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Postmortem Panoramic Dental Radiography: Human Identification Based on Convolution Neural Network and Contourlet Transform
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Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted from the CNN to perform identification. Various models with different numbers of layers were applied as a try and test for the proposed system. Data augmentation is used to enhance the system's results. The experimental results illustrate that the best accuracy is 98.9% achieved by implementing the PDRs of size 224*224 using 16 layers (VGG16) with data augmentation of batch size 64*64 and 200 epochs. The prediction time of the proposed system to test PDR was just 3.1 sec. per image. The proposed system can be used to generate candidate images for critical issues. It will likely help with criminal investigations and people identification in large-scale disasters.

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Publication Date
Tue Dec 16 2025
Journal Name
Radioelectronics. Nanosystems. Information Technologies.
Intelligent Control and Stability Analysis of Smart Grids Using CNN-LSTM Network and Model Predictive Controller
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It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

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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)
Identification and Isolation of Caffeic, Chlorogenic and Ferulic Acids in Aerial Parts of Capparis spinosa wildly grown in Iraq
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Capparis spinosa is one of the oldest genera grown in Iraqi land with worldwide traditional medicinal uses beside the culinary uses. These uses were own to the presence of many phytochemical including flavonoids, polyphenols. Among the reported polyphenolic acids are caffeic, chlorogenic and ferulic acids with well-known powerful antioxidant properties. The present work aimed to identify the presence of these polyphenolic acids in Iraqi caper naturally gown in the rural area of middle Iraq following standard chromatographic procedures. Aerial parts of the plant (buds, berries and leaves) were extracted with hydroalcoholic solvent by maceration method. Thin layer chromatographic techniques and HPLC analysis were performed to iden

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
An Ecological and Identification Study for Algae in Groundwater of Selected Area in Tikrit city and It’s Surrounding Area
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The present study is carried out to identify the algae in the groundwater of the three areas of Tikrit city, including (the center of Tikrit , the region of AL-Jazira , Awainat village) by nine wells, a depths ranged between 9 meter at well 8 and 110 meter at wells 3 and 5 . And examined the environmental characteristics of physical, chemical and biological factors during the study period from September 2009 to June 2010. It is obtained that wells in the study area is lower alkalinity, average it ranged (6.448-7.418). It was noted that the values of the dissolved oxygen are few and almost non-existent in some cases it ranged between (6.5-6.3)mg/l , analysis of biological oxygen demand refers to wells water (clean- very clean) average

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Publication Date
Wed Jul 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
Pacifier Sucking Habit and its Relation to Dental Caries and Type of Feeding Habits among Group of Children (Comparative Study)
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Publication Date
Sun Nov 01 2020
Journal Name
The International Journal Of Oral & Maxillofacial Implants
Early Failure Rate and Associated Risk Factors for Dental Implants Placed With and Without Maxillary Sinus Augmentation: A Retrospective Study
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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The role of practices by the Managing of human resources on effectiveness of organizational crisis Management Described and analysis research for ministry of Iraqi interior
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The practice by the  administration of human resources  on effectiveness of organization  crisis as two knowledge fields , it were be until now as center for many studies, but the collect it, study of relation between them ,and The role of practices  by the  administration of human resources  on effectiveness of organization  crisis administration  were considered a new study and first according to the available and showing  studies at this field .

The problem of this research was specified by answer for the question that deal for size of consciousness at the ministry of interior for import of&nbs

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Publication Date
Mon Jan 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The use of IT infrastructure and its impact on the performance of human resources in public universities: A field study at the University of Diyala
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This study aims to identify the impact of using the infrastructure of the Information Technology (IT) on the performance of human resources in the public universities. This process is done by doing research in the size, quality, and efficiency of the performance, also speed of achievement and simplification of procedures. Diyala University was chosen for the diagnosis through the opinions and attitudes of its employees.  Consequently, suggestions that contribute to improve the performance of the employees and thus its overall performance are obtained. Another objective of this study is identifying the human resources which are currently used in academic institutions and educational services systems because the significant role of th

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Publication Date
Tue Jan 01 2013
Journal Name
Bio-genetics Journal
Measuring the toxicity of Heat Stable Enterotoxin (a) produced by Enterotoxigenic Escherichia coli on human blood lymphocyte from normal and colorectal cancer patients in vitro
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This research was conducted to measure the safety of heat stable enterotoxin a (STa) produced by enterotoxigenic Escherichia coli, through studying its toxic effect on human blood lymphocyte, since it showed a promising effect in reducing the proliferation of colorectal cancer cells. the cytogenetic effects of (STa) by using five different concentrations (100, 200, 400, 800 and 1600μg/ml) in comparison with negative (PBS, Phosphate buffer saline) and positive (MMC, Mitomycin C) at concentration of 5μg/ml, controls on human blood lymphocytes obtained from both (10) normal healthy persons and (20) colorectal cancer patients was measured by employing the following parameters: mitotic index, blast index, chromosomal aberrations and micronucle

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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
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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