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.
There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja
Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS
... Show MoreIntroduction: In recent decades, the endovascular treatment of cerebral arteriovenous malformations (AVMs) has advanced. However, it still carries risks of unanticipated complications. Coil migration is a reported complication of aneurysmal coiling procedures. Herein, we report a case of early intraprocedural coil migration during pressure cooker technique embolization of right thalamic AVM, discussing the management and potential explanations. The literature showed no report of coil migration after the pressure cooker technique in the form of coil-augmented Onyx injection technique (CAIT). Case description: An otherwise healthy 26-year-old female suddenly developed a severe headache with no loss of consciousness. Computed tomograp
... Show MoreClimate change is one of the global issues that is receiving wide attention due to its clear impact on all living organisms. This is essential for Iraq since it was classified as the fifth most vulnerable country to climate change. One of the manifestations of these changes in Iraq is the increasing frequency and severity of dust storms. In this study, the Normalized Difference Dust Index (NDDI) spectral index for Moderate Resolution Imaging Spectroradiometer (MODIS) sensor bands was used to measure and track the dust storm that occurred on May 16, 2022, as well as to test the validity of one of the daily products of this sensor, MOD11A1, to measure surface temperature and emissivity before and after the storm. It was found that the MOD0
... Show MoreIn this work the parameters of plasma (electron temperature Te,
electron density ne, electron velocity and ion velocity) have been
studied by using the spectrometer that collect the spectrum of
plasma. Two cathodes were used (Si:Si) P-type and deposited on
glass. In this research argon gas has been used at various values of
pressures (0.5, 0.4, 0.3, and 0.2 torr) with constant deposition time
4 hrs. The results of electron temperature were (31596.19, 31099.77,
26020.14 and 25372.64) kelvin, and electron density (7.60*1016,
8.16*1016, 6.82*1016 and 7.11*1016) m-3. Optical properties of Si
were determined through the optical transmission method using
ultraviolet visible spectrophotometer with in the range
(
Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.