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Atmospheric and Oceanic Science Letters 2013年第4期6卷 173-178页

作者： Mahmoud El-Nouby ADAM khalafallah omar kassem Emad Ali AHMED Quality Assurance Unit(ALI) King Saud University Faculty of Science(Physics Department) South Valley University

The present study quantifies the relationship between ultraviolet-B(UVB) and broadband solar radiation(G) at Qena,*** from 10-year hourly integrated totals for both UVB and G on a horizontal surface were used to determine the best fit between the two radiation *** the basis of the correlation of determination(r2),a second-order polynomial was determined to provide the best *** the purpose of developing an empirical model to estimate UVB,all of the cases of UVB and G from a nine-year study from 2001 to 2009 were *** and seasonal empirical models,as well as a general expression,were established for UVB as a function of *** values of r2 ranged from 0.90 to *** using a new dataset of G,the estimated and the corresponding measured values of UVB were determined to be in good agreement whereby the values of r2 between the two ranged from 0.91 to *** addition,the significance and performance of the regression forms were evaluated with the aid of several statistical analysis *** values of the index of modeling(d) and coefficient of modeling efficiency(ME) were close to ***,the values of RMSE,mean bias error(MBE),and mean absolute error(MAE) were lower than the experimental *** the basis of this analysis,it has been determined that the suggested regression forms can be used to estimate UVB when it difficult to obtain measurements or when measurements are available only for limited periods at the studied region.

关键词： UVB solar radiation broadband solar radia- tion empirical model Egypt

Cervical Cancer Prediction Empowered with Federated Machine Learning

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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad Umar Nasir omar kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy M.A.Khan Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir omar kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad Adnan Khan Muhammad Hasnain Azam Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

Impact of renal transplantation on cardiac morphological and functional characteristics in children and adults

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World Journal of Nephrology 2016年第6期5卷 517-523页

作者： Sahier omar El-Khashab Eman El-Sayed Mohamed Mahmoud A Soliman Hussein Heshmat kassem Amin Roshdy Soliman Department of Nephrology Kasr Al-Ainy Cairo University Department of Medicine Kasr Al-Ainy Cairo University Department of Cardiology Kasr AlAiny Cairo University

AIM To compare the effects of renal transplantation on cardiac functions in children and *** One hundred and ten patients attending the nephrology outpatient clinic were enrolled in this study and were divided into six groups. The first two groups consisted each of 30 renal transplant patients who had a successful renal transplantation more than six months, but less than one year. Group Ⅰ were less than 18 years and group Ⅱ were more than 18 years. The third and fourth groups, each were 20 chronic renal failure patients on regular hemodialysis. Again, group Ⅲ were less than 18 years and group Ⅳ were more than 18 years. Group Ⅴ and Ⅵ(The control Groups) consisted each of 5 subjects below and above 18 years of age, respectively with normal kidney functions. All patients were subjected to history and examination. The kidney functions and the hemoglobin were analyzed. Afterobtaining informed consent, echocardiography was done to all *** There was a statistically significant improvement(P < 0.0001) in all cardiac parameters. A regression in left ventricular end diastolic volume(LVED) both in children(4.7 ± 0.8 to 4.2 ± 0.5) and in adults(5.9 ± 0.7 to 4.9 ± 0.6) were found. There was a regression in left ventricular end systolic volume(LVES) both in children(3.1 ± 0.6 to 2.4 ± 0.4) and in adults(4.1 ± 0.9 to 3.1 ± 0.5). Fractional shortening improves both in children(32.6 ± 5.3 to 41.7 ± 7.6) and in adults(29.0 ± 6.6 to 36.5 ± 4.1). The improvement in ejection fraction(EF) was higher in children(59.7 ± 7.0 to 71.9 ± 6.1) than in adults(52.0 ± 12.5 to 64.8 ± 5.9). However, this degree of improvement(in children: 12.2 ± 5.1) did not show statistical difference(P-value 0.8), when compared to adults(12.7 ± 9.8). CONCLUSION After renal transplantation cardiac functions and morphology(EF/LVED/LVES) do improve markedly and rapidly in both children and adults.

关键词： Echocardiography chronic renal disease Renal transplantation Cardiac problems

Wi-Fi Traffic Enforcement System (WiTE)

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Journal of Transportation Technologies 2013年第2期3卷 142-148页

作者： Fady W. Gendi Tarek K. Refaat Amir H. Sadek Ramez M. Daoud Hassanein H. Amer Chahir S. Fahmy omar M. kassem Hany M. ElSayed Electronics and Communication Department Cairo University Giza Egypt Electronics Engineering Department American University in Cairo New Cairo Egypt

This paper proposes a single integrated traffic enforcement system that is able to recognize and report various traffic violations. It consists of a Wi-Fi infrastructure that enables communication between moving vehicles and a central node. Unlike existing solutions, which address single violations, the proposed model encompasses several issues like exceeding speed limits, entering a no entry street, car theft, congestion and tolling. OPNET simulations were run to test the Wi-Fi model and define its different characteristics and limitations. A proof-of-concept case was modeled, and the proposed architecture succeeded in meeting all design requirements.

关键词： Wi-Fi Traffic Enforcement Vehicular Networking Vehicle to Infrastructure (V2I) Infrastructure to Vehicle (I2V)