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Characterization of biochar (bio carbon) on the properties of plasticized polylactic acid composites for antistatic packaging
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A new  light-weight nanocarbon prepared by spray-drying method  to obtain  particle size is 21.7 nm based of polylactic acid biodegradable film in antistatic packaging .Bio carbon (biochar) is  obtained from  plants and soils to naturally absorb and store carbon dioxide from the atmosphere . Therefor it has been used to support biodegradable polylactic acid (PLA) with to obtain 100% recyclable material.

Using plasticizer thymol of polylactic acid and biochar (bio carbon) as composites were prepared by a solution casting method with (0.5-10)wt% biochar. The composites  characterized by  FTIR, electrical conductivity, mechanical properties , contact angle and Colar and Brightness . Results show that electrical conductivity of increased with increased biochar and makes the composite lower resistive and appropriate for use as antistatic packaging for the transportation and store of electronic components, mechanical tests show reduced the tensile strength and   tensile modulus but increased in  elongation, Tear Resistance and Hardness because used thymol as plasticizers  at PLA/thymol  (95/5) and films composites change from brittle to ductile   . The results of contact angle of pure PLA is 83 that mean hydrophobic materials and decreased to 54at PLA/thymol/biochar 10% to obtain hydrophilic materials that able to dissipate or promote the decay of static electricity and improve process ability of electronic device. Optical such as Color and Brightness show that decreased but suitable for antistatic packaging   and became opacity at 10% biochar.  

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Publication Date
Fri Jan 01 2016
Journal Name
Modern Applied Science
New Combined Technique for Fingerprint Image Enhancement
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This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one

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Publication Date
Tue Jan 01 2019
Journal Name
Aip Conference Proceedings
Highly selective CdS:Ag heterojunction for photodetector applications
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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
INITIAL COLLECTION EFFICIENCY FOR GLASS FILTER MEDIA
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This study investigated the ability of using crushed glass solid wastes in water filtration by using a pilot plant, constructed in Al-Wathba water treatment plant in Baghdad. Different depths and different grain sizes of crushed glass were used as mono and dual media with sand and porcelaniate in the filtration process. The mathematical model by Tufenkji and Elimelech was used to evaluate the initial collection efficiency η of these filters. The results indicated that the collection efficiency varied inversely with the filtration rate. For the mono media filters the theoretical ηth values were more than the practical values ηprac calculated from the experimental work. In the glass filter ηprac was obtained by multiplying ηth by a facto

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Publication Date
Thu Oct 18 2018
Journal Name
Proceedings Of The Future Technologies Conference (ftc) 2018
Using Mouse Dynamics for Continuous User Authentication
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Intelligent Systems And Internet Of Things
Enhancing Convolutional Neural Network for Image Retrieval
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With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

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Publication Date
Mon Feb 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Differential evolution detection models for SMS spam
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With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

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Publication Date
Tue Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Design Mobile Application for Blood Donation System
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Publication Date
Wed Jul 17 2019
Journal Name
Advances In Intelligent Systems And Computing
A New Arabic Dataset for Emotion Recognition
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In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

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Publication Date
Sun May 11 2025
Journal Name
Iraqi Statisticians Journal
Nonparametric Estimation for Nonstationary Time Series Models
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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Oxygen Mass Transfer Coefficients in Stirred Bioreactor with Rushton Turbine Impeller for Simulated (Non-Microbial) Medias
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 Abstract

The study of oxygen mass transfer was conducted in a laboratory scale 5 liter stirred bioreactor equipped with one Rushton turbine impeller. The effects of superficial gas velocity, impeller speed, power input and liquid viscosity on the oxygen mass transfer were considered. Air/ water and air/CMC systems were used as a liquid media for this study. The concentration of CMC was ranging from 0.5 to 3 w/v. The experimental results show that volumetric oxygen mass transfer coefficient increases with the increase in the superficial gas velocity and impeller speed and decreases with increasing liquid viscosity. The experimental results of kla were correlated with a mathematical correlation des

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