Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

Background: Few updated retrospective histopathological-based studies in Iraq evaluate a comprehensive spectrum of oro-maxillofacial lesions. Also, there was a need for a systematic way of categorizing the diseases and reporting results in codes according to the WHO classification that helps occupational health professionals in the clinical-epidemiological approach.

Objectives: to establish an electronic archiving database according to the ICD-10 that encompasses oro-maxillofacial lesions in Sulaimani city for the last 12 years, then to study the prevalence trend and correlation with clinicopathological parameters.

Subjects and Methods:  A descri

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

The aim of this research is to study the influence of additives on the properties of soap greases, such as lithium, calcium, sodium, lithium-calcium grease, by adding varies additives, such as graphite, molybdenum disulfide, carbon black, corrosion inhibitor, and extreme pressure.
These additives have been added to grease to obtain the best percentages that improve the properties of grease such as load carrying, wear resistance, corrosion resistance, drop point, and penetration.
The results showed the best weight percentages to all types of grease which give good properties are 1.5% extreme pressure additive, 3% graphite, 1% molybdenum disulfide, 2.5% carbon black.
The other hand, the best weight percentage for corrosion inhibit

In this study, a theoretical scenario has been used to calculate the electronic current in sensitizer N3 molecule contact to TiO2 semiconductor for electrons in functional solar cells. It is known to play an important role on the compute the eficiency of solar cell. Some parameters of electronic current such as the transition energy, driving force energy, barrier height coupling overlapping values are determined. Transition energy is a necessary parameter to calculate the electronic current in solar cell with using wide polarity solvents Acetic acid, 2-Methoxyethanol, 1-Butanol, Methyl alcohol, chloroform, N,N-Dimethylacetamide and Ethyl alcohol via the quantum donor-acceptor system. Here, we show the results of transition energy can be var

(3) (PDF) Theoretical calculation of the electronic current at N3 contact with TiO2 solar cell devices. Available from: https://www.researchgate.net/publication/362780274_Theoretical_calculation_of_the_electronic_current_at_N3_contact_with_TiO2_solar_cell_devices [accessed May 01 2023].

In this study, investigations of structural properties of n-type porous silicon prepared by laser assisted-electrochemical etching were demonstrated. The Photo- electrochemical Etching technique, (PEC) was used to produce porous silicon for n-type with orientation of (111). X-ray diffraction studies showed distinct variations between the fresh silicon surface and the synthesized porous silicon surfaces. Atomic force microscopy (AFM) analysis was used to study the morphology of porous silicon layer. AFM results showed that root mean square (RMS) of roughness and the grain size of porous silicon decreased as etching current density increased. The chemical bonding and structure were investigated by using fourier transformation infrared spec