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Polluted Water Sensor Based on Carbon Quantum Dots/Alq3 Using Drop Casting and Spin Coating Techniques
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Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of 30 oC. Through the results, it was found that the highest sensitivity of sample 3 to the carbon continuous dot was in the case of the contaminant fructose and was 99.55%, while the highest sensitivity of sample 4 was for the one sensitive to the contaminant (mercury chloride) and was 81. As for sample 1, the highest sensitivity was in the case of detecting the contaminant lead chloride and was 80. The results showed that the best sensor was obtained using a spin-coating technique when the solution sample of CQDs+Alq3 was placed on a silicon slide in fructose and the sensitivity was 200%. This demonstrates the importance of quantum dots in measuring the sensitivity of water pollutants. The thin film thickness was measured to be 500 nm.

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Publication Date
Wed Dec 30 2020
Journal Name
Al-kindy College Medical Journal
A Population-Based Study on Agreement between Actual and Perceived Body Image
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Background: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.

Objective: This study aims to determine the agreement between actual and perceived body image in the general population.

Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10th January 2020 to 21st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition
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There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Implementation of Power System Stabilizer Based on Conventional and Fuzzy Logic Controllers
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To damp the low-frequency oscillations which occurred due to the disturbances in the electrical power system, the generators are equipped with Power System Stabilizer (PSS) that provide supplementary feedback stabilizing signals. The low-frequency oscillations in power system are classified as local mode oscillations, intra-area mode oscillation, and interarea mode oscillations. A suitable PSS model was selected considering the low frequencies oscillation in the inter-area mode based on conventional PSS and Fuzzy Logic Controller. Two types of (FIS) Mamdani and suggeno were considered in this paper. The software of the methods was executed using MATLAB R2015a package.

 

 

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Publication Date
Fri Mar 15 2024
Journal Name
Iraqi Statisticians Journal
Estimate a nonparametric copula density function based on probit and wavelet transforms
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This study employs wavelet transforms to address the issue of boundary effects. Additionally, it utilizes probit transform techniques, which are based on probit functions, to estimate the copula density function. This estimation is dependent on the empirical distribution function of the variables. The density is estimated within a transformed domain. Recent research indicates that the early implementations of this strategy may have been more efficient. Nevertheless, in this work, we implemented two novel methodologies utilizing probit transform and wavelet transform. We then proceeded to evaluate and contrast these methodologies using three specific criteria: root mean square error (RMSE), Akaike information criterion (AIC), and log

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Publication Date
Mon Apr 15 2024
Journal Name
Journal Of Engineering Science And Technology
Text Steganography Based on Arabic Characters Linguistic Features and Word Shifting Method
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In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Journal Of Information And Communication Technology
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Fingerprints Identification and Verification Based on Local Density Distribution with Rotation Compensation
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The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Synthesis and Characterization of New phenolic Schiff bases Derivatives Based on Terephthaladehyde
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A variety of new phenolic Schiff bases derivatives have been synthesized starting from Terephthaladehyde compound, all proposed structures were supported by FTIR, 1H-NMR, 13C-NMR, Elemental analysis, some derivatives evaluated by Thermal analysis (TGA).

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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Proposed Hybrid Cryptosystems Based on Modifications of Playfair Cipher and RSA Cryptosystem
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Cipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared

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