Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The results illustrate that Euclidean Squared Distance with (UUT) feature provide low error rate and high accuracy compared with the other two types of distances used.
In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.
The aim of this research work is to study the effect of stabilizing gypseous soil, which covers vast areas in the middle, west and south parts of Iraq, using liquid asphalt on its strength properties to be used as a base course layer replacing the traditional materials of coarse aggregate and broken stones which are scarce at economical prices and hauling distances. Gypseous soil brought from Al-Ramadi City, west of Iraq, with gypsum content of 66.65%, medium curing cutback asphalt (MC-30), and hydrated lime are used in this study. The conducted tests on untreated and treated gypseous soil with different percentages of medium curing cutback asphalt (MC-30), water, and lime were: unconfined compression strength, and one dimensional confine
... Show MoreIn this investigation, water-soluble N-Acetyl Cysteine Capped-Cadmium Telluride QDs (NAC/CdTe nanocrystals), utilizing N-acetyl cysteine as a stabilizer, were prepared to assess their potential in differentiating between DNA extracted from pathogenic bacteria (e.g. Escherichia coli isolated from urine specimen) and intact DNA (extracted from blood of healthy individuals) for biomedical sensing prospective. Following the optical characterization of the synthesized QDs, the XRD analysis illustrated the construction of NAC-CdTe-QDs with a grain size of 7.1 nm. The prepared NAC-CdTe-QDs exhibited higher PL emission features at of 550 nm and UV-Vis absorption peak at 300 nm. Additionally, the energy gap quantified via PL and UV–Vis were 2.2 eV
... Show MoreObiovisly that the holy thresholds are directly related to Islam and Muslims and related to the general culture of the Islamic peoples. In terms of architecture, it is considered a distinctive architectural scene that reviews the history of this origin and its architectural styles. Recently, with the increase in the number of pilgrims and visitors to the holy shrines, there is a need to develop and expand the buildings and provide them with services and introduce modern technology. The building of the holy thresholds consists of a number of functional design indicators: The general problem of research is that there is no clear theoretical framework for the design indicators for the development of the holy shrines according to the functio
... Show MoreThis paper presents on the design of L-Band Multiwavelength laser for Hybrid Time Division Multiplexing/ Wavelength Division Multiplexing (TDM/WDM) Passive Optical Network (PON) application. In this design, an L-band Mulltiwavelength Laser is designed as the downstream signals for TDM/WDM PON. The downstream signals ranging from 1569.865 nm to 1581.973 nm with 100GHz spacing. The multiwavelength laser is designed using OptiSystem software and it is integrated into a TDM/WDM PON that is also designed using OptiSystem simulation software. By adapting multiwavelength fiber laser into a TDM/WDM network, a simple and low-cost downstream signal is proposed. From the simulation design, it is found that the proposed design is suitable to be used
... Show MoreCoaxial (wire-cylinder) electrodes arrangements are widely used for electrostatic deposition of dust particles in flue gases, when a high voltage is applied to electrodes immersed in air and provide a strongly non-uniform electric field. The efficiency of electrostatic filters mainly depends on the value of the applied voltage and the distribution of the electric field. In this work, a two-dimensional computer simulation was constructed to study the effect of different applied voltages (20, 22, 25, 26, 28, 30 kV) on the inner electrode and their effect on the efficiency of the electrostatic precipitator. Finite Element Method (FEM) and COMSOL Multiphysics software were used to simulate the cross section of a wire cylinder. The results sh
... Show MoreA novel mixed natural coagulant has been developed to remove sewage pollutants and heavy metals from Qanat- al- Jayesh by using low cost adsorbent natural materials. In these materials, significant interaction contains Arabic gum mixed with extracted silica from rice husk ash (natural coagulants) by the Batch device approach, using two variables, pH values ranging from 5-8 and contact times between 0.25-5 hrs. All wastewater samples were collected after treatment by adsorbents and examined for determination of residual heavy metal concentrations: Pb, Ni, Zn and Cu by atomic absorption spectroscopy (AAS), turbidity, pH, total dissolved salts (TDS), electrical conductivity (EC) and total salinity (TS). The results obtained indicate Th
... Show MoreSoftware-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an
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