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Aspect Categorization Using Domain-Trained Word Embedding and Topic Modelling
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Aspect-based sentiment analysis is the most important research topic conducted to extract and categorize aspect-terms from online reviews. Recent efforts have shown that topic modelling is vigorously used for this task. In this paper, we integrated word embedding into collapsed Gibbs sampling in Latent Dirichlet Allocation (LDA). Specifically, the conditional distribution in the topic model is improved using the word embedding model that was trained against (customer review) training dataset. Semantic similarity (cosine measure) was leveraged to distribute the aspect-terms to their related aspect-category cognitively. The experiment was conducted to extract and categorize the aspect terms from SemEval 2014 dataset.

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Feature Extraction of Human Facail Expressions Using Haar Wavelet and Neural network
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One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural networ

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Engineering
Analysis of Shell and Double Concentric Tube Heat Exchanger Using CFD Application
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This study focuses on CFD analysis in the field of the shell and double concentric tube heat exchanger. A commercial CFD package was used to resolve the flow and temperature fields inside the shell and tubes of the heat exchanger used. Simulations by CFD are performed for the single shell and double concentric tube.

This heat exchanger included 16 tubes and 20 baffles. The shell had a length of 1.18 m and its diameter was 220 mm. Solid Works 2014, ANSYS 15.0 software was used to analyze the fields of flow and temperature inside the shell and the tubes. The RNG k-ε model was used and it provided good results. Coarse and fine meshes were investigated, showing that aspect ratio has no significant effect. 14 million

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
An Efficient Image Encryption Using a Dynamic, Nonlinear and Secret Diffusion Scheme
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The growing use of tele

This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe

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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Design and Implementation for optical fiber communication system using frequency shift coding
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In this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system a

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Publication Date
Sun Jun 03 2018
Journal Name
Baghdad Science Journal
Synthesis, Spectroscopic Characterization of Cobalt ComplexfromC16H19N3O3S and photodegradation using prepared Nano TiO2catalyst
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Coblatcomplex has been prepared by reaction between C16H19N3O3S (L) as ligand and metal salt (II). The prepared complex were characterized by infrared spectra, electromic spectra, magnetic susceptibility, molar conductivity measurement and metal analysis by atomic absorption and (C.H.N) analysis. From these studies tetrahedral geometry structure for the complex was suggested. The photodegredation of complex were study using photoreaction cell and preparednanoTiO2 catalyst in different conditions (concentration, temperatures, pH).The results show that the recation is of a first order with activation energy equal to (6.6512 kJ /mol).

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Publication Date
Sun Mar 02 2008
Journal Name
Baghdad Science Journal
Spectrophotometric determination of Procaine penicillin in pure and pharmaceutical formulations using metol
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A simple, accurate and sensitive spectrophotometric method for the determination of Procaine penicillin (PP) is described. The method is based on charge-transfer reaction of PP with metol (N-methyl-p-hydroxy aniline) in the presence of ferric sulphate to form a purple-water soluble complex ,which is stable and has a maximum absorption at 510 nm .A graph of absorbance versus concentration shows that Beer’s low is obeyed over the concentration range of 3-80 µg /ml of PP (i.e.,3-80 ppm) with a molar absorbativity of 4.945 ×103 L.mol-1.cm-1 ,Sandell sensitivity of 0.1190 µg cm-2 ,a relative error of (-1.57)-2.79 % and a standard deviation of less than 0.59 depending on the concentration of PP.The optimum conditions for full co

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Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
ON-Line MRI Image Selection and Tumor Classification using Artificial Neural Network
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When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
An Automated Classification of Mammals and Reptiles Animal Classes Using Deep Learning
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Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

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Publication Date
Thu Sep 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
USING ALUMINUM REFUSE AS A COAGULANT IN THE COAGULATION AND FLIOCCULATION PROCESSES
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The present work aims to study the efficiency of using aluminum refuse, which is available locally (after dissolving it in sodium hydroxide), with different coagulants like alum [Al2 (SO4)3.18H2O], Ferric chloride FeCl3 and polyaluminum chloride (PACl) to improve the quality of water. The results showed that using this coagulant in the flocculation process gave high results in the removal of turbidity as well as improving the quality of water by precipitating a great deal of ions causing hardness. From the experimental results of the Jar test, the optimum alum dosages are (25, 50 and 70 ppm), ferric chloride dosages are (15, 40 and 60 ppm) and polyaluminum chloride dosages were (10, 35 and 55 ppm) for initial water turbidity (100, 500 an

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