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A Prediction of Skin Cancer using Mean-Shift Algorithm with Deep Forest Classifier
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      Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift algorithm is used for segmenting the affected areas of skin cancer images. Finally, these segmented images are given to a deep learning classifier called Deep forest for prediction of skin cancer. The experiments are carried out on two publicly available datasets called ISIC-2019 and HAM10000 datasets for the analysis of segmentation and classification. From the outcomes, it is clearly verified that the projected model achieved better performance than the existing deep learning techniques.

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Publication Date
Tue Jan 02 2007
Journal Name
Journal Of The Faculty Of Medicine Baghdad
An evaluation of methods of inducing sputum production in patient with suspected lung cancer
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Background : the major focus of respiratory cytology is the diagnosis of lung cancer , carcinoma of the lung is now reported to be the most commonly diagnosed non- Cutaneous malignancy in the world. Iraq has faced the increase in incidence of this lethal type of cancer. Sputum cytology is a convenient method of screening and diagnosing primary epithelial tumor of the lung which is of many types include fresh smear ,Sacccomanno smear, and mailing container method.
Methods : Sputum cytological study was done on 50 patients suspected to have pulmonary carcinoma prepared by fresh smear method ,Saccomanno method ,and mailing container
method.One, two,or three samples taken from each patient.Slides were prepared

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Scale-Invariant Feature Transform Algorithm with Fast Approximate Nearest Neighbor
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There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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Publication Date
Sun Sep 29 2019
Journal Name
Iraqi Journal Of Science
Intelligent TRIPLE DES with N Round Based on Genetic Algorithm
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     This work presents an approach for the applying Triple DES (TRIPLE DES) based on using genetic algorithm by adding intelligent feature for TRIPLE DES with N round for genetic algorithm. Encapsulated cipher file with special program which send an acknowledgment to a sender to know who decipher or  broken to  crash it , Thus it is considered as the initial step to improve privacy. The outcome for proposed system gives a good indication that it is a promising system compared with other type of cipher system.

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Sun Apr 02 2006
Journal Name
Journal Of The Faculty Of Medicine Baghdad
possible association of HLA class-1 molecules with colorectal cancer in Iraqi patients
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Background:

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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
Biological & Immunological Effect of Ozonated Water on Certain Skin Pathogenic Bacteria In vivo
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This in vivo study was conducted to investigate the effect of different concentrations of ozonated water on experimentally skin infection with some of bacterial isolates (Pseudomonas aeruginosa and Staphylococcus aureus ) which Showed dermal infection in experimental animals after 48 hours of exposure to these Microorganisms. Results revealed that ozone has the power to accelerated the healing process depending on the perfect concentration of ozonated water used and the severity of infection & nature of causative agent , in which the recovering period was 7 days for the infection caused by P. aeruginosa and 5 day for S.aureus by using the concentration 60 µg/ml . Results also indicated in this study the stimulated effect of O

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Publication Date
Sun Jan 02 2011
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Relation- ships of neonatal septicemia with the mean serum levels of IL-8 and IL-1 in three large hospitals in Baghdad
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Background: Neonatal septicemia (NNS) is the most serious complication in Neonatal Intensive Care Units (NICU) that demand urgent diagnosis and accurate treatment.
Methods: Serum was obtained from 31 neonates aged 1 hour-28 days that were diagnosed clinically and bacteriologically to have neonatal septicemia.
Results: Mean serum levels of both IL-8 and IL-1 recorded a significant increase in neonatal septicemia cases.
Conclusion: Usage of IL-8, IL-1 as diagnostic marker for NNS reduces unnecessary antibiotic therapy and therefore unnecessary costs, pain, and possible side effects of antibiotic
therapy and it may help to reduce development and spread of drug resistant bacteria.

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
The Effects of Soft Laser on Some Blood Parameters of Patients with Breast Cancer
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Background: Soft Laser has been advantageous in medical applications and is widely used in clinical practice. It is applied because it doesn’t cause the significant thermal effects or tissue hurt when irradiated. The blood response to low power laser radiation provides information about processes of laser radiation interaction with live creatures. Objective: The aim of the current work was to evaluate the laser-induced changes of in vitro erythrocyte sedimentation rate (ESR), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC) in patients with breast cancer by irradiating a human blood sample using a green laser and comparing its effects before and after irradiation with the same power density (100mW/c

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