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Quantitative analysis of sentinel lymph node detection using a novel small field of view hybrid gamma camera (HGC)
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Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm and 40 mm. The second plate contains four rectangular wells to simulate background activity uptake surrounding the SLNs. The activity used ranged between 4 MBq and 0.025 MBq for the SLNs. The background activity was 1/10 of the SLNs activity. The collimator to source distance was 120 mm. Results Signal to Noise Ratio (SNR) analysis and spatial resolution measurements of the simulated SLN were used to compare the imaging sets over acquisition times ranging between 60s and 240s. The HGC successfully detected 87.5% to 100% of the SLNs through 20mm of scattering material, and it could detect 75% to 93.75% of the SLNs through 40mm of scattering material. Measurement of Full-Width-at-Half-Maximum (FWHM) for the detected SLNs ranged between 9.5 mm and 12 mm. Conclusion The HGC is capable of detecting low activity uptake in small SLNs indicating its usefulness as an intraoperative imaging system during surgical SLN procedures.

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
A review on hybrid methods using playfair and RSA techniques
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Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
Serum Vascular Endothelial Growth Factor VEGF and Interlukin-8 As a Novel Biomarkers For Early Detection of Ovarian Tumors
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Epithelial ovarian cancer is the leading cause of cancer deaths from gynecological malignancies. Angiogenesis is considered essential for tumor growth and the development of metastases. VEGF and IL?8 are potent angiostimulatory molecules and their expression has been demonstrated in many solid tumors, including ovarian cancer.VEGF and IL-8 concentrations were measured by ELISA test (HumanVEGF,IL-8). Bioassay ELISA/ US Biological / USA).The median VEGF and IL-8 levels were significantly higher in the sera of ovarian cancer patients than in those with benign tumors and in healthy controls.Pretreatment VEGF and IL-8 serum levels might be regarded as an additional tool in the differentiation of ovarian tumors.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Tue Dec 22 2020
Journal Name
Collaboration And Integration In Construction, Engineering, Management And Technology
A Hybrid Conceptual Model for BIM Adoption in Facilities Management: A Descriptive Analysis for the Collected Data
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Publication Date
Tue Feb 20 2018
Journal Name
University Of Manchester
NOVEL POLYHYDROXYBUTYRATE (PHB) PRODUCTION USING A WASTE DATE SEED FEEDSTOCK
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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Natural Sciences
Geology and Structure Analysis of Shaqlawa – Merawa Area, Northern Iraq Using Remote Sensing, GIS and Field Observations
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This study appears GIS techniqueand remote sensing data are matching with the field observation to identify the structural features such as fault segments in the urban area such as the Merawa and Shaqlawa Cities. The use of different types of data such as fault systems, drainage patterns (previously mapped), lineament, and lithological contacts with spatial resolution of 30m was combined through a process of integration and index overlay modeling technique for producing the susceptibility map of fault segments in the study area. GIS spatial overlay technique was used to determine the spatial relationships of all the criteria (factors) and subcriteria (classes) within layers (maps) to classify and map the potential ar

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Publication Date
Mon Jun 01 2015
Journal Name
Iraqi Journal Of Science
Simulation of Solar Coronal Magnetic Field Using Potential Field Model
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In this paper, 3D simulation of the global coronal magnetic field, which use observed line of sight component of the photosphere magnetic field from (MDI/SOHO) was carried out using potential field model. The obtained results, improved the theoretical models of the coronal magnetic field, which represent a suitable lower boundary conditions (Bx, By, Bz) at the base of the linear force-free and nonlinear force free models, provides a less computationally expensive method than other models. Generally, very high speed computer and special configuration is needed to solve such problem as well as the problem of viewing the streamline of the magnetic field. For high accuracy special mathematical treatment was adopted to solve the computation comp

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Publication Date
Wed Sep 30 2026
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
UAV-STNet: A Hybrid U-Net–Transformer–LSTM Architecture for Real-Time Object Detection in UAV Video Surveillance
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It is difficult to perform real time object detection in Uncrewed Aerial Vehicle(UAV) based video surveillance because of the dynamic movement of camera, scale, occlusion, variation of illumination and limited power availability on-board of the computer. Purpose: In this paper of researches, the author suggests the proposed UAV Spatial-Temporal Network(UAV-STNet), which is a hybrid model of spatio-temporal deep learning model that is expected to improve the accuracy of the detection, balance of time, and real-time performance. Approaches: techniques: The proposed framework incorporates U-Net representing the system of total encoder involving extraction of multiscale space features mode, Transformer attention module which will involve global

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
The effect of losing one view of the independent variableAnd its location in simple regression analysis
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The objective of the research , is to shed light on the most important treatment of the problem of missing values of time series data and its influence in simple linear regression. This research deals with the effect of the missing values in independent variable only. This was carried out by proposing missing value from time series data which is complete originally and testing the influence of the missing value on simple regression analysis of data of an experiment related with the effect of the quantity of consumed ration on broilers weight for 15 weeks. The results showed that the missing value had not a significant effect as the estimated model after missing value was consistent and significant statistically. The results also

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Publication Date
Wed Mar 16 2022
Journal Name
2022 Muthanna International Conference On Engineering Science And Technology (micest)
A hybrid feature selection technique using chi-square with genetic algorithm
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