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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
Mon Jan 01 2024
Journal Name
Lecture Notes In Electrical Engineering
A Study of the Influence of Steel Brushes in Rail Surface Magnetic Flux Leakage Detection Using Finite Elements Simulation
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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Isolation and Identification of Fungal Propagation in Stored Maize and detection of aflatoxin B1 Using TLC and ELISA Technique
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Aflatoxin B1 (AFB1) is a mycotoxin produced mainly by fungi Aspergillus flavus in food and animals feed. It is considered as a carcinogenic toxin for human and animals. The current study is designed to investigate the incidence of mycoflora in twenty four samples of local stored maize collected from Iraqi governorates; investigate the presence of aflatoxin B1 on these samples using TLC and ELISA techniques. The fungi recovered from maize samples were Aspergillus flavus (18.57 % ), Fusarium spp. (12.8 % ), A. ocraceus (9.96 % ) , A. terrus (9.07 % ), A. fumigatus (8.46 % ) , Alternaria spp. (6.40 % ) Rhizopus spp. (4.98 % ), A. niger spp., A. oryzae spp. (4.80 % ), Penicillium spp. (4.53 %) A. versicolor spp., Rhizoctonia spp. (4.27 %), A

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Detection of Methamphetamine using Nanobentonite as a Novel Solid Phase Extraction Column Matrix Assisted with Gas Chromatography- Mass Spectroscopy
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          This study was done to evaluate a new technique to determine the presence of methamphetamine in the hair using nano bentonite-based adsorbent as the filler of extraction column. The state of the art of this study was based on the presence of silica in the nano bentonite that was assumed can interact with methamphetamine. The hair used was treated using methanol to extract the presence of methamphetamine, then it was continued by sonicating the hair sample. Qualitative analysis using Marquish reagent was performed to confirm the presence of methamphetamine in the isolate.The hair sample that has been taken in a different period confirmed that this current developing method can be used to analyzed methamphetamine. This m

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Publication Date
Sat Jun 03 2023
Journal Name
Iraqi Journal Of Science
Determination of hydroquinone in pure form and pharmaceutical preparations using Batch and FIA-Merging Zone techniques with spectrophotometric detection
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In this study, a new, rapid and sensitive batch and flow injection-merging zones spectrophotometric methods for the determination of hydroquinone in a pure material and in pharmaceutical preparation were proposed. These methods were based on the oxidative-coupling reaction of HQ with 2,4-dinitrophenylhydazine (DNPH) in the presence of sodium periodate and sodium hydroxide to form a dark brown water slouble dye that is stable and has maximum absorption at 530 nm, graphs of absorbance versus concentration show that Beer's low is obeyed over the concentration rang of 1-40 and 3-300 μg.ml-1 of hydroquinone, with detection limits of 0.162 and 0.510 μg.ml-1 of hydroquinone for batch and FIA methods, respectively. The optimized FIA system is

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Convergence Analysis for the Homotopy Perturbation Method for a Linear System of Mixed Volterra-Fredholm Integral Equations
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           In this paper, the homotopy perturbation method (HPM) is presented for treating a linear system of second-kind mixed Volterra-Fredholm integral equations. The method is based on constructing the series whose summation is the solution of the considered system. Convergence of constructed series is discussed and its proof is given; also, the error estimation is obtained. Algorithm is suggested and applied on several examples and the results are computed by using MATLAB (R2015a). To show the accuracy of the results and the effectiveness of the method, the approximate solutions of some examples are compared with the exact solution by computing the absolute errors.

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Publication Date
Tue Apr 04 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
INVESTIGATION OF BACTERIAL CONTAMINANTS IN FREEZERS KEEPING FROZEN FOOD IN LOCAL MARKETS: INVESTIGATION OF BACTERIAL CONTAMINANTS IN FREEZERS KEEPING FROZEN FOOD IN LOCAL MARKETS
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This study aimed to evaluate the occurrence of microbial contamination in food keeping freezers in some local markets in Baghdad city/ Iraq, as well as the contamination of the hands of workers in markets, and the possibility of contamination caused by the transport of food. 30 samples of snow ice found in food keeping freezers in local markets was randomly collected, and 30 swabs from workers hands were taken from the same markets at the same time. Microbiological examination of ice samples was conducted as well as the hands of workers’swabs, and the bacteria were isolated and diagnosed through microbiological and biochemical tests followed. Microbial test results showed some isolates of bacteria in ice samples obtained from food keep

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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
IRAQI CONSUMER OPINION OF THE QUALITY AND SAFETY OF LOCAL FOOD PRODUCTS: IRAQI CONSUMER OPINION OF THE QUALITY AND SAFETY OF LOCAL FOOD PRODUCTS
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The aim of this research was to indicate the opinion of the Iraqi consumer about the quality and safety of local food products, the questionnaire was included 19 questions for product quality, price, distribution and promotion as a tool to survey the opinions of 128 consumers in Baghdad, the data was analyzed by using percentage, weighted mean, and weight percent, the results obtained showed that the Iraqi consumer prefer local food products for their high quality and appropriate price, however they need attention to packaging, promotion and distribution.

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Publication Date
Tue Aug 23 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Face mask detection based on algorithm YOLOv5s
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

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