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Gamma irradiation-induced effects on the properties of TiO_2 on fluorine-doped tin oxide prepared by atomic layer deposition

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Nuclear Science and Techniques 2018年第7期29卷 191-197页

作者： Syed Mansoor Ali M.S.Algarawi Turki S.ALKhuraiji S.S.Alghamdi muhammad hammad aziz M.Isa Department of Physics and Astronomy College of ScienceKing Saud University National Center for Irradiation Technology King Abdulaziz City for Science and Technology Department of Physics COMSATS Institute of Information and Technology Department of Physics Faculty of ScienceUniversity of GujratHafiz Hayat Campus

The effect of gamma irradiation with different doses(25–75 kGy) on TiO_2 thin films deposited by atomic layer deposition has been studied and characterized by X-ray diffraction(XRD),photoluminescence measurements,ultraviolet–visible(UV–Vis) spectroscopy,and impedance *** XRD results for the TiO_2 films indicate an enhancement of crystallization after irradiation,which can be clearly observed from the increase in the peak intensities upon increasing the gamma irradiation *** UV–Vis spectra demonstrate a decrease in transmittance,and the band gap of the TiO_2 thin films decreases with an increase in the gamma irradiation *** Nyquist plots reveal that the overall charge-transfer resistance increases upon increasing the gamma irradiation *** equivalent circuit,series resistance,contact resistance,and interface capacitance are measured by simulation using Z-view *** present work demonstrates that gamma irradiation-induced defects play a major role in the modification of thestructural,electrical,and optical properties of the TiO_2 thin films.

关键词： TiO2 原子层 Gamma 性质氧化物 gamma Nyquist 光致发光

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Reinforcing Artificial Neural Networks through Traditional Machine Learning Algorithms for Robust Classification of Cancer

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Computers, Materials & Continua 2023年第5期75卷 4293-4315页

作者： muhammad hammad Waseem Malik Sajjad Ahmed Nadeem Ishtiaq Rasool Khan Seong-O-Shim Wajid aziz Usman Habib Department of Computer Sciences and Information Technology University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Computer Science and AI College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of Computer and Network Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of AI&DS School of ComputingNational University of Computer and Emerging SciencesIslamabad44000Pakistan

Machine Learning(ML)-based prediction and classification systems employ data and learning algorithms to forecast target ***,improving predictive accuracy is a crucial step for informed *** the healthcare domain,data are available in the form of genetic profiles and clinical characteristics to build prediction models for complex tasks like cancer detection or *** ML algorithms,Artificial Neural Networks(ANNs)are considered the most suitable framework for many classification *** network weights and the activation functions are the two crucial elements in the learning process of an *** weights affect the prediction ability and the convergence efficiency of the *** traditional settings,ANNs assign random weights to the *** research aims to develop a learning system for reliable cancer prediction by initializing more realistic weights computed using a supervised setting instead of random *** proposed learning system uses hybrid and traditional machine learning techniques such as Support Vector Machine(SVM),Linear Discriminant Analysis(LDA),Random Forest(RF),k-Nearest Neighbour(kNN),and ANN to achieve better accuracy in colon and breast cancer *** system computes the confusion matrix-based metrics for traditional and proposed *** proposed framework attains the highest accuracy of 89.24 percent using the colon cancer dataset and 72.20 percent using the breast cancer dataset,which outperforms the other *** results show that the proposed learning system has higher predictive accuracies than conventional classifiers for each dataset,overcoming previous research ***,the proposed framework is of use to predict and classify cancer patients ***,this will facilitate the effective management of cancer patients.

关键词： ANN decision support systems gene-expression data hybrid classification machine learning predictive analytics

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Amblyopia screening for first and second-grade children in Jordan

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International Journal of Ophthalmology(English edition) 2022年第2期15卷 352-356页

作者： Khalil M.Al-Salem Mohammad S.Saleem Ismat Ereifej Hamzeh M.Alrawashdeh Rayed Falah Hussein Obeidat Asma Ali Abdlmohdi Raeda Zaki Al-Momani Layal Mohammed hammad Omar Ahmad al-Habahbeh Yaqeen M.Assassfeh Laith Ramzi Najib Al-Qsous Ashraf Hatim Adeeb Nasraween Tariq A.Al Maaitah Deya'-Aldin Muneer Hasan Aqeel Ibtehal Eyadeh Awad Alabdulrazzg Abdullah Mahmoud Mohammad Murad Amany Jehad Faleh AL-Zurqan Enas Jamal Mohammad Jaradat Slsabela Emad Suliman Aldhoon Ala'a Majed Dmour Ahmad Talal Asassfeh Jeries Ayman Halaseh Abdel aziz Ammar Daoud Waha Ayman Alkasasbeh Kholoud GH.Matar Department of Ophthalmology and Visual Sciences Mutah UniversityAl-Karak 11183Jordan Royal Medical Services Department of Ophthalmology Amman 11855Jordan Department of Ophthalmology and Visual Sciences Al-Sharif Eye CenterAmman 11194Jordan Jordanian Menistrery of Health IrbidAmman 11855Jordan National Woman's Health Care Center(NWHCC) Amman 11855Jordan

AIM:To share the results of a national screening program for amblyopia in school children in the north of ***:This is a prospective national screening study for *** program rolls first and second-grade children(6 to 7 years old) in the north of *** eye examination included:best-corrected visual acuity,cover-uncover test,and cycloplegic *** visual acuity was tested using an ETDRS visual acuity chart without ***,children were tested with full cycloplegic refraction when the test criteria were *** amblyopia was defined as a best-corrected visual acuity difference of 2 or more *** comparison,bilateral amblyopia was defined as a best-corrected visual acuity of 20/40 or worse in the best ***:The prevalence of amblyopia for the total sample tested(n=17 203) was 2.78%(n=479).The most common cause of amblyopia was hypermetropia(64.45%),followed by previous ocular surgeries(15.1%),myopia(10.43%),strabismus(9.39%),and congenital cataract(0.63%).CONCLUSION:This is the first and only study,identifing modifiable risk factors in Jordanian children with *** their first couple of years of elementary education,many Jordanian children are affected by amblyopia and pass unnoticed.A more governmental effort is needed into screening programs to improve vision in the Jordanian population.

关键词： amblyopia screening Jordan community ophthalmology pediatric ophthalmology population-based study screening program

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