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Effect of Deep Remediation and Improvement on Bearing Capacity and Settlement of Piled Raft Foundation Subjected to Static and Cyclic Vertical Loading
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Publication Date
Sat Dec 31 2022
Journal Name
International Journal On “technical And Physical Problems Of Engineering”
Age Estimation Utilizing Deep Learning Convolutional Neural Network
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Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Fri May 01 2020
Journal Name
Systematic Reviews In Pharmacy
Methotrexate effect on obestatin, progranulin and kidney function in RA Iraqi males patients
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Methotrxate (MTX) has become the standard of care and first-line therapy for patients who have RA and consider as a gold standard of treatment for RA. The role of MTX in the treatment of RA has now been well established. The use of MTX treatment of RA inhibits proliferation of the lymphocytes, reduces signs and symptoms this disease, reduces progression damage of the joints and improves quality of life outcome. Progranulin (PGRN) acts a role in autoimmune inflammatory, has important function in several processes including immune response. Present study has conducted to find the effect of MTX drugs as a therapeutic target for RA patients because of its ability to bind with tumor necrosis factor receptor (TNFR), with progranulin, obestatin an

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Scopus
Publication Date
Wed Jan 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Study the synergistic Effect between Nanoparticles and Spiramycin on Immunological Response Against Toxoplasmosis
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Abstract<p>This investigation was carried out to estimate the antiparasitic potential of silver and Chitosan nanoparticles loaded with spiramycin against toxoplasmosis infected. After mice injected intraperitoneal in a dose 10<sup>3</sup>viable tachyzoites for acute infection; then treated with spiramycin, chitosan nanoparticles and silver nanoparticles as a single or combined therapy given for seven days. Peritoneal fluid examination revealed a significant decrease in the number of<italic>T. gondii</italic>tachyzoites in all treated infected mice compared with infected non-treated. The combined therapy presented better results than the single one. The best effect was observed in a group of </p> ... Show More
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Blockchain Technology and its Potential Effect on the Banking Industry (China Case Study)
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The aim of the research is to investigate potential effects of the finance industry and block-chain to general business of financing in particular, as well as its shortcomings and difficulties. To answer the research questions, the researcher used the objective narrative-analytical descriptive approach and included a qualitative analysis of Blockchain technology. The process of Blockchain technology based on their industries, the authors were selected based on their reputation in the Blockchain field. The research found that Blockchain can improve the efficiency of the banking industry's various sections. It has the ability to upgrade and transfer wages across borders, financial reporting and compliance, as well as trade finance

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Study The effect of central ion to the dithene complexes on spectral shifting of saturable absorber band
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In this work dithine complexes prepared from dithiol benzil ligand and central ion to the Ni,Pd,Pt, element the ligand and complexes have been investigated using FTIR spectrophotometer and uv-vis-NIR spectral reigns show higher intensity represents the ?-?* transition in the chromopher cycle .These absorption which appear in visible and near IR spectral regions ,According to the complexes of one group ,the spectral shifting due to the change of central ion has been found to be related to atomic number of central ion .This shifting is increased while decreasing the central ion atom number These complexes have been implemented in Nd+2:YAG cavity because each posses resonant absorption band near Nd+2:YAG, Nd+2:Glass emitting at (106

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of the Effect of Topical Artemisia dracunculus Administration on Serum Levels of Selected Interleukins and Spleen Index in Imiquimod-Induced Psoriasis in Male Mice Compared to Clobetasol Propionate (Dermovate (R)) Ointment
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Psoriasis is a long-lasting autoimmune disease that is characterized by swollen skin patches. Normally, these skin patches are dark, swollen, itchy and scaly. The single application of the innate TLR7/8 ligand Imiquimod (IMQ) in mice easily induces a dermatitis that closely resembles human psoriasis, critically dependent on the axis of IL-23/IL-17. Artemisia dracunculus prepared as an ointment and has been used topically to mice before imiquimod application. The results of the current study showed that A. dracunculus ointment can significantly reduce psoriasis area and severity index in (A. dracunculus ointment + imiquimod group as compared with both control group and (vehicle ointment + imiquimod) group.

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