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THE IMPACT OF PLOWING DEPTH AND SOIL MOISTURE ON SOME TECHNICAL INDICATORS AT USING DISK PLOW
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An experiment was carried out in a field in Husayniyah sub-district of the Holy Karbala Governorate. The research included studying the impact of the plowing depth and soil moisture on some technical indicators when using the disc plow. The 80 hp New Holland tractor was used in this experiment. Two factors were studied, the first factor is the soil moisture (12- 9%), (16-13%) and (20-17%) and the second factor was the depth of tillage (10-13) cm, (15-18) cm and (20-23) cm, which represented the secondary blocks. Bulk density, percentage of slippage and drawing force were studied. The field trials was conducted according to Split blocks in a randomized complete block design in three replicate. Consequences showed (according to the conditions of the experiment) that soil moisture of 17-20% outperformed in obtaining the lowest average bulk density of 1.25 g cm-3 whereas soil moisture of 12-9% recorded the lowest rate of slippage of 8.72% and the lowest rate of the net drawing of 1310.39 (kg.N). The plowing depth of 10-13 cm outperformed in obtaining the lowest average of bulk density of 1.25 g cm-3, the lowest slippage percentage of 7.19%, and the lowest rate of net drawing of 1013.84 (kg. N). The results also showed that soil moisture of 9-12% and plowing depth of 10-13 cm outperformed in obtaining the best interaction in most of the studied traits

Publication Date
Mon Jun 01 2015
Journal Name
International Photonics And Optoelectronics
Canonical Logic Units using Bidirectional Four-Wave Mixing in Highly Nonlinear Fiber
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All-optical canonical logic units at 40 Gb/s using bidirectional four-wave mixing (FWM) in highly nonlinear fiber are proposed and experimentally demonstrated. Clear temporal waveforms and correct pattern streams are successfully observed in the experiment. This scheme can reduce the amount of nonlinear devices and enlarge the computing capacity compared with general ones. The numerical simulations are made to analyze the relationship between the FWM efficiency and the position of two interactional signals. © 2015 Chinese Laser Press

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
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Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Furfural Degradation in Waste Water by Advanced Oxidation Process Using UV/H2O2
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Furfural is one of the one of pollutants in refinery industrial wastewaters. In this study advanced oxidation process using UV/H2O2 was investigated for furfural degradation in synthetic wastewater. The results from the experimental work showed that the degradation of furfural decreases as its concentration increases, reaching 100% at 50mg/l furfural concentration and increasing the concentration of H2O2 from 250 to 500 mg/l increased furfural removal from 40 to 60%.The degradation of furfural reached 100% after 90 min exposure time using two UV lamps, where it reached 60% using one lamp after 240 min exposure time. The rate of furfural degradation k increased at the pH and initial concentratio

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Publication Date
Sat Jul 01 2017
Journal Name
2017 Computing Conference
Protecting a sensitive dataset using a time based password in big data
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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
High spatial resolution digital elevation model (DEM) production using different interpolations techniques
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DEMs, thus, simply regular grids of elevation measurements over the land surface.The aim of the present work is to produce high resolution DEM for certain investigated region (i.e. Baghdad University Campus\ college of science). The easting and northing of 90 locations, including the ground-base and buildings of the studied area, have been obtained by field survey using global positioning system (GPS). The image of the investigated area has been extracted from Quick-Bird satellite sensor (with spatial resolution of 0.6 m). It has been geo-referenced and rectified  using 1st order polynomial transformation. many interpolation methods have been used to estimate the elevation such as ordinary Kriging, inverse distance weight

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Publication Date
Mon Mar 23 2020
Journal Name
International Journal Of Nanoscience
Gold Nanoparticles Synthesis Using Environmentally Friendly Approach for Inhibition Human Breast Cancer
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In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Sentiment analysis in arabic language using machine learning: Iraqi dialect case study
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Publication Date
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Applying Cognitive Methodology in Designing On-Line Auto-Tuning Robust PID Controller for the Real Heating System
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A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA)

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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology & Applied Science Research
An Enhanced Document Source Identification System for Printer Forensic Applications based on the Boosted Quantum KNN Classifier
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

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