The present work reports an approach of hydrothermal growth of ZnO nanorods, which simplifies the production of low cost films with controlled morphology for H2S gas sensor application. The prepared ZnO nanorods exhibit a hexagonal wurtzite phase analyzed by the X-ray diffraction analysis. The FTIR spectra provide information that the band located between 465-570 cm-1 corresponds to the stretching bond of Zn-O, which confirms the creation of ZnO. PL spectroscopic studies showed that the doping of Ag NPs and f-MWCNT in the ZnO matrix leads to the tuning of the bandgap. The SEM analysis showed the morphology of ZnO was the nanorods. The nanocomposites Ag/ZnO and F-MWCNT/ZnO which prepared, separately were tested for H2S gas at low (2 ppm) and high (50 ppm) concentrations. ZnO nanorods films showed a sensitivity of 14.71% for pure ZnO with a fast response time of 25.2 sec and recovery time of 33.3 sec towards 2 ppm H2S. For Ag NPs/ZnO and f-MWCNTs/ZnO, sensors showed a significant sensitivity of 27.95 and 42.39 % at ~150 °C with a response time and recovery time less than pure ZnO. The ZnO sensor showed a higher sensitivity at ~150 °C for both Ag NPs and F-MWCNTs at high gas concentration, where it was 35.085 and 58.89% respectively.
Abstract:
This research aims to apply the Performance Focused Activity Based Costing System in the consultant office of Al-Khwarizmi College of Engineering at the University of Technology for the purpose of measuring the cost of consulting services provided by these offices in order to reduce costs and their reflection in achieving profits. For the purpose of calculating costs accurately, and to test the hypothesis of the research, the research was applied in the office of the consultant of the College of Engineering Al-Khwarizm - University of Baghdad through the financial statement
... Show MoreIn the current study, new derivatives were synthesized by reaction of N-hydroxyphthalimide with chloro acetyl chloride in the presence of Et3N as a base to form 1,3-dioxoisoindolin-2-yl 2-chloroacetate (B1), which in turn enters several reactions with different amines where it interacts with primary amines to give 1,3-dioxoisoindolin-2-yl acetate derivatives (B2-B4) in basic medium, in the same way it interacts with these amines but with adding KNCS to form thiourea derivatives (B5-B7). It also reacts with diamines to give bis(azanediyl) derivatives (compounds B8-B10). The prepared derivatives were diagnosed using infrared FTIR and 1HNMR,13CNMR for some derivatives. Compounds B4, B5 and B9 were measured as corrosion inhibitors the inhibitio
... Show MoreBackground: The mechanical and physical properties of Polymethyl methacrylate (PMMA) don’tfulfill the entire ideal requirements of denture base materials. The purpose of this study was to produce new modified polymer nanocomposite (PMMA /ZrO2-TiO2) andassess itsimpact strength, transverse strength and thermal conductivity in comparison to the conventionalheat polymerized acrylic resin. Materials and Methods: Both ZrO2 and TiO2nano fillers were silanized with TMSPM (trimethoxysilyl propyl methacrylate) silane coupling agent before beingdispersed by ultrasonication with the methylmethacrylate (monomer) and mixed with the polymer by means of 2% by weight in (1:1) ratio, 60 specimens were constructed by conventional water bath processing
... Show MoreThis 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
... Show MoreIn 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
... Show MoreThis 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
... Show MoreIn 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