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Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samples of experimental data were used, including nineteen to train the network. Moreover six other experimental tests were implemented to test the network. The study concludes that ANN was a dependable and precise method for predicting machining parameters in CNC turning operation.

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Publication Date
Mon Oct 01 2018
Journal Name
2018 Ieee/acs 15th International Conference On Computer Systems And Applications (aiccsa)
Utilizing Hopfield Neural Network for Pseudo-Random Number Generator
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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
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Study the Effect of Forming Media on the Hydroforming Process for Copper Tube
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To observe the effect of media of the internal pressure on the equivalent stress distribution in the tube, an experimental study is done by constructing a testing rig to apply the hydraulic pressure and three dies are manufactured with different bulging configurations (square, cosine, and conical). In the other part, ANSYS APDL is generated to analyze the bulging process with hydraulic and rubber (natural and industrial) media. It was found that when the media is a rubber, the stress is decreased about 9.068% in case of cosine die and 5.4439% in case of conical die and 2.8544% in case of square die. So, it can be concluded that the internal pressure in the rubber media is much better than in hydraulic media. Also, the force needed for fo

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Hepatocellular Carcinoma Prediction and early Diagnosis of Hepatitis B and C viral infection using miR-122 and miR-223 in a sample of Iraqi patients.
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Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth.  In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre

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Publication Date
Tue Dec 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Adsorption of Cd(II) and Pb(II) Ions from Aqueous Solution by Activated Carbon
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Heavy metal consider as major environmental pollutants. Many of industrial wastewater effluents contain a wide range of these heavy metals. The adsorption of Cd2+ and Pb2+ metal ions from aqueous solution by activated carbon was studied. The results showed that maximum adsorption capacity occurred at 486.9×10-3 mg/kg for Pb2+ ion and 548.8×10-3 mg/kg for Cd2+ ion. The adsorption in a mixture of the metal ions had a balancing effect on the adsorption capacity of the activated carbon. The adsorption capacity of each metal ion was affected by the presence of other metal ions rather than its presence individually. The study showed the presence of other heavy metals attribute to the reduction in the activated carbon capacity, and the adsorp

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Publication Date
Tue Jun 01 2021
Journal Name
Political Sciences Journal
The role of elections in solidifying the process of democratization: a case study of Tunisian elections in 2019
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The electoral mechanism is remarkably clear, a political tool for institutional construction, directing political life, forming the political scene, and forming the partisan scene. This process was through the design of electoral laws, as elections in Tunisian political history represented the indicator of its slow and accelerated transformations, so The elections in Tunisia usually coincide with important political stages, accompanied by legislative or constitutional amendments in general, Islamic or secular forces have played a fundamental role in promoting the democratic experience and the principle of the peaceful transfer of power. This led to the formation of a national consensus that would help the country not enter into political

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
The role of MIS in the negotiation process "An Analytical Study in a Sample of Iraqi Organizations"
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Negotiation is considered as one of the most important kinds of communication in the contemporary organizations, which depend on the important role of managerial information systems in providing necessary and suitable information for success of the negotiation process.

Accordingly, this study aims at measuring the extent of the variables effect of managerial information system in the negotiation process.

To achieve this study, two hypotheses were chosen; the first is the correlation relation and the second is the effect, and statistical means represented by correlation coefficient "Spearman" and (R2) were used.

 A Number of conclusions were

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Publication Date
Thu Aug 01 2019
Journal Name
The Journal Of Solid Waste Technology And Management
Recycling of Waste Compact Discs in Concrete Mix: Lab Investigations and Artificial Neural Networks Modeling
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This study aimed to investigate the incorporation of recycled waste compact discs (WCDs) powder in concrete mixes to replace the fine aggregate by 5%, 10%, 15% and 20%. Compared to the reference concrete mix, results revealed that using WCDs powder in concrete mixes improved the workability and the dry density. The results demonstrated that the compressive, flexural, and split tensile strengths values for the WCDs-modified concrete mixes showed tendency to increase above the reference mix. However, at 28 days curing age, the strengths values for WCDs-modified concrete mixes were comparable to those for the reference mix. The leaching test revealed that none of the WCDs constituents was detected in the leachant after 180 days. The

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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