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Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that the
proposedmethod obtained very good results but it requires more testing on different types of Skin
Cancer Images.

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archives
DETECTION OF sHLA-G PROTEINS IN THE SERA OF PATIENTS INFECTED WITH VISCERAL LEISHMANIASIS
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Visceral leishmaniasis (VL) or kala-azar is one of the worlds most neglected tropical diseases in mortality and fourth in morbidity, rK39 dipstick was used to diagnose the suspected infected patients as cheapest simple technique which can differentiate recent from chronic infection, for disease out-coming, naïve T-lymphocyte cells should be differentiated into pathogen-specific immunity responses, such as T-helper 1(Th-1) or (Th-2). HLA-G is a special protein defined as nonclassical HLA class I molecule can suppress the immune system through prevention of T-cell function by foul all T-cell mechanisms. So, this study aimed to detect and evaluate the level of sHLA-G in the sera of patients infected with VL. The results showed that there was

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Publication Date
Tue Oct 16 2018
Journal Name
International Journal Of Pharmaceutical Quality Assurance
Isolation and Detection of Candida tropicalis from Aborted Placenta in Al-Najaf city/Iraq
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Background: Candida tropicalis is one of the most causes of vulvovaginal candidiasis (VVC) in women. Systemic candidiasis and candidemia may also occur in pregnancies. Objective: This study was carried out to detect and isolate of this yeast from aborted placenta, which may cause severe complications such as spontaneous abortion. Materials and methods: Fresh aborted placenta were collected and washed by normal saline to remove the blood. Then, cut it into portions and place it in test tube containing 5 ml of normal saline. Finally, shake for 10 minutes, after that, cultured for microbial isolation. Isolation and detection were done by some conventional methods with Api candida and CHROMagar. Results: The results showed that four iso

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Influence of Gold Concentration on the Main Detection Parameters of Ge-Au Photoconductive Detector
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Ge-Au infrared photoconductive detection was prepared from germanium single crystal which were doped with different gold concentration using thermal evaporation. The spectral resonsivity (Rλ), spectral detectivity (D*) were determined as function of wavelength, also the resistance, conductivity in dark and with illumination to infrared radiation, the gain and relative photo response have been measured with different gold concentration. Remarkable improvements in the photoresponse gain were observed for the highest resistance specimen at the expense of spectral detectivity values.

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Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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Publication Date
Fri Jan 01 2016
Journal Name
World Journal Of Experimental Biosciences
Detection of anti-Helicobacter pylori antibodies in sera of women with recurrent spontaneous abortion
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To determine the relationship between Helicobacter pylori infection and reproduction disorder (recurrent spontaneous abortion), twenty women patients who undergo spontaneous abortion during first trimester of pregnancy (20-38) years and have been investigated from 2015/12/1 -2016/3/1 and compared to fifteen healthy individuals. All subjects were carried out to measure anti-H. pylori IgA and anti- H. pylori IgG antibodies by enzyme linked immunosorbent assay (ELISA). There was significant elevation (p≤ 0.05) in concentration of anti- H. pylori IgG Abs (6.30± 0.99) compared to control group (4.48± 0.61) and IgA Abs (5.42 ± 0.90 U /ml) as compared to control group (3.92 ± 0.41 U/ml). The percentage of H. pylori IgG and IgA was 20% and 25

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Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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Publication Date
Fri Jun 10 2022
Journal Name
Eurasian Chemical Communications
Detection of lead and cadmium in types of chips from local markets in Baghdad
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Publication Date
Wed Mar 05 2025
Journal Name
Iraqi Journal Of Biotechnology,
Molecular Detection of Esp and Ace Genes in Enterococcus faecalis Isolated from Endodontic Infections
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Enterococcus faecalis is a natural inhabitant of the human gastrointestinal tract but can become dominant and cause infections when the intestinal homeostasis is disrupted. Enterococcal bacteria are considered one of the main reasons for the failure of endodontic treatment. This study aim to isolation and identification of E.faecalis depended on phenotype and molecular method, the phenotypic patterns using traditional biochemical methods, and then diagnosed it based on the genotypes and using specialized primers for 16srRNA and D-Ala: D-Ala ligase genes using polymerase chain reaction, In order to achieve successful treatment, it is necessary to study the bacterial behavior within the root canal system together with their resistance and def

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Detection of Type 2 Diabetes Mellitus in Serum from Women with Polycystic Ovarian Syndrome
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Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorder. To determine the metabolic disorders in women with PCOS, (25) women with PCOS ages (15 - 47) years have been investigated and compared with (20) healthy individuals. All the studied groups were carried out to measure fasting blood sugar, (anti-GAD Ab, anti ?-islet cell Ab by IFAT) and measured insulin level by ELISA. There was significant elevation in the concentration of fasting blood sugar than in control groups (p ? 0.05) and there was negative results for anti-GAD Ab and anti ?-islet cell Ab by IFAT test for serum of women with PCOS, while there was significant differences in the insulin level for women with PCOS compared with control groups (p ? 0.05), these

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