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Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusion Detection System (IDS). Success is measured by a variety of metrics, including accuracy, precision, recall, F1-Score, and execution time. Applying feature selection approaches such as Analysis of Variance (ANOVA), Mutual Information (MI), and Chi-Square (Ch-2) reduced execution time, increased detection efficiency and accuracy, and boosted overall performance. All classifiers achieve the greatest performance with 99.99% accuracy and the shortest computation time of 0.0089 seconds while using ANOVA with 10% of features.

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Independent Thermal Network Through Thermal Synergy Between Four Architectural Units
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The manifestations of climate change are increasing with the days: sudden rains and floods, lakes that evaporate, rivers that experience unprecedentedly low water levels, and successive droughts such as the Tigris, Euphrates, Rhine, and Lape rivers. At the same time, energy consumption is increasing, and there is no way to stop the warming of the Earth's atmosphere despite the many conferences and growing interest in environmental problems. An aspect that has not received sufficient attention is the tremendous heat produced by human activities. This work links four elements in the built environment that are known for their high energy consumption (houses, supermarkets, greenhouses, and asphalt roads) according t

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Publication Date
Sun Mar 02 2008
Journal Name
Baghdad Science Journal
Tamper Detection in Color Image
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In this work a fragile watermarking scheme is presented. This scheme is applied to digital color images in spatial domain. The image is divided into blocks, and each block has its authentication mark embedded in it, we would be able to insure which parts of the image are authentic and which parts have been modified. This authentication carries out without need to exist the original image. The results show the quality of the watermarked image is remaining very good and the watermark survived some type of unintended modification such as familiar compression software like WINRAR and ZIP

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Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
Tamper Detection in Text Document
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Although text document images authentication is difficult due to the binary nature and clear separation between the background and foreground but it is getting higher demand for many applications. Most previous researches in this field depend on insertion watermark in the document, the drawback in these techniques lie in the fact that changing pixel values in a binary document could introduce irregularities that are very visually noticeable. In this paper, a new method is proposed for object-based text document authentication, in which I propose a different approach where a text document is signed by shifting individual words slightly left or right from their original positions to make the center of gravity for each line fall in with the m

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
Image Segmentation for Skin Detection
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Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

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Publication Date
Sun Mar 01 2009
Journal Name
Diyala Journal Of Human Research
Stability of the Finite Difference Methods of Fractional Partial Differential Equations Using Fourier Series Approach
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The fractional order partial differential equations (FPDEs) are generalizations of classical partial differential equations (PDEs). In this paper we examine the stability of the explicit and implicit finite difference methods to solve the initial-boundary value problem of the hyperbolic for one-sided and two sided fractional order partial differential equations (FPDEs). The stability (and convergence) result of this problem is discussed by using the Fourier series method (Von Neumanns Method).

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Removal of Ciprofloxacin Antibiotic from Synthesized Aqueous Solution Using Three Different Metals Nanoparticles Synthesized Through the Green Method
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This study investigates the possibility of removing ciprofloxacin (CIP) using three types of adsorbent based on green-prepared iron nanoparticles (Fe.NPs), copper nanoparticles (Cu. NPS), and silver nanoparticles (Ag. NPS) from synthesized aqueous solution. They were characterized using different analysis methods. According to the characterization findings, each prepared NPs has the shape of a sphere and with ranges in sizes from of 85, 47, and 32 nanometers and a surface area of 2.1913, 1.6562, and 1.2387 m2/g for Fe.NPs, Cu.NPs and Ag.NPs, respectively. The effects of various parameters such as pH, initial CIP concentration, temperature, NPs dosage, and time on CIP removal were investigated through batch experiments. The res

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Publication Date
Wed Feb 06 2019
Journal Name
National Academy Science Letters
The Detection Limit of PCR Amplification for Cryptosporidium spp. Oocysts in Fecal Samples
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Publication Date
Thu Jul 01 2004
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
DETECTION OF SUBSURFACE CAVITIES BY THE ELECTROMAGNETIC METHOD (Case Study at Haditha Area)
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Two EM techniques, terrain conductivity and VLF-Radiohm resistivity (using two
different instruments of Geonics EM 34-3 and EMI6R respectively) have been applied to
evaluate their ability in delineation and measuring the depth of shallow subsurface cavities
near Haditha city.
Thirty one survey traverses were achieved to distinguish the subsurface cavities in the
investigated area. Both EM techniques are found to be successfiul tools in study area.

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Publication Date
Mon May 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Screening and optimization of a novel gallic acid and tannase production under semi quantitative and quantitative methods
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Abstract<p>Tannin acyl hydrolase as the common name of tannase is an inducible extracellular enzyme that causes the hydrolysis of galloyl ester and depside bonds in tannins, yielding gallic acid and glucose. The main objective of this study is to find a novel gallic acid and tannase produced by <italic>Acinetobacter Baumannii</italic>. A number of optimization steps were followed in order to improve the highest production of gallic acid and tannase. In present study, <italic>A. baumannii</italic> were isolated from ICU burn. <italic>A. baumannii</italic> was examined by microscopic examination, morphological and biochemical assay including oxidase and catalase. The </p> ... Show More
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Publication Date
Wed Mar 01 2023
Journal Name
Iraqi Journal Of Physics
Design and Construction of a Dust Detection System using Infrared Laser: The Case of Dust Storms in Baghdad in the Summer 2022
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Iraq suffers from serious pollution with harmful particles that have important direct and indirect effects on human activities and human health. In this research, a system for detecting pollutants in the air was designed and manufactured using infrared laser technology. This system was used to detect the presence of pollutants in the dust storms that swept the city of Baghdad which could have a negative impact on human health and living organisms.

The designed detection system based on the use of infrared laser (IR) with a wavelength of 1064 nm was used for the purposes of detecting pollutants based on the scattering of the laser beam from these pollutants. The system was aligned to obtain the best signal for the scattered rays, w

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