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Quantitative analysis of sentinel lymph node detection using a novel small field of view hybrid gamma camera (HGC)

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
Sun Jan 04 2015
Journal Name
Journal Of Educational And Psychological Researches
Undesirable behaviors for university students by their instructors view

Undesirable behaviors among students  are consider one of the danger problems threating societies and educational and scientific institutions of countries  because its one of the way to express aggression , so the instructors consider one of the most important people could be trust their evaluation and logical view , therefore the present research aimed to :

  1. Recognize undesirable behavior in students of University by the view of their instructors
  2. Measure the level of undesirable behavior in students of university by the view of their instructors
  3. Recognize more common  undesirable behavior in students of University by the view o

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Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
Statistical analysis from a Gender perspective

This research is a theoretical study that deals with the presentation of the literature of statistical analysis from the perspective of gender or what is called Engendering Statistics. The researcher relied on a number of UN reports as well as some foreign sources to conduct the current study. Gender statistics are defined as statistics that reflect the differences and inequality of the status of women and men overall domains of life, and their importance stems from the fact that it is an important tool in promoting equality as a necessity for the process of sustainable development and the formulation of national and effective development policies and programs. The empowerment of women and the achievement of equality between men and wome

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach

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
Wed Nov 14 2018
Journal Name
Fiber And Integrated Optics
Design Investigation of 2 × 2 Mach–Zehnder Optical Switch Based on a Metal–Polymer–Silicon Hybrid Plasmonic Waveguide

In this paper, a miniaturized 2 × 2 electro-optic plasmonic Mach– Zehnder switch (MZS) based on metal–polymer–silicon hybrid waveguide is presented. Adiabatic tapers are designed to couple the light between the plasmonic phase shifter, implemented in each of the MZS arms, and the 3-dB input/output directional couplers. For 6 µm-long hybrid plasmonic waveguide supported by JRD1 polymer (r33= 390 pm/V), a π-phase shift voltage of 2 V is obtained. The switch is designed for 1550 nm operation wavelength using COMSOL software and characterizes by 2.3 dB insertion loss, 9.9 fJ/bit power consumption, and 640 GHz operation bandwidth

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Fri Apr 15 2016
Journal Name
International Journal Of Computer Applications
Hybrid Techniques based Speech Recognition

Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

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Publication Date
Sat Dec 03 2011
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Detection of shoreline change in AL-Thirthar Lake using remotely sensed imagery and topography map

Publication Date
Mon Aug 01 2011
Journal Name
International Journal Of Research And Reviews In Computer Science
Detection of the photon number splitting attack by using decoy states quantum key distribution system

The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.