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A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with 213 eyes examined in Iraq and obtained AUCs of 0.91–0.92 and an accuracy range of 88–92%. The proposed model is a step toward improving the detection of clinical and subclinical forms of KCN.

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Shared Congestion Detection: A Comparative Study
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Most Internet-tomography problems such as shared congestion detection depend on network measurements. Usually, such measurements are carried out in multiple locations inside the network and relied on local clocks. These clocks usually skewed with time making these measurements unsynchronized and thereby degrading the performance of most techniques. Recently, shared congestion detection has become an important issue in many computer networked applications such as multimedia streaming and
peer-to-peer file sharing. One of the most powerful techniques that employed in literature is based on Discrete Wavelet Transform (DWT) with cross-correlation operation to determine the state of the congestion. Wavelet transform is used as a de-noisin

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Publication Date
Fri Sep 23 2022
Journal Name
Specialusis Ugdymas
Intrusion Detection System Techniques A Review
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With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.

Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Multifocus Images Fusion Based On Homogenity and Edges Measures
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Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Research on Emotion Classification Based on Multi-modal Fusion
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Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

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Publication Date
Tue May 07 2019
Journal Name
Acm Journal On Emerging Technologies In Computing Systems
Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis
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Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

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Publication Date
Wed May 24 2023
Journal Name
2023 9th International Conference On Information Technology Trends (itt)
A Comparative Study of Unauthorized Drone Detection Techniques
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Publication Date
Wed Jul 01 2015
Journal Name
Al–bahith Al–a'alami
Photos of Women in Iraqi Feature Films after 2003
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The research seeks to examine the image of women in Iraqi films produced after 2003 over the answer to questions such as “ level of the representation of women and appearing in films and features that are attributable to them and their relationships with men and their interests and tendencies , activities and ways and methods pursued to achieve their goals , or what appeared to be trying to achieve and whether made movies vivid and varied models for women, or confined to a rigid model and duplicate Is films raised issues concerning women? The research seeks to examine the image of women in Iraqi films produced after 2003 over the answer to questions such as “ level of the representation of women and appearing in films and features th

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Publication Date
Tue Mar 15 2022
Journal Name
Al-academy
Dramatic function of temporal variables in the feature film
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Time and space are indispensable basics in cinematic art. They contain the characters, their actions and the nature of events, as well as their expressive abilities to express many ideas and information. However, the process of collecting space and time in one term is space-time, and it is one of Einstein’s theoretical propositions, who sees that Time is an added dimension within the place, so the study here differs from the previous one, and this is what the researcher determined in the topic of his research, which was titled (The Dramatic Function of Space-Time Variables in the Narrative Film), Which included the following: The research problem, which crystallized in the following question: What is the dramatic function of the tempor

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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Therapeutic Use of Silymarin in the Management of Suspected Renal and Hepatic Injury Produced by NSAIDs in Osteoarthritis Patients
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Long-term use of non-steroidal anti-inflammatory drugs (NSAIDs) mostly associated with renal and hepatic adverse effects, and the adjunct use of compounds with potent protective effects, like silymarin, may be one of the choices to avoid these effects. This project was designed to evaluate the protective effect of silymarin against the suspected renal and hepatic injury induced with long term use of NSAIDs; 220 patients with osteoarthritis were randomized into 5 groups and treated with either silymarin 300mg/day alone, piroxicam 20mg/day alone, meloxicam 15mg/day alone or the combination of each of them with silymarin for 8 weeks. The renal and hepatic functions were evaluated before starting treatment and after 8 weeks including assessm

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