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Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based features and color based features. The extracted features are finally fed to Deep Belief Network (DBN) for classification purpose. Different tests were performed and different combinations of feature types are attempted. The achieved results showed that when using combined vectors of local descriptors, the system gives the desired accuracy which is 100%. The achieved result demonstrates the effectiveness of using local descriptors in solving malaria infection detection problem.

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Publication Date
Sun Aug 13 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimation Optimal Threshold Value for Image Edge Detection
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      A new approach presented in this study to determine the optimal edge detection threshold value. This approach is base on extracting small homogenous blocks from unequal mean targets. Then, from these blocks we generate small image with known edges (edges represent the lines between the contacted blocks). So, these simulated edges can be assumed as true edges .The true simulated edges, compared with the detected edges in the small generated image is done by using different thresholding values. The comparison based on computing mean square errors between the simulated edge image and the produced edge image from edge detector methods. The mean square error computed for the total edge image (Er), for edge regio

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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Sat Oct 29 2022
Journal Name
Computers
Intelligent Robotic Welding Based on a Computer Vision Technology Approach
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Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Engineering Science And Technology
Membrane Fouling Reduction for Reverse Osmosis System Using Zeta Rod
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Reverse osmosis membrane desalination is one of the most significant water treatments that is used to offer freshwater. The aim of this research is to study the effect of controlling the value of the zeta potential on the suspended particles in the water and the proximity of the membrane surfaces in the colloidal solution, to keep the water stable electrically and disperse the colloidal particles. To achieve this aim, the experimental study was conducted in the Sanitary Engineering Laboratory, in the engineering college - University of Baghdad. Two systems were set up, one worked normally and the other worked by using the zeta rod placed before the reverse osmosis membrane. The results showed that the effect of the zeta rod increas

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Prediction of Explicit Features for Recommendation System Using User Reviews
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    With the explosive growth of data, it has become very difficult for a person to process the data and find the right information from it. So, to discover the right information from the colossal amount of data that is available online, we need information filtering systems. Recommendation systems (RS) help users find the most interesting information among the options that are available. Ratings given by the users play a vital role in determining the purposes of recommendations. Earlier, researchers used a user’s rating history to predict unknown ratings, but recently a user’s review has gained a lot of attention as it contains a lot of relevant information about a user’s decision. The proposed system makes an attempt to deal w

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
Elderly Healthcare System for Chronic Ailments using Machine Learning Techniques – a Review
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     World statistics declare that aging has direct correlations with more and more health problems with comorbid conditions. As healthcare communities evolve with a massive amount of data at a faster pace, it is essential to predict, assist, and prevent diseases at the right time, especially for elders. Similarly, many researchers have discussed that elders suffer extensively due to chronic health conditions.  This work was performed to review literature studies on prediction systems for various chronic illnesses of elderly people. Most of the reviewed papers proposed machine learning prediction models combined with, or without, other related intelligence techniques for chronic disease detection of elderly patie

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Emergency Messages Dissemination Challenges Through Connected Vehicles for Efficient Intelligent Transportation Systems: A Review
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Recent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and p

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Publication Date
Mon Jan 10 2022
Journal Name
Iraqi Journal Of Science
Genetic Algorithm based Clustering for Intrusion Detection
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Clustering algorithms have recently gained attention in the related literature since
they can help current intrusion detection systems in several aspects. This paper
proposes genetic algorithm (GA) based clustering, serving to distinguish patterns
incoming from network traffic packets into normal and attack. Two GA based
clustering models for solving intrusion detection problem are introduced. The first
model coined as handles numeric features of the network packet, whereas
the second one coined as concerns all features of the network packet.
Moreover, a new mutation operator directed for binary and symbolic features is
proposed. The basic concept of proposed mutation operator depends on the most
frequent value

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
DAMAGE DETECTION AND LOCATION FOR IN AND OUT-OFPLANE CURVED BEAMS USING FUZZY LOGIC BASED ON FREQUENCY DIFFERENCE
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In this study, structures damage identification method based on changes in the dynamic characteristics
(frequencies) of the structure are examined, stiffness as well as mass matrices of the curved
(in and out-of-plane vibration) beam elements is formulated using Hamilton's principle. Each node
of both of them possesses seven degrees of freedom including the warping degree of freedom. The
curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory
in 1994. A computer program was developing to carry out free vibration analyses of the curved
beam as well as straight beam. Comparing with the frequencies for other researchers using the general
purpose program MATLAB. Fuzzy logic syste

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