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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 on each subsystem to futher reduce the hardware requirements. The DNN was designed using a system generator and implemented using very hardware description language (VHDL). The system achievments outcomes the superior’s accuracy rate of approximately 99.6 percent in distinguishing bengin from malignant tissue. Also, the hardware resources were reduced by 30 percent from works of literature with an error rate of 7e-4 when using the Kintex-7 xc7k325t-3fbg676 board.

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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Achieving the Benefits and Requirements of Integrated Project Delivery Method Using BIM
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Abstract<p>Through the last decade, Integrated Project Delivery (IPD) methodology considers one of the new contractual relations that are also on the way to further integrate the process of combining design and instruction. On the other hand, Building Information Modeling (BIM) made significant advancements in coordinating the planning and construction processes. It is being used more often in conjunction with traditional delivery methods. In this paper, the researcher will present the achievement of IPD methodology by using BIM through applying on the design of the financial commission building in Mayssan Oil Company in Iraq. The building has not been constructed yet and it was designed by usin</p> ... Show More
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Publication Date
Fri Apr 01 2022
Journal Name
International Journal Of Nanoscience
Study of the Interaction Between Reduced Graphene Oxide and NO<sub>2</sub>Gas Molecules via Density Functional Theory (DFT)
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Electronic properties such as density of state, energy gap, HOMO (the highest occupied molecular orbital) level, LUMO (the lowest unoccupied molecular orbital) level and density of bonds, as well as spectroscopic properties like infrared (IR), Raman scattering, force constant, and reduced masses for coronene C24, reduced graphene oxide (rGO) C24O5and interaction between C24O5and NO2gas molecules were investigated. Density functional theory (DFT) with the exchange hybrid function B3LYP with 6-311G** basis sets through the Gaussian 09 W software program was used to do these calculations. Gaussian view 05 was em

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Thu Jul 01 2021
Journal Name
Mustansiriya Medical Journal
Evaluation of some biomarkers in diagnosis of bacterial bloodstream infection in children
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Background Bloodstream infection (BSI) is a life-threatening condition caused by the presence of microorganisms, generally caused by a range of bacteria in the blood. Objectives The aim of this study was to evaluate the possible role of procalcitonin (PCT) and C-reactive protein (CRP) as biomarkers of pediatric BSI. Methodology The study was conducted on 150 blood samples collected from the patient who admitted to Children Welfare Teaching Hospital, Medical City, Baghdad. During the period from November 2020 to March 2021, ninety blood samples from them were positive culture and 60 blood samples were negative culture (control group). The isolates were identified depending on the morphological, microscopic examination, and biochemical tests.

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Fri Jul 01 2022
Journal Name
Eurasian Chemical Communications
Assessment of hypoxemia status by measuring serum level of hypoxia inducible factor 1 alpha in relation to tumor suppression protein p53, estradiol and tumor proliferation markers of breast cancer in Thi-Qar province/Iraq
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Publication Date
Fri Jul 01 2022
Journal Name
Archives Of Razi Institute
Prognostic Value of Intracellular Transcription of Factors HIF-1α and p53 and Their Relation to Estradiol and TNM Parameters of Breast Cancer Tissues in Women with Invasive Ductal Carcinoma in Thi-Qar Province, Iraq
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Breast cancer is the most common malignancy affecting women's health, with an increasing incidence worldwide. This study aimed to measure the intracellular concentration of the hypoxia-inducible factor 1 α (HIF-1α), tumor suppression protein p53, and estradiol (E2) in tumor tissues of adult females with breast cancer and their relation to tumor grade, tumor size, and lymph node metastases (LNM). The study was conducted on 65 adult female participants with breast mass admitted to the operating theater in Al-Hussein Teaching Hospital and Al-Habboby Teaching Hospital in Nasiriyah, Iraq, from January to November 2021. Fresh breast tumor tissues were collated and homogenized for intracellular biochemical analysis using the enzyme-linked immuno

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Impact of the career path requirements in determining the type of training program
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The research deals with the important and modern two subject (career path and the type of training program), and tries to find identify the extent of the impact of the requirements of a career path in determining the type of training program in the Ministry of Oil.

In order to achieve the aim of the research was the formulation of the following hypothesis: the impact of the requirements of the career path a meaningful moral influence in determining the type of training program.

The survey was adopted in the search, and sample consisted of (75) people were a factor in the Oil Ministry of People's managers and officials and staff, and used the questionnaire as an es

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Publication Date
Thu Dec 09 2021
Journal Name
Revista Latinoamericana De Hipertension
Synthesis, chemical hydrolysis and biological evaluation of doxorubicin carbamate derivatives for targeting cancer cell
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