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Study Effects of Illumination and Temperature on Performance of (pn-Si) Device using Simulation Program SCAPS-1D

The current research included obtaining the best performance specifications for a silicon device with a mono-crystalline type pn junction (pn–Si). A simulation of the device was performed by the use of a computer program in one dimension SCAPS-1D in order to reach the optimum thickness for both p and n layers and to obtain the best efficiency in performance of the pn-Si junction. The optimum device efficiency was eta (η) = 12.4236 % when the ideal thickness for the p and n layers was 5µm and 1.175µm, respectively (p=5 µm and n=1.75µm).

     The research included studying the effects of different spectra of solar illumination using simulation of the device; the usual solar spectrum AM1_5 G1 sun. Spectrum, Black body spectrum, White spectrum constant photon flux, White spectrum constant photon power, Monochromatic spectrum constant flux, and Monochromatic spectrum constant power. The highest efficiency was obtained from the monochrome spectrum with constant power (eta (η) =22.4338 %). The effects of different temperatures on the device was studied on 250K, 300K, 350K, 400K, and 450K. The highest efficiency was revealed for Monochromatic spectrum constant power (eta (η) =24.5381 %) when the temperature was 250K.

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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Intrusion Detection System Using Data Stream Classification

Secure data communication across networks is always threatened with intrusion and abuse. Network Intrusion Detection System (IDS) is a valuable tool for in-depth defense of computer networks. Most research and applications in the field of intrusion detection systems was built based on analysing the several datasets that contain the attacks types using the classification of batch learning machine. The present study presents the intrusion detection system based on Data Stream Classification. Several data stream algorithms were applied on CICIDS2017 datasets which contain several new types of attacks. The results were evaluated to choose the best algorithm that satisfies high accuracy and low computation time.

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
Visible image watermarking using biorthogonal wavelet transform

In this paper, visible image watermarking algorithm based on biorthogonal wavelet
transform is proposed. The watermark (logo) of type binary image can be embedded in the
host gray image by using coefficients bands of the transformed host image by biorthogonal
transform domain. The logo image can be embedded in the top-left corner or spread over the
whole host image. A scaling value (α) in the frequency domain is introduced to control the
perception of the watermarked image. Experimental results show that this watermark
algorithm gives visible logo with and no losses in the recovery process of the original image,
the calculated PSNR values support that. Good robustness against attempt to remove the
watermark was s

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Publication Date
Thu Sep 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
TREATING THE USED AUTOMOBILES OILS USING SOLVENTS

Used automobile oils were subjected to filtration to remove solid material and dehydration to remove water, gasoline and light components by using vacuum distillation under moderate pressure, and then the dehydrated waste oil is subjected to extraction by using liquid solvents. Two solvents, namely n-butanol and n-hexane were used to extract base oil from automobile used oil, so that the expensive base oil can be reused again.
The recovered base oil by using n-butanol solvent gives (88.67%) reduction in carbon residue, (75.93%) reduction in ash content, (93.73%) oil recovery, (95%) solvent recovery and (100.62) viscosity index, at (5:1) solvent to used oil ratio and (40 oC) extraction temperature, while using n-hexane solvent gives (6

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
Plants Leaf Diseases Detection Using Deep Learning

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Optical Character Recognition Using Active Contour Segmentation

Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could b

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Publication Date
Wed Nov 27 2019
Journal Name
Iraqi Journal Of Science
Watermarking in 3D Models Using Depth Path

This paper presents a 3D watermarking model based on the nearest distance between two vertices in mesh, where the embedding path moves as deep as possible until the embedding data is completed. The proposed algorithm achieved good results according to invisibility and robustness. The visibility was measured in term
of Root Mean Square Error (RMSE) and Hausdroff Distance (HD), which obtained good results. As related to robustness, the proposed method showed resistance to geometrical attack (translation, scaling and rotation) as well as acceptable resistance to signal processing attacks like noise addition and simplification.

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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Desalination by Membrane Distillation Using Electrospun Membranes

Electrospinning is a novel technique that can be used to produce highly porous fibers with highly tunable properties. In this research, this technique is adopted to prepare the electrospun nanofiber membrane for membrane distillation application. A custom-built electrospinning setup was made to prepare the nanofibers membrane. Polyvinylidene fluoride (PVDF) polymer was used in the electrospinning process due to its high hydrophobicity. Electrospun (PVDF) nanofibers were tested in direct contact membrane distillation (DCMD) process using 0.6 M sodium chloride as a feed solution. The resulting nanofiber membrane exhibited high performance in DCMD (i.e. relatively high water flux and high salt rejection). It has been found

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Geolocation Android Mobile Phones Using GSM/UMTS

The proliferation of cellular network enabled users through various positioning tools to track locations, location information is being continuously captured from mobile phones, created a prototype that enables detected location based on using the two invariant models for Global Systems for Mobile (GSM) and Universal Mobile Telecommunications System (UMTS). The smartphone application on an Android platform applies the location sensing run as a background process and the localization method is based on cell phones. The proposed application is associated with remote server and used to track a smartphone without permissions and internet. Mobile stored data location information in the database (SQLite), then transfer it into location AP

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Publication Date
Fri Feb 14 2014
Journal Name
Desalination And Water Treatment
Copper biosorption using local Iraqi natural agents

Industrial effluents loaded with heavy metals are a cause of hazards to the humans and other forms of life. Conventional approaches, such as electroplating, ion exchange, and membrane processes, are used for removal of copper, cadmium, and lead and are often cost prohibitive with low efficiency at low metal ion concentration. Biosorption can be considered as an option which has been proven as more efficient and economical for removing the mentioned metal ions. Biosorbents used are fungi, yeasts, oil palm shells, coir pith carbon, peanut husks, and olive pulp. Recently, low cost and natural products have also been researched as biosorbent. This paper presents an attempt of the potential use of Iraqi date pits and Al-Khriet (i.e. substances l

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Fuzzy-assignment Model by Using Linguistic Variables

      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

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