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PDF Biosensing technique for detection of H.pylori bacteria: Israa M.L. SaQari*, Layla M.H. Al-ameri
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Abstract :H.pylori is an important cause of gastric duodenal disease, including gastric ulcers, Mucosa-associated lymphoid tissue (MALT), and gastric carcinoma. biosensors are becoming the most extensively studied discipline because the easy, rapid, low-cost, highly sensitive, and highly selective biosensors contribute to advances in next-generation medicines such as individualized medicine and ultrasensitive point-of-care detection of markers for diseases.  Five of ten patients diagnosed with H.pylori ranging in age from 15–85 participated in this research. who [gastritis, duodenitis, duodenal ulcer (DU), and peptic ulcer (PU)] Suspected H.pylori colonies were identified by the presence of urease, catalase, oxidase activity, and PCR. All parameters are fixed: Laser power:40 mW, size of drops:25 μ, Turbidity:0.5. , Multi modes optical fiber, and Coreless optical fiber to construct optical biosensor (Multimode-Coreless-Multimode) optical fibers based on an inline Mach-Zehnder Interferometer. All samples had a sensitivity. Multimode-Coreless-Multimode optical Biosensor: is a rapid and sensitive method for the detection of H.pylori bacteria.

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The psychological, social and academic problems that encounter students of college of education in Al-Anbaar University /Al-qaim
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The study aims to identify the psychological, social, and academic problems that encounter students at the college of education. To this end, the researcher utilized the descriptive approach, where a questionnaire was used as a tool to collect the study data. The findings of study revealed that the main academic problems are inability to understand what the students read, lack of concentration over the process of studying. The Difficulty of preparation for test. Lack of ability to memorize quickly. As for the prominent social problems: the excessive usage of social media that drove students away from their main tasks, the Lack of participation in social activities, the scarcity the religious information. The psychological problems includ

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Publication Date
Wed Mar 02 2022
Journal Name
International Journal Of Early Childhood Special Education
Understanding the life applications of green chemistry among students of the College of Education for Pure Sciences, Ibn al-Haytham in Iraq
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Publication Date
Wed Mar 30 2022
Journal Name
College Of Islamic Sciences
The interpreter Shamus al- Deen Ibn al – Labban (749H) his biography and scientific efforts
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- Abstract -

 This research tackles one of this nations scholar , was not studied by other researchers . Many of us know nothing about his life , books , arguments in a manner Like other scholars of this nation . Therefore , it is the task of this study , in a response to the favour of Ibn al – Labban on us , to reveal his works .

       This study deals with him through four sections . section one investigate his biography , including six sub divisions regarding his name date of birth , Life , his father life , death , and finally , this section concludes with the embarrassment which might a reader face in differentiation between Ibn al – labban and the other respec

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Publication Date
Fri Feb 20 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Validity of Hounsfield Units from computed tomographic images of mandibular bone in detection of osteoporosis
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Background: The figure for the clinical application of computed tomography have been increased significantly in oral and maxillofacial field that supply the dentists with sufficient data enables them to play a main role in screening osteoporosis, therefore Hounsfield units of mandibular computed tomography view used as a main indicator to predict general skeleton osteoporosis and fracture risk factor. Material and Methods: Thirty subjects (7 males &23 females) with a mean age of (60.1) years underwent computed tomographic scanning for different diagnostic assessment in head and neck region. The mandibular bone quality of them were determined through Hounsfield units of CT scan images and were correlated with the bone mineral density v

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Sat Jun 03 2023
Journal Name
Journal Of Electronic Materials
Thiophosgene Detection by Ag-Decorated AlN Nanotube: A Mechanical Quantum Survey
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The density functional B3LYP is used to investigate the effect of decorating the silver (Ag) atom on the sensing capability of an AlN nanotube (AlN-NT) in detecting thiophosgene (TP). There is a weak interaction between the pristine AlN-NT and TP with the sensing response (SR) of approximately 9.4. Decoration of the Ag atom into the structure of AlN-NT causes the adsorption energy of TP to decrease from − 6.2 to − 22.5 kcal/mol. Also, the corresponding SR increases significantly to 100.5. Moreover, the recovery time when TP is desorbed from the surface of the Ag-decorated AlN-NT (Ag@AlN-NT) is short, i.e., 24.9 s. The results show that Ag@AlN-NT can selectively detect TP among other gases, such as N2, O2, CO2, CO, and H2O.

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Multi – Linear in Multiple Nonparametric Regression , Detection and Treatment Using Simulation
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             It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the

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Publication Date
Mon Jun 07 2021
Journal Name
Jurnal Teknologi
MODELS, DETECTION METHODS, AND CHALLENGES IN DC ARC FAULT: A REVIEW
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The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Wed Jun 24 2015
Journal Name
Chinese Journal Of Biomedical Engineering
Single Channel Fetal ECG Detection Using LMS and RLS Adaptive Filters
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ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.