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Improving Wireless Sensor Network Security Using Quantum Key Distribution
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Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB84 protocol with the AES algorithm in
WSN security. The results of analysis indicated a high level of security between the data by depending on the
generation of secure keys, and reached an accuracy rate of about (80-95) % based on using NIST statistical.
The efficiency of the work increased to 0.704 after using the Quantum Bit Error Rate equation, eventually
increasing the network performance. This results in the reduction of the overall amount of energy, and the time
required for performing the key exchange in the encryption and decryption processes decreased.

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Fri Feb 28 2025
Journal Name
International Journal Of Intelligent Engineering And Systems
MCNet: Mask Cell of Multi Class Deep Network for Blood Cells Detection and Classification
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Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

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Publication Date
Thu Oct 30 2025
Journal Name
Iraqi Journal Of Science
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

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
The Evaluation of Information Security Management System in the Iraqi Commission for Computers and Informatics according to the International Standard (ISO 27001: 2013)
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    The current research included (the evaluation of Information Security Management System on according to international standard (ISO / IEC 27001: 2013) in Iraqi Commission for Computers and Informatics), for the development of an administrative system for information security is considered a priority in the present day, and in the light of the organizations  dependence on computers and information technology in work and communication  with others. The international legitimacy (represented by the  International Organization for standardization (ISO)) remains the basis for matching and commitment and the importance of the application of information Security Management System accordi

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Publication Date
Fri Dec 31 2021
Journal Name
Review Of International Geographical Education
Investing Organizational Identity in Improving Work Teams: An Exploratory Study of a Sample of The Capital's Traffic Directorates
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The research aims to identify the role of organizational identity in improving work teams, and to suggest ways to deal with the outputs of work teams in a way that achieves the goals of the Baghdad Traffic Directorate as it is the subject of the application of the research, while the research community was represented by its officers, while the research sample was embodied in (General Director, Associate The Director General, the directors of Rusafa and Karkh traffic and their assistants, as well as the heads of the divisions and the officials of the departments) in it. The sample was (200) observations. The descriptive exploratory approach was devoted to conducting the research, relying on the questionnaire in data collection, as well as e

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
THE EFFECT OF CHEMICAL AND BIOLOGICAL TREATMENTS ON IMPROVING THE NUTRITIVE VALUE OF CORN COBS AND WILD REED
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This study was conducted in Animal Resources Department , College of Agriculture to estimate the effect of chemical and biological treatments to improve the nutritive value of poor quality roughages ( corn cobs and wild reed ) . The feeds were treated chemically with 4% NaoH solution ,whereas Aspergillus niger was used to ferment corn cobs and wild reed samples . The chemical analysis showed that protein percentages of corn cobs and wild reed was increased significantly (P<0.05) from 6.05% to 10.51% and 17.70% and from 3.10 %to 6.50% and 9.96% for both chemical and biological treatments respectively. The crude fiber percentages decreased significantly (P<0.05) from 29.19% and 26.10% to 23.60% and 20.10% for chemical treatment and was 20

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Protective Effect of Daidzein on Ifosfamide-Induced Neurotoxicity Via Improving Some Selected Oxidative Stress Parameters in Male Rats
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  In this study, the possible protective effects of daidzein on ifosfamide-induced neurotoxicity in male rats were examined by the determination of changes in selected oxidant–antioxidant markers of male rats’ brain tissue.

Twenty-eight (28) apparently-healthy Wistar male rats weighing (120-150gm) allocated into 4 groups (n=7) were used in this study. Rats orally-administered 1% tween 20 dissolved in distilled water/Control (Group I); rats were orally-administered daidzein suspension (100mg/kg) for 7 days (Group II); rats intraperitoneally-injected with a single dose of ifosfamide (500 mg/kg) (Group III); rats orally-administered for 7 days with the daidzein (100mg/

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Protective Effect of Daidzein on Ifosfamide-Induced Neurotoxicity Via Improving Some Selected Oxidative Stress Parameters in Male Rats
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  In this study, the possible protective effects of daidzein on ifosfamide-induced neurotoxicity in male rats were examined by the determination of changes in selected oxidant–antioxidant markers of male rats’ brain tissue. Twenty-eight (28) apparently-healthy Wistar male rats weighing (120-150gm) allocated into 4 groups (n=7) were used in this study. Rats orally-administered 1% tween 20 dissolved in distilled water/Control (Group I); rats were orally-administered daidzein suspension (100mg/kg) for 7 days (Group II); rats intraperitoneally-injected with a single dose of ifosfamide (500 mg/kg) (Group III); rats orally-administered for 7 days with the daidzein (100mg/kg) before a single intraperitoneal dose of ifosfamide (

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