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Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details provided by the X-ray images dataset, the study showed that the using of X-ray data set in our deep learning algorithm could provide promising results by getting accuracy of validation for both Convolution Neural Network and SequeezeNet models 93%, 76%, respectively while the validation loss in both models Convolution Neural Network and SequeezeNet 34%, 30% respectively, these promise results will make the physician give a swift decision in diagnosis of lung cancer and keeping the patients away from exposing to unnecessary extra radiation dose during the Computed Tomograph exam as well as the low cost of X-ray examination comparing with Computed Tomograph exam.

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Maxillofacial Surgery
The use of screw retained hybrid arch bar for maxillomandibular fixation in the treatment of mandibular fractures: A comparative study
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Introduction: The use of screw-retained hybrid arch bars (HABs) is a relatively recent development in the treatment of mandibular fractures. The purpose of this study is to compare the clinical outcome between HAB and the conventional Erich arch bar (EAB) in the closed treatment of mandibular fractures. Materials and methods: This study included 18 patients who were treated for mandibular fractures with maxillomandibular fixation (MMF), patients were randomly assigned into a control group (n = 10) in which EAB was used and study group (n = 8) in which HAB was used. The outcome variables were time required for application and removal, gingival inflammation scores, postoperative complications, and incidence of wire-stick injury or gloves perf

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Publication Date
Tue Jan 01 2019
Journal Name
Science International
USING CRYPTOANALYSIS POLICIES AND TECHNIQUES TO CREATE STRONG PASSWORD
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Publication Date
Tue Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Improve Data Mining Techniques with a High-Performance Cluster
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Publication Date
Sat Jun 01 2024
Journal Name
Civil And Environmental Engineering
Constructing a Corrected Stations Network Using Some Geomatic Techniques
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Abstract<p>The major objective of this study is to establish a network of Ground Control Points-GCPs which can use it as a reference for any engineering project. Total Station (type: Nikon Nivo 5.C), Optical Level and Garmin Navigator GPS were used to perform traversing. Traversing measurement was achieved by using nine points covered the selected area irregularly. Near Civil Engineering Department at Baghdad University Al-jadiriya, an attempt has been made to assess the accuracy of GPS by comparing the data obtained from the Total Station. The average error of this method is 3.326 m with the highest coefficient of determination (R<sup>2</sup>) is 0.077 m observed in Northing. While in</p> ... Show More
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Publication Date
Thu Jul 02 2026
Journal Name
Innovative Construction And Petrochemical Technologies
Improving Arabic Text Classification Accuracy Using Lightweight NLP Techniques
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Arabic text classification is a challenging task because of the complex morphology of the language, the existence of different writing forms and a multitude of dialects, which can result in sparser common text representations. While transformer models such as AraBERT have obtained superior results on many Arabic NLP tasks, their high computational requirements make them difficult to deploy in environments with limited hardware resources. In some cases this can also make the model less practical for researchers working with basic computer systems. This study focuses on a more practical issue: how much accuracy a simple classifier may lose when the amount of required computation is reduced. We use a combined TF-IDF representation based on bo

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Publication Date
Mon Oct 02 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Image Encryption Techniques Using Dynamic Approach: An Article Review
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In this study, dynamic encryption techniques are explored as an image cipher method to generate S-boxes similar to AES S-boxes with the help of a private key belonging to the user and enable images to be encrypted or decrypted using S-boxes. This study consists of two stages: the dynamic generation of the S-box method and the encryption-decryption method. S-boxes should have a non-linear structure, and for this reason, K/DSA (Knutt Durstenfeld Shuffle Algorithm), which is one of the pseudo-random techniques, is used to generate S-boxes dynamically. The biggest advantage of this approach is the production of the inverted S-box with the S-box. Compared to the methods in the literature, the need to store the S-box is eliminated. Also, the fabr

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Fri Jan 01 2016
Journal Name
Proceedings Of The Eleventh International Network Conference (inc 2016)
A review on power consumption reduction techniques on OFDM
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Advanced Pharmacy Education And Research
Impact of preparation techniques on formulation and characterization of captopril effervescent granules
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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Techniques of family guidance in the face of marital and marital problems
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Summary First: The importance of the study and the need for it: The society is composed of an integrated unit of groups and institutions that seek to achieve a specific goal within a system of salary, and the family remains the most influential institutions on the individual and the unity of society, with the roles and responsibilities of the individual and society, and through the continuation and strength of other social organizations derive their ability On the other hand, any break-up in the institution of the family is reflected negatively on the cohesion of society and its interdependence, and the causes of this disintegration vary from society to another, but family problems remain the main factor in obtaining it. Second: Study Ob

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