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Idiopathic cystic artery aneurysm complicated with hemobilia and acute pancreatitis

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Hepatobiliary & Pancreatic Diseases International 2008年第5期7卷 547-550页

作者： subhi J.al'Aref Husham Abdel-Rahman Nasir Hussain Weill Cornell Medical College in Qatar P.O.Box 24144 DohaQatar Hamad Medical Corporation-General Surgery Department DohaQatar

BACKGROUND:Aneurysm of the cystic artery is no common,and it is a rare cause of *** o reported cases are pseudoaneurysms resulting from eithe an inflammatory process in the abdomen or abdomina trauma. METHOD:We report a healthy individual who developed hemobilia and acute pancreatitis associated with cysti artery aneurysm. RESULT:The patient was managed with angio-embolization with an uneventful post-embolization course. CONCLUSIONS:Visceral artery aneurysms are rare and can rupture with potentially grave outcome due to excessive *** embolization as a common method of treatment for visceral artery aneurysms was used in ou patient with good outcome.

关键词： aneurysm cystic artery

Parameter Tuned Deep Learning Based Traffic Critical Prediction Model on Remote Sensing Imaging

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Computers, Materials & Continua 2023年第5期75卷 3993-4008页

作者： Sarkar Hasan Ahmed Adel al-Zebari Rizgar R.Zebari subhi R.M.Zeebaree Computer Networks Department Sulaimani Polytechnic UniversitySulaimaniIraq Information Technology Department Technical College of Informatics-AkreDuhok Polytechnic UniversityIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Remote sensing(RS)presents laser scanning measurements,aerial photos,and high-resolution satellite images,which are utilized for extracting a range of traffic-related and road-related *** has a weakness,such as traffic fluctuations on small time scales that could distort the accuracy of predicted road and traffic *** article introduces an Optimal Deep Learning for Traffic Critical Prediction Model on High-Resolution Remote Sensing Images(ODLTCP-HRRSI)to resolve these *** presented ODLTCP-HRRSI technique majorly aims to forecast the critical traffic in smart *** attain this,the presented ODLTCP-HRRSI model performs two major *** the initial stage,the ODLTCP-HRRSI technique employs a convolutional neural network with an auto-encoder(CNN-AE)model for productive and accurate traffic ***,the hyperparameter adjustment of the CNN-AE model is performed via the Bayesian adaptive direct search optimization(BADSO)*** experimental outcomes demonstrate the enhanced performance of the ODLTCP-HRRSI technique over recent approaches with maximum accuracy of 98.23%.

关键词： Remote sensing images traffic prediction deep learning smart cities intelligent transportation systems

Case Report: Unusual Complication Post Otoplasty

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Modern Plastic Surgery 2018年第1期8卷 1-7页

作者： Fatima al subhi Department of Plastic Surgery Prince Sultan Military Medical City Riyadh Saudi Arabia

Otoplasty is very commonly used for the surgical correction of prominent ears. This procedure generally does not involve major complications. Pain and itching, hematoma and bleeding and infection are the most common complications generally observed in post otoplasty patients. We present a case of a 13 years old boy who showed abnormal swelling from the pre- to the post-auricular area throughout the temporal region one day after the surgery. This case is distinct as the swelling was without the involvement of active bleeding but hematoma like complication at the site of surgery. The investigations were undertaken and the probable cause for these unusual observations were most likely related to lymphatic malformation.

关键词： Otoplasty Unusual Complication Swelling Pre-Post Auricular Area No Hematoma Lymphatic Malformation

STUDIES ON ULTRASONIC ABSORPTION AND VISCO-RELAXATION OF POLY (ETHYLENE GLYCOL) AQUEOUS SOLUTIONS

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Chinese Journal of Polymer Science 1989年第3期7卷 270-279页

作者： subhi KEMal HASSUN alIA ABDULMUHSIN SHIHAB FATIMA ABDULAMIR JASSIM Physics Department-College of Education-University of Baghdad Iraq.Physics Department-College of Education-University of BaghdadIraq.Physics Department-College of Education-University of BaghdadIraq.

Ultrasonic absorption and velocity measurements were made on aqueous solutions of poly (ethylene glycol)(PEG)of different molecular weights and concentrations, using a pulse sender-receiver ultrasonic generator, Measurements were obtained at a frequency of 2MHz. , and a temperature of 293 K. The results show a linear increase of the Values of velocity, density and viscosity with increase of molecu lar weight and concentration of PEG. On the contrary, the attenuation values decreased with increase of molecular weight and concentration of PEG. A mathematical equation correlating relaxation amplitude and molecular weight of the polymer is suggested. This was applied to calculate the molecular weights of unknown samples of PEG from their measured relaxation amplitude. The results obtained were in good agreement with those obtained from osmometry.

关键词： PEG ETHYLENE GLYCOL STUDIES ON ULTRASONIC ABSORPTION AND VISCO-RELAXATION OF POLY

Characterization of Unsaturated Polyester Filled with Waste Coconut Shells, Walnut Shells, and Carbon Fibers

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Fluid Dynamics & Materials Processing 2023年第10期19卷 2449-2469页

作者： Marwah subhi Attallah Reem alaa Mohammed Ruaa Haitham Abdel-Rahim Department of Materials Engineering University of Technology-IraqBaghdadIraq

This study aims to evaluate the erosion behavior and the hardness of hybrid composites made of varying amounts of coconut shells,walnut shells,and carbonﬁbers dispersed in a polyester ***(L16)Taguchi experiments were used to determine the optimal combination of *** particular,an erosion device con-sisting of a motor with a constantﬂow rate of 45 L/min,a pump with a diameter of 40 mm,a nozzle with a dia-meter of 5 mm,and a tank made of“perspex glass”55 cm long,30 cm tall,and 25 cm wide was *** tests were conducted by varying the sample-to-nozzle distance,the pattern angle,and the sand particle *** results have revealed that the presence of 7.5%by weight of waste coconut shell,for conditions corresponding to 90°angle,sand size 425μm,stand distance 30 cm,gives the best wear resistance(3.04×10^(-5) g/g).Theﬁller content and sand particle size affect the erosive rate,with the angle playing a secondary *** distance between the sample and the nozzle has a weaker effect on erosive *** hardness results show that the models(UP-5%carbonﬁber-2.5-3.5-4.5-5.5-6.5-7.5 wt.%waste coconut shell)give the best values for prayer compared to the samples(UP-5 wt.%carbonﬁber-2.5-3.5-4.5-5.5-6.5-7.5 wt.%waste walnut shell).

关键词： Unsaturated polyester resin carbonﬁber waste coconut shell walnut shell erosive behavior Taguchi’s method L16

Modified Wild Horse Optimization with Deep Learning Enabled Symmetric Human Activity Recognition Model

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Computers, Materials & Continua 2023年第5期75卷 4009-4024页

作者： Bareen Shamsaldeen Tahir Zainab Salih Ageed Sheren Sadiq Hasan subhi R.M.Zeebaree Accounting Department College of Administration and EconomicsUniversity of DuhokDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq ITM Department Technical College of AdministrativeDuhok Polytechnic UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Traditional indoor human activity recognition(HAR)is a timeseries data classification problem and needs feature ***,considerable attention has been given to the domain ofHARdue to the enormous amount of its real-time uses in real-time applications,namely surveillance by authorities,biometric user identification,and health monitoring of older *** extensive usage of the Internet of Things(IoT)and wearable sensor devices has made the topic of HAR a vital subject in ubiquitous and mobile *** more commonly utilized inference and problemsolving technique in the HAR system have recently been deep learning(DL).The study develops aModifiedWild Horse Optimization withDLAided Symmetric Human Activity Recognition(MWHODL-SHAR)*** major intention of the MWHODL-SHAR model lies in recognition of symmetric activities,namely jogging,walking,standing,sitting,*** the presented MWHODL-SHAR technique,the human activities data is pre-processed in various stages to make it compatible for further processing.A convolution neural network with an attention-based long short-term memory(CNNalSTM)model is applied for activity *** MWHO algorithm is utilized as a hyperparameter tuning strategy to improve the detection rate of the CNN-alSTM *** experimental validation of the MWHODL-SHAR technique is simulated using a benchmark *** extensive comparison study revealed the betterment of theMWHODL-SHAR technique over other recent approaches.

关键词： Human activity recognition symmetry deep learning machine learning pattern recognition time series classification

The High Energy Region of the Absorption Edge of a-Si:H, a Theoretical Study—III

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Materials Sciences and Applications 2012年第8期3卷 562-565页

作者： Salwan Kamal Jamil al-Ani Abdullah Ibrahim subhi Saeed al-Rawi Physics Department College of Science for Women Baghdad University Baghdad Iraq

In this paper we try to give a reasonable account for the origin of the experimental optical energy gap Eo of a-Si:H deduced from the plot due to Cody ( vs. E). Using a realistic model density of states diagram for a-Si:H and the constant dipole matrix element assumption, and a reasonable definition of the real optical energy gap EG, a new theoretical equation for ε2(E) was derived. The plot of the square root of this function as a function of the photon energy E for appropriate fitting parameters gives a straight line fit in the energy region of significance extrapolating to the energy axis at a value similar to the experimental optical gap but about 0.1 eV lower than the theoretical optical gap EG proposed in our paper. We conclude that the experimental optical gap Eo does not necessarily coincide with any optical transition threshold in the density of states diagram of a-Si:H.

关键词： High Energy Absorption Edge

A Comprehensive Investigation of Machine Learning Feature Extraction and ClassificationMethods for Automated Diagnosis of COVID-19 Based on X-ray Images

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Computers, Materials & Continua 2021年第3期66卷 3289-3310页

作者： Mazin Abed Mohammed Karrar Hameed Abdulkareem Begonya Garcia-Zapirain Salama A.Mostafa Mashael S.Maashi alaa S.al-Waisy Mohammed Ahmed subhi Ammar Awad Mutlag Dac-Nhuong Le College of Computer Science and Information Technology University of AnbarRamadi31001Iraq College of Agriculture Al-Muthanna UniversitySamawah66001Iraq eVIDA Lab University of DeustoBilbao48007Spain Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn MalaysiaJohor86400Malaysia Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia Faculty of Engineering and Built Environment Universiti Kebangsaan MalaysiaBangi43600Malaysia Pure Science Department Ministry of EducationGeneral Directorate of CurriculaBaghdad10Iraq Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam

The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global *** biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 *** this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 ***(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection *** on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 *** comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.

关键词： Coronavirus disease COVID-19 diagnosis machine learning convolutional neural networks resnet50 artificial neural network support vector machine X-ray images feature transfer learning

Solar Radiation Prediction Using Satin Bowerbird Optimization with Modified Deep Learning

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Computer Systems Science & Engineering 2023年第9期46卷 3225-3238页

作者： Sheren Sadiq Hasan Zainab Salih Agee Bareen Shamsaldeen Tahir subhi R.M.Zeebaree ITM Department Technical College of AdministrativeDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Accounting Department College of Adminstration and EconomicsUniversity of DuhokDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Solar energy will be a great alternative to fossil fuels since it is clean and *** photovoltaic(PV)mechanism produces sunbeams’green energy without noise or *** PV mechanism seems simple,seldom malfunctioning,and easy to *** energy productivity significantly contributes to smart grids through many small PV *** solar radiation(SR)prediction could substantially reduce the impact and cost relating to the advancement of solar *** recent times,several SR predictive mechanism was formulated,namely artificial neural network(ANN),autoregressive moving average,and support vector machine(SVM).Therefore,this article develops an optimal Modified Bidirectional Gated Recurrent Unit Driven Solar Radiation Prediction(OMBGRU-SRP)for energy *** presented OMBGRU-SRP technique mainly aims to accomplish an accurate and time SR prediction *** accomplish this,the presented OMBGRU-SRP technique performs data preprocessing to normalize the solar ***,the MBGRU model is derived using BGRU with an attention mechanism and skip *** last,the hyperparameter tuning of the MBGRU model is carried out using the satin bowerbird optimization(SBO)algorithm to attain maximum prediction with minimum error *** SBO algorithm is an intelligent optimization algorithm that simulates the breeding behavior of an adult male Satin Bowerbird in the *** experiments were conducted to demonstrate the enhanced SR prediction *** experimental values highlighted the supremacy of the OMBGRU-SRP algorithm over other existing models.

关键词： Solar radiation prediction deep learning parameter optimization energy management sustainability