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jcoeduw-1361
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.

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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Quantitative Determination of Fluoroquinolones in Contaminated Soils by HPLC with Solid-Phase Extraction
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This work reports the development of an analytical method for the simultaneous analysis of three fluoroquinolones; ciprofloxacin (CIP), norfloxacin (NOR) and ofloxacin (OFL) in soil matrix. The proposed method was performed by using microwave-assisted extraction (MAE), solid-phase extraction (SPE) for samples purification, and finally the pre-concentrated samples were analyzed by HPLC detector. In this study, various organic solvents were tested to extract the test compounds, and the extraction performance was evaluated by testing various parameters including extraction solvent, solvent volume, extraction time, temperature and number of the extraction cycles. The current method showed a good linearity over the concentration ranging from

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Publication Date
Mon Jan 02 2017
Journal Name
Journal Of Educational And Psychological Researches
The effectiveness of the structural model of learning in the acquisition of geographical concepts among students of the first grade average)
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The current research aims to find out ( the effectiveness of the structural model of learning in the acquisition of geographical concepts at the first grade average students ) , and achieving the goals of research has been formulating the null hypothesis of the following :

    " There is no difference statistically significant when Mistoi (0.5 ) between the mean scores of the collection of students in the experimental group that is studying the general geographical principles " Bonmozj constructivist learning " and the mean scores of the control group , which is considering the same article ," the traditional way " to acquire concepts.

The researcher adopted th

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Designing and Synthesising Novel Benzophenone Biscyclic Imides Comprising Drug Moity with Investigating their Antimicrobial Activity
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The present work involved designing and synthesizing of a series of new. compounds which their molecules are composed from two biologically active components namely sulfamethoxazole or β-lactam containing drugs and cyclic imides. The target new compounds were synthesized by two steps in the first one a series of six bis (N-drug phthalamic acid_4-yl) ketone (1-6) were prepared from the reaction of sulfamethoxazole or β-lactam containing drugs with benzophenone 3, 3′, 4, 4′ -tetracarboxylic dianhydride.

In the second step, compounds (1-6) were introduced in dehydration reaction via fusion process producing the target compounds bis (N-drug phthalimidyl-4-yl) ketone (7-12). The antibacterial and antifungal high

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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
Extraction of Bovine Serum Albumin by Aqueous Two-Phase System Using PEG4000/Sodium Citrate and PEG8000/Sodium Phosphate
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Aqueous Two Phase System (ATPS) or liquid-liquid extraction is used in biotechnology to recover valuable compounds from raw sources. In Aqueous Two-Phase Systems, many factors influence the Partition coefficient, K, (which is the ratio of protein concentration in the top phase to that in the bottom phase) and the Recovery percentage (Rec%). In this research, two systems of ATPS were used: first, polyethylene glycol (PEG) 4000/Sodium citrate (SC), and the second, PEG8000/ Sodium phosphate (SPH), for the extraction of Bovine Serum Albumin (BSA). The behavior of Rec% and K of pure (BSA) in ATPS has been investigated throughout the study by the effects of five parameters: temperature, concentration of polyethylene glycol (P

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Publication Date
Tue Feb 27 2024
Journal Name
Tem Journal
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
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Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Publication Date
Wed Aug 15 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Simulation investigations of Micro Flexible Deep Drawing Using Floating Ring Technique
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Micro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Analysis of Temperature and Residual Stress Distribution in CO2 Laser Welded Aluminum 6061 Plates Using FEM
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This paper develops a nonlinear transient three-dimensional heat transfer finite element model and a rate independent three-dimensional deformation model, developed for the CO2 laser welding simulations in Al-6061-T6 alloy. Simulations are performed using an indirect coupled thermal-structural method for the process of welding. Temperature-dependent thermal properties of Al-6061-T6, effect of latent heat of fusion, and the convective and radiative boundary conditions are included in the model. The heat input to the model is assumed to be a Gaussian heat source. The finite element code ANSYS12, along with a few FORTRAN subroutines, are employed to obtain the numerical results. The benefit of the proposed methodology is that it

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