Nowad ays, with the development of internet communication that provides many facilities to the user leads in turn to growing unauthorized access. As a result, intrusion detection system (IDS) becomes necessary to provide a high level of security for huge amount of information transferred in the network to protect them from threats. One of the main challenges for IDS is the high dimensionality of the feature space and how the relevant features to distinguish the normal network traffic from attack network are selected. In this paper, multi-objective evolutionary algorithm with decomposition (MOEA/D) and MOEA/D with the injection of a proposed local search operator are adopted to solve the Multi-objective optimization (MOO) followed by Naïve Bayes (NB) classifier for classification purpose and judging the ability of the proposed models to distinguish between attack network traffic and normal network traffic. The performance of the proposed models is evaluated against two baseline models feature vitality based reduction method (FVBRM) and . The experiments on network security laboratory-knowledge discovery and data mining (NSL-KDD) benchmark dataset ensure the ability of the proposed MOO based models to select an optimal subset of features that has a higher discriminatory power for discriminating attack from normal over the baselines models. Furthermore, the proposed local search operator ensures its ability to harness the performance of MOO model through achieving an obvious feature reduction on average from 16.83 features to 8.54 features (i.e., approximately 50%) in addition to the increase in classifier accuracy from 98.829 to 98.859 and detection rate from 98.906 to 99.043.
This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).
Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so
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Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak
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In this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational req
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On 2-9th April 2001 the Energetic and Relativistic Nuclei and Electron (ERNE) instrument on the Solar and Heliospheric Observatory (SOHO) observed three gradual solar energetic particle (SEP) events separated by 9 hour and 7days respectively, in association with three effective solar flares and coronal mass ejections (CMEs).
In this paper, a study of MESEP events was considered. As the definition of this phenomenon suggested there might be many sources for each MESEP event. This event has been examined in order to view the different sources that might relate to suspected accelerator of the SEPs. A careful analysis for the spectra and associated emission with such eruptions was made. Soft X-ray emission was observed by the Geostationar
On 2-9th April 2001 the Energetic and Relativistic Nuclei and Electron (ERNE)
instrument on the Solar and Heliospheric Observatory (SOHO) observed three
gradual solar energetic particle (SEP) events separated by 9 hour and 7days
respectively, in association with three effective solar flares and coronal mass
ejections (CMEs).
In this paper, a study of MESEP events was considered. As the definition of this
phenomenon suggested there might be many sources for each MESEP event. This
event has been examined in order to view the different sources that might relate to
suspected accelerator of the SEPs. A careful analysis for the spectra and associated
emission with such eruptions was made. Soft X-ray emission was obse
In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-
... Show MoreIn this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r
... Show MoreThe Tigris River in Iraq is of highly meandering in several of its parts. So, the largest meandering inside Baghdad City, is in Al-Jadriyah. During its course, the Tigris Riverbanks are facing erosion frequently due to alteration in the geomorphological and hydrological characteristics affecting the river channel. The entire length of Tigris River from the northern entrance of Baghdad to the convergence with Diyala River at southern of Baghdad is about 49 km length. The Tigris River is suffering from the erosion, deposition, and migration conditions. The river migration was found as maximum in the left bank at the side of the University, and lesser in the right bank in the opposite side, Dora. The aim of this study is to measure the magn
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