases exerting danger to the general population, offering advanced conditions for testing abilities in research and arranging an emergency treatment through the graphical user interface (UI). The design of first aid treatment in FADSS depends on the general cases in first aid. We presented a strategy to manage first aid treatment by modelling an application (FADSS) that assists pe
... Show MoreBusiness incubator is a new effective mechanism in developing small projects through its introductions of a new integral system of services. It aims at supporting and developing making new projects. Hence, there is a big number of factors that are interrelated in the processes of preparation for those projects. Those factors are: organizing the incubator and the market available for the projects attached to them and the work programs which will have to be implemented. Those small projects represent more than 98% of the total work institutions in the world. Also it has become responsible for a ration reaching half of the national output of those countries. These projects have created between 40 to 80% of job opportunities availabl
... Show MoreIn this study, the concept of fuzzy α-topological vector space is introduced by using the concept fuzzy α-open set , some properties of fuzzy α-topological vector spaces are proved .We also show that the space is -space iff every singleton set is fuzzy α- closed .Finally, the convex property and its relation with the interior points are discussed.
Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration p
... Show MoreRegistration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration process by de
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