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Age Estimation Utilizing Deep Learning Convolutional Neural Network
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Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes into account the majority of the challenges faced by existing methods of age estimate. Making use of the data set that serves as the foundation for the face estimation system in this region (IMDB-WIKI). By performing preparatory processing activities to setup and train the data in order to collect cases, and by using the CNN deep learning method, which yielded results with an accuracy of 0.960 percent, we were able to reach our objective.

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Publication Date
Mon Dec 01 2025
Journal Name
Sensors And Actuators A: Physical
IoT based hybrid optical-wireless microstructured optical fiber sensor network for cadmium ions detection
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Publication Date
Thu Jun 27 2024
Journal Name
Journal Of Image And Graphics
ALL-FABNET: Acute Lymphocytic Leukemia Segmentation Using a Flipping Attention Block Decoder-Encoder Network
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Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

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Publication Date
Sat Apr 01 2017
Journal Name
Iracst – International Journal Of Computer Networks And Wireless Communications (ijcnwc)
Optimizing Network Security Considerations with Transition to IPv6 in University of Baghdad, A Prototype
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It is believed that Organizations around the world should be prepared for the transition to IPv6 and make sure they have the " know how" to be able to succeed in choosing the right migration to start time. This paper focuses on the transition to IPv6 mechanisms. Also, this paper proposes and tests a deployment of IPv6 prototype within the intranet of the University of Baghdad (BUniv) using virtualization software. Also, it deals with security issues, improvements and extensions of IPv6 network using firewalls, Virtual Private Network ( VPN), Access list ( ACLs). Finally, the performance of the obtainable intrusion detection model is assessed and compared with three approaches.

Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Transmitter Zigbee System based on Wireless Sensor Network of IEEE 802.15.4 Standard
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Abstract

 

Zigbee is considered to be one of the wireless sensor networks (WSNs) designed for short-range communications applications. It follows IEEE 802.15.4 specifications that aim to design networks with lowest cost and power consuming in addition to the minimum possible data rate. In this paper, a transmitter Zigbee system is designed based on PHY layer specifications of this standard. The modulation technique applied in this design is the offset quadrature phase shift keying (OQPSK) with half sine pulse-shaping for achieving a minimum possible amount of phase transitions. In addition, the applied spreading technique is direct sequence spread spectrum (DSSS) technique, which has

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of University Of Anbar For Pure Science
Mobile ad hoc network wireless security: problems, solutions, and application: state-of-the-art
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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
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Publication Date
Tue Oct 13 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of gender, age and tooth loss on the dimensions of incisive canal, and buccal bone anterior to the canal (Computed Tomography study)
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Background: The incisive canal is an anatomical structure with an important location in the anterior maxilla, analyzing this canal and its relation to the bone anterior to the canal is necessary during dental implant. Aim of this study is evaluated effect of gender, age and tooth loss in area of maxillary central incisors teeth on the dimensions of incisive canal and buccal bone anterior to the canal using spiral computed tomography. Materials and Methods: Sample consists of prospective study for 156 subjects for both gender, they divided into two groups, 120 dentate group (60 male and 60 female) with age ranging from (20-70) and 36 edentate group (with missing maxillary central incisors) (18 male and 18 female) with age ranging from (50-70

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Publication Date
Sun Jun 27 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Level of Depression and Anxiety among School Age Children with Acute Lymphoblastic Leukemia under Chemotherapy Treatment at Pediatric Teaching Hospitals in Baghdad City
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Objective(s): To assess the level of depression and anxiety among school age children with acute lymphoblastic leukemia under chemotherapy treatment and to find out the relationship between the level of depression and anxiety among the affected children and their demographic characteristics.
Methodology: A cross-sectional study was conducted on school age children both gender having acute lymphoblastic leukemia under chemotherapy treated and their age between 6 years to 12 years. The study started from the period of September, 19th 2020 to March,1st 2021. Non-probability (Purposive) sample of (114) children with acute lymphoblastic leukemia under chemotherapy was selected in attending hospital wards, outpatient and counseling clinics

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Publication Date
Wed Aug 07 2019
Journal Name
Iraqi National Journal Of Nursing Specialties
Impact of Factors upon Children’ Weight Status of age one to Five years old at Primary Health Care Centers in AL Samawah City
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Objective: The study aim is to identify factors that may contribute to children’s weight status variations. Methodology: A descriptive cross sectional study is carried out has been conducted at the AL- Samawah city in Primary Health Care Centers for the purpose of the screening children’s weight status of Age One to five Years Old. This study is started from December 16th 2018 to February 14th 2019. A(non propriety) purposive sample comprised of (20) primary health centers (10 main and 10 sub) are selected of 500 children who visit the primary health care center during the period for the purpose of the study; Data was collected through using a questionnaire designed and developed for the purpose of the study . It consists of two main

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Publication Date
Wed Jun 04 2025
Journal Name
Engineering, Technology & Applied Science Research
Evaluation of the Accuracy of Machine Learning Classifiers and Spectral Indices in Land Cover Classification
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Population growth and economic and industrial development coupled have significantly accelerated the rate of Land Use and Land Cover (LULC) changes, particularly in developing countries, so finding optimum ways to observe these change has become a pressing issue. Quantification evaluation of these changes is crucial to comprehend and oversee land management conversion, therefore, it is necessary to evaluate the accuracy of various algorithms for LULC classification to determine the most effective classifier for Earth observation applications. The performance of Maximum Likelihood (ML), Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN) was examined in this study, based on Sentinel 2A satellite images. T

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