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Capacitance and Resistivity Measurements of Polythiophene /Metallic Nanoparticles-based Humidity Sensors
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Capacitive–resistive humidity sensors based on polythiophene (P3HT) organic semiconductor as an active material hybrid with three types of metallic nanoparticles (NP) (Ag, Al, and Cu) were synthesized by pulsed laser ablation (PLA). The hybrid P3HT/metallic nanoparticles were deposited on indium-tin-oxide (ITO) substrate at room temperature. The surface morphology of theses samples was studied by using field emission scanning electron micrographs (FE-SEM), which indicated the formation of nanoparticles with grain size of about 50nm. The electrical characteristics of the sensors were examined as a function of the relative humidity levels. The sensors showed an increase in the capacitance with variation in the humidity level.  While the resistivity While the resistivity decrease nonlinearity in the variation of humidity level from 10% to 100%.. The results show that the recovery and response times were higher for the Al/P3HT/Cu/Al sensor compared with those of the other nanoparticles.   

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Electronic Security And Digital Forensics
LSB based audio steganography preserving minimum sample SNR
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Publication Date
Thu Jan 01 2015
Journal Name
Iraqi Journal Of Science
Keystroke Dynamics Authentication based on Naïve Bayes Classifier
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Authentication is the process of determining whether someone or something is, in fact, who or what it is declared to be. As the dependence upon computers and computer networks grows, the need for user authentication has increased. User’s claimed identity can be verified by one of several methods. One of the most popular of these methods is represented by (something user know), such as password or Personal Identification Number (PIN). Biometrics is the science and technology of authentication by identifying the living individual’s physiological or behavioral attributes. Keystroke authentication is a new behavioral access control system to identify legitimate users via their typing behavior. The objective of this paper is to provide user

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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Hybrid LDPC-STBC communications system based on chaos
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Publication Date
Fri Oct 02 2015
Journal Name
American Journal Of Applied Sciences
Advances in Document Clustering with Evolutionary-Based Algorithms
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Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
GNSS Baseline Configuration Based on First Order Design
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The quality of Global Navigation Satellite Systems (GNSS) networks are considerably influenced by the configuration of the observed baselines. Where, this study aims to find an optimal configuration for GNSS baselines in terms of the number and distribution  of baselines to improve the quality criteria of the GNSS networks. First order design problem (FOD) was applied in this research to optimize GNSS network baselines configuration, and based on sequential adjustment method to solve its objective functions.

FOD for optimum precision (FOD-p) was the proposed model which based on the design criteria of A-optimality and E-optimality. These design criteria were selected as objective functions of precision, whic

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Content Based Image Retrieval (CBIR) by Statistical Methods
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            An image retrieval system is a computer system for browsing, looking and recovering pictures from a huge database of advanced pictures. The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visual and semantic content to a so-called query image. The researchers were developing a new mechanism to retrieval systems which is mainly based on two procedures. The first procedure relies on extract the statistical feature of both original, traditional image by using the histogram and statistical characteristics (mean, standard deviation). The second procedure relies on the T-

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
BCI-Based Smart Room Control using EEG Signals
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In this paper, we implement and examine a Simulink model with electroencephalography (EEG) to control many actuators based on brain waves. This will be in great demand since it will be useful for certain individuals who are unable to access some control units that need direct contact with humans. In the beginning, ten volunteers of a wide range of (20-66) participated in this study, and the statistical measurements were first calculated for all eight channels. Then the number of channels was reduced by half according to the activation of brain regions within the utilized protocol and the processing time also decreased. Consequently, four of the participants (three males and one female) were chosen to examine the Simulink model duri

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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Publication Date
Tue Sep 01 2020
Journal Name
Microprocessors And Microsystems
Design considerations for a microprocessor-based Doppler radar
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Publication Date
Sat Oct 01 2022
Journal Name
Therapeutic Delivery
Particles-based Medicated Wound Dressings: A Comprehensive Review
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