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ijs-3315
Efficient Hybrid DCT-Wiener Algorithm Based Deep Learning Approach For Semantic Shape Segmentation
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    Semantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF) rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional layers giving modularity in the design using multi scale convolution block. The impact of selection of DCT coefficients in the proposed model is validated on the benchmark database as City Spaces. The same level of accuracy compared to the conventional algorithm is achieved using only 40 % of the DCT coefficients. Extensive experiments validate the advantages of adaptive DCT modeling of CNN in semantic segmentation and image classification.

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Publication Date
Sun Mar 04 2018
Journal Name
Iraqi Journal Of Science
Heartbeat Amplification and ECG Drawing from Video (Black and White or Colored Videos)
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Electrocardiography (ECG or EKG) is the process of recording the electrical activity of the heart over a period of time using electrodes placed on the skin. The main idea is how to detect activity of the heart from skin that appears in video without using electrodes. This paper, proposes an algorithm that works on analyzing video frames to detect heartbeats from tiny changes that happen in a skin color luminance (brightness) and then using them to amplifying heartbeat and drawing ECG. The results show that the heartbeat was detected and amplified and ECG was drawing from any part of the human body in different situations and from different video.

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Predictive Significance of Interleukins 17A and 33 in Risk of Relapsing–Remitting Multiple Sclerosis
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Cytokines are signaling molecules between inflammatory cells that play a significant role in the pathogenesis of a disease. Among these cytokines are interleukins (ILs) 17A and 33, and accordingly, the current case-control study sought to investigate the role of each of the two cytokines in the risk of developing multiple sclerosis (MS). Sixty-eight relapsing-remitting MS (RRMS) Iraqi patients and twenty healthy individuals (control group) were enrolled. Enzyme linked immunosorbent assay (ELISA) kits were used to determine serum levels of IL-17A and IL-33. Results revealed that IL-17A and IL-33 levels were significantly higher in MS patients than in controls (14.1 ± 4.5 vs. 7.5 ± 3.8 pg/mL; p < 0.001 and 65.3 ± 16

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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
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Optimized Artificial Neural network models to time series
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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Fibrewise totally topological spaces
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Publication Date
Fri Jan 01 2021
Journal Name
Review Of International Geographical Education
Evaluating the performance of project management using network diagrams methods: A case study in the Ramadi Municipality
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This study came for the reason that some project administrations still do not follow the appropriate scientific methods that enable them to perform their work in a manner that achieves the goals for which those projects arise, in addition to exceeding the planned times and costs, so this study aims to apply the methods of network diagrams in Planning, scheduling and monitoring the project of constructing an Alzeuot intersection bridge in the city of Ramadi, as the research sample, being one of the strategic projects that are being implemented in the city of Ramadi, as well as being one of the projects that faced during its implementation Several of problems, the project problem was studied according to scientific methods through the applica

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Science And Research (ij
Simulation of Chlorine Decay in Al-Gukook WaterDistribution Networks Using EPANET
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The approach of the research is to simulate residual chlorine decay through potable water distribution networks of Gukookcity. EPANET software was used for estimating and predicting chlorine concentration at different water network points . Data requiredas program inputs (pipe properties) were taken from the Baghdad Municipality, factors that affect residual chlorine concentrationincluding (pH ,Temperature, pressure ,flow rate) were measured .Twenty five samples were tested from November 2016 to July 2017.The residual chlorine values varied between ( 0.2-2mg/L) , and pH values varied between (7.6 -8.2) and the pressure was very weak inthis region. Statistical analyses were used to evaluated errors. The calculated concentrations by the calib

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Impact of Denial-of-Service Attack on Directional Compact Geographic Forwarding Routing Protocol in Wireless Sensor Networks
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Directional Compact Geographic Forwarding (DCGF) routing protocol promises a minimal overhead generation by utilizing a smart antenna and Quality of Service (QoS) aware aggregation. However, DCGF was tested only in the attack-free scenario without involving the security elements. Therefore, an investigation was conducted to examine the routing protocol algorithm whether it is secure against attack-based networks in the presence of Denial-of-Service (DoS) attack. This analysis on DoS attack was carried out using a single optimal attacker, A1, to investigate the impact of DoS attack on DCGF in a communication link. The study showed that DCGF does not perform efficiently in terms of packet delivery ratio and energy consumption even on a sin

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
AndroidTrack: An Investigation of Using Social Networks’ Applications in Android Platforms
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     In this paper, time spent and the repetition of using the Social Network Sites (SNS) in Android applications are investigated. In this approach, we seek to raise the awareness and limit, but not eliminate the repeated uses of SNS, by introducing AndroidTrack. This AndroidTrack is an android application that was designed to monitor and apply valid experimental studies in order to improve the impacts of social media on Iraqi users. Data generated from the app were aggregated and updated periodically at Google Firebase Real-time Database. The statistical factor analysis (FA) was presented as a result of the user’s interactions.

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Use of Multi-Response Logistic Regression to Determine the Factors Affecting the Radiation Values of Light-Curing Units in Private Dental Clinics in Erbil
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     This study aims to determine the exposure of dentists to radiation resulting from the use of light therapy units and to assess their risk and impact on dental clinics.  This study was conducted in private dental clinics in the city of Erbil in northern Iraq. Surveys were conducted to collect information about light-curing units. The results were analysed using the multi-response logistic regression to determine the factors affecting the radiation values of light-curing units. The results of the study showed that five major variables have a major effect by radiation.  This is shown with a value of P ≤ 0.05. Typical treatment times with radiant light, with a typical number of daily restorations, may exceed the risk limits for

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