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Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting ADR.

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Publication Date
Sun Jan 12 2025
Journal Name
القادسية للعلوم الانسانية
Employment of Artificial Intelligence Technologies in Improving Agricultural Productivity and Sustainability
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Abstract. This research examines the role of artificial intelligence (AI) in improving and sustaining agricultural production in the Arab world, with a particular focus on the challenges facing Iraq in implementing this technology. It reviews several developments, such as big data, the Internet of Things (IoT), and drone technology, which improve irrigation, increase soil fertility, and reduce waste. The study highlights the diverse applications of AI in crop production and pest control, while revealing Iraq's infrastructure challenges and the need for better training for farmers, To find effective solutions, the research recommends collaboration between governments and the private sector.

Publication Date
Fri Jul 26 2019
Journal Name
Dental Materials Journal
Semi-interpenetrating network composites reinforced with Kevlar fibers for dental post fabrication
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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
A Realistic Aggregate Load Representation for A Distribution Substation in Baghdad Network
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Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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Publication Date
Mon Nov 22 2021
Journal Name
Nanomaterials
Melting Enhancement in a Triple-Tube Latent Heat Storage System with Sloped Fins
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Due to the potential cost saving and minimal temperature stratification, the energy storage based on phase-change materials (PCMs) can be a reliable approach for decoupling energy demand from immediate supply availability. However, due to their high heat resistance, these materials necessitate the introduction of enhancing additives, such as expanded surfaces and fins, to enable their deployment in more widespread thermal and energy storage applications. This study reports on how circular fins with staggered distribution and variable orientations can be employed for addressing the low thermal response rates in a PCM (Paraffin RT-35) triple-tube heat exchanger consisting of two heat-transfer fluids flow in opposites directions throug

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Publication Date
Wed Dec 29 2021
Journal Name
Journal Of The College Of Education For Women
The Skills of Intended Meaning behind the Context when Reading Poetry among Fifth Grade Students- Literary Branch from Teachers’ Perspectives
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        The current research aims to investigate the skills of the intended meaning beyond the context when reading poetry among fifth literary students. To achieve the aim of the research, the researcher has followed the descriptive approach and used two tools: an open questionnaire that includes an inquiry about the skills of the intended meaning beyond the poetic context, and a closed questionnaire that were examined by the juries, and modified accordingly. Besides, its validity and stability were examined by applying the study on an exploratory sample of (15) teachers to reach its final version and determine the time required to answer it. Then, the researcher applied it on the research sample of (9

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Publication Date
Sun Jun 05 2011
Journal Name
Baghdad Science Journal
Reaction of Thiols with formaldehyde in Presnce of succinimid and Reduction of Phenyl Tetrazole Derivative with Hydrogen and Borohydraide
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One of most the important compounds which have active hydrogen (substrate) is the thiols which used in a wide field in preparation of Mannich bases . A large number of Mannich bases have been prepared as a biologically active compound (pharmaceutical, pesticides, bactericidal, fungicidal and tuberculostatic) and in order to correlate their structure and reactivity with their pharmacological activity such as . It has been reported that the reaction is easily proceeded by using primary and secondary amine beside formaldehyde. But when we tried the reaction of thiols as substrate and formaldehyde and succinimide instead of amine, the reaction did not proceed to give Mannich base but product were methylenene – bis – sulfide . Mann

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Thu Sep 01 2016
Journal Name
Physica Medica
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

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Engineering
Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

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