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Fulminant hepatic failure caused by Salmonella paratyphi A infection

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World Journal of Gastroenterology 2006年第32期12卷 5253-5255页

作者： Fahmi Yousef Khan ahmed A Kamha ibrahim Y Alomary Department of Medicine Hamad General Hospital DohaQatar

We report a case of fulminant hepatic failure associated with Salmonella paratyphi A infection, in a 29-yearold patient who was admitted to the intensive care unit （ICU） with fever of two days, headache and vomiting followed by behavioural changes and disorientation. On examination, the patient appeared acutely ill, agitated, confused, and deeply jaundiced. Temperature 38.5℃, pulse 92/min, blood pressure 130/89 mmHg. Both samples of blood grew S. paratyphi A, which was sensitive to ceftriaxone and ciprofloxacin. Ceftriaxon was administered with high-dose dexamethasone. Two weeks after treatment with ceftriaxon, the patient was discharged in satisfactory condition.

关键词： Typhoid hepatitis Fulminant hepatic failure Salmonella paratyphi A

Numerical investigation on the heat transfer enhancement using a confined slot impinging jet with nanofluid

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Propulsion and Power Research 2019年第4期8卷 351-361页

作者： ibrahim K.Alabdaly M.A.ahmed Department of Mechanical Engineering College of EngineeringUniversity of AnbarRamadiAnbarIraq

In this article,laminar convective heat transfer of a confined slot impinging jet with nanofluid has been numerically investigated over Reynolds number ranges of *** circular ribs are mounted on the lower-target surface:one rib located right the stagnation point and another one located on the left of the stagnation ***2-water nanofluid with nanoparticles volume fraction ranging from 0 to 4%and nanoparticles diameters of 30 nm has been *** two-dimensional governing continuity,momentum and energy equations have been solved using finite volume method based on SIMPLE *** effect of Reynolds number,nanoparticles volume fraction,rib height and rib location on the flow and thermal characteristics are presented and *** showed that the average Nusselt number,performance factor,total entropy generation as well as friction factor increase with increasing nanoparticles volume *** addition,it is found that the best thermal-hydraulic performance factor is around 1.89 which is obtained at Reynolds number of 1000,nanoparticles volume fraction of 4%,the rib height of 0.1 and the rib location of 2.

关键词： Jet impingement Nanofluid Entropy generation Thermal-hydraulic performance Finite volume method

Effects of groove-textured surfaces filled with Sn-Ag-Cu and MXene-Ti_(3)C_(2) composite lubricants on tribological properties of CSS-42L bearing steel

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Friction 2022年第7期10卷 1091-1113页

作者： Yawen XUE Chaohua WU Xiaoliang SHI Qipeng HUANG ahmed Mohamed Mahmoud ibrahim School of Mechanical and Electronic Engineering Wuhan University of TechnologyWuhan 430070China Shenzhen Research Institute of Wuhan University of Technology Shenzhen 518000China Department of Production Engineering and Mechanical Design Faculty of EngineeringMinia UniversityEI-Minya 61519Egypt

To improve the tribological performance of CSS-42L bearing steel,smooth surfaces(SSs),groovetextured surfaces(GSs),GSs with Sn-Ag-Cu(GSs-SAC),and GSs with Sn-Ag-Cu-Ti_(3)C_(2)(GSs-SACT)were prepared on *** addition,experimental studies were conducted on tribological *** obtained results indicated that GSs-SACT exhibited the best anti-friction and noise reduction *** remarkable tribological performances were attributed to the synergistic effects of grooves,Sn-Ag-Cu,and MXene-Ti_(3)C_(2).The inconsistent rules of frictional forces were improved by the grooves and SACT,which inhibit the friction-induced *** micro-nano size-effects of MXene-Ti_(3)C_(2) enhanced the repairing effect and anti-friction property of composite lubricants,which improved the profile characteristics of GSs-SACT.

关键词： CSS-42L MXene Sn-Ag-Cu-Ti_(3)C_(2)(SACT) grooves tribological properties friction-induced noise

Detection of Left Ventricular Cavity from Cardiac MRI Images Using Faster R-CNN

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Computers, Materials & Continua 2023年第1期74卷 1819-1835页

作者： Zakarya Farea Shaaf Muhammad Mahadi Abdul Jamil Radzi Ambar ahmed Abdu Alattab Anwar Ali Yahya Yousef asiri Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn MalaysiaParit RajaBatu Pahat86400JohorMalaysia Department of Computer Science College of Science and ArtsSharurahNajran UniversityNajran61441Saudi Arabia Department of Computer Science Faculty of Computer Science and Info.SystemsThamar UniversityDhamar87246Yemen Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

The automatic localization of the left ventricle(LV)in short-axis magnetic resonance(MR)images is a required step to process cardiac images using convolutional neural networks for the extraction of a region of interest(ROI).The precise extraction of the LV’s ROI from cardiac MRI images is crucial for detecting heart disorders via cardiac segmentation or ***,this task appears to be intricate due to the diversities in the size and shape of the LV and the scattering of surrounding tissues across different ***,this study proposed a region-based convolutional network(Faster R-CNN)for the LV localization from short-axis cardiac MRI images using a region proposal network(RPN)integrated with deep feature classification and *** was trained using images with corresponding bounding boxes(labels)around the LV,and various experiments were applied to select the appropriate layers and set the suitable *** experimental findings showthat the proposed modelwas adequate,with accuracy,precision,recall,and F1 score values of 0.91,0.94,0.95,and 0.95,*** model also allows the cropping of the detected area of LV,which is vital in reducing the computational cost and time during segmentation and classification ***,itwould be an ideal model and clinically applicable for diagnosing cardiac diseases.

关键词： Cardiac short-axis MRI images automatic left ventricle localization deep learning models faster R-CNN

BERT-CNN: A Deep Learning Model for Detecting Emotions from Text

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Computers, Materials & Continua 2022年第5期71卷 2943-2961页

作者： ahmed R.Abas ibrahim Elhenawy Mahinda Zidan Mahmoud Othman Department of Computer Science Faculty of Computer and InformaticsZagazig UniversityZagazig44519Egypt Department of Computer Science Faculty of Computers and Information TechnologyFuture University in Egypt11835Egypt

Due to the widespread usage of social media in our recent daily lifestyles,sentiment analysis becomes an important field in pattern recognition and Natural Language Processing(NLP).In this field,users’feedback data on a specific issue are evaluated and *** emotions within the text is therefore considered one of the important challenges of the current NLP *** have been widely studied in psychology and behavioral science as they are an integral part of the human *** describe a state of mind of distinct behaviors,feelings,thoughts and *** main objective of this paper is to propose a new model named BERT-CNN to detect emotions from *** model is formed by a combination of the Bidirectional Encoder Representations from Transformer(BERT)and the Convolutional Neural networks(CNN)for textual *** model embraces the BERT to train the word semantic representation language *** to the word context,the semantic vector is dynamically generated and then placed into the CNN to predict the *** of a comparative study proved that the BERT-CNN model overcomes the state-of-art baseline performance produced by different models in the literature using the semeval 2019 task3 dataset and ISEAR *** BERTCNN model achieves an accuracy of 94.7%and an F1-score of 94%for semeval2019 task3 dataset and an accuracy of 75.8%and an F1-score of 76%for ISEAR dataset.

关键词： BERT-CNN deep learning emotion detection semeval2019 text classification

Geochemistry of lamprophyre dykes, Wadi Sikait area, South Eastern Desert, Egypt

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Chinese Journal Of Geochemistry 2011年第3期30卷 323-331页

作者： ibrahim M.El-Ahmadi Ragab A.ahmed Nuclear Materials Authority El-Maadi P.O.Box 530 Cairo Egypt

The Wadi Sikait area lies at about 95 km southwest of Marsa Alam City along the Red Sea Coast, Eastern Desert, Egypt. It is occupied by Precambrian rocks of ophiolitic mélange, metamorphosed sandstones (MSS), gab-bros and monzogranites which were later intruded by lamprophyre dykes and quartz veins. The lamprophyre dykes were extruded in NW-SE and NE-SW trends cutting monzogranites and metamor-phosed sandstones. The lamprophyres are porphyritic and composed of clinopyroxene, olivine and amphibole phenocrysts enclosed in a fine-grained groundmass of clinopyroxene, amphibole, opaque and lithium mica. The al-teration products are represented by amphibole (tremolite-actinolite and hornblende), carbonate, epidote, chlorite, iddingsite, clay minerals, limonite and serpentine. The Sikait lamprophyre dykes can be classified as alkaline lamprophyres characterized by silica contents rang-ing from 41.65 wt% to 50.88 wt% and Na2O>K2O. They are enriched in LILE, LREE and HFSE, but strongly de-pleted in compatible elements such as Cr and Ni relative to the primitive mantle. Sikait lamprophyres have moderate Zr/Hf (35.6-52.8) and Nb/Ta (20.5-22.5) ratios. Most of these features are attributed to the origin of these dykes from the metasomatized mantle affected by subduction-related fluid. These lamprophyres are compositionally similar to Salu lamprophyres in eastern China. The Sikait lamprophyre samples have high LREE (320×10-6-419×10-6) relative to HREE (20×10-6-33×10-6) with ratios (LREE/HREE=11.6-18.7) and no negative Eu anomaly (Eu/Eu*=0.9-1.04). The relative presence of posi-tive Ce anomaly (Ce/Ce*=1.04) in lamprophyre samples suggests the oxidizing condition under which the REEs were precipitated due to the common occurrence of fluorite and apatite.

关键词：煌斑岩地球化学特征岩脉沙漠埃及二长花岗岩单斜辉石蛇绿混杂岩

Adaptive Power Control Aware Depth Routing in Underwater Sensor Networks

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Computers, Materials & Continua 2021年第10期69卷 1301-1322页

作者： Ghufran ahmed Saiful Islam Ihsan Ali Isra Adil Hayder Abdelmuttlib ibrahim Abdalla ahmed Muhammad Talha Sultan S.Alshamrani Ag Asri Ag ibrahim Department of Computer Science FAST National University of Computer and Emerging Sciences(NUCES)KarachiPakistan Dr.A.Q.Khan Institute of Computer Sciences and Information Technology KahutaPakistan Faculty of Computer Science and Information Technology University of MalayaKuala Lumpur50603Malaysia Department of Computer Science COMSATS University IslamabadIslamabadPakistan Deanship of Scientific Research King Saud UniversityRiyadhSaudi Arabia Department of Information Technology College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia Faculty of Computing and Informatics Universiti Malaysia SabahKota KinabaluSabahMalaysia

Underwater acoustic sensor network(UASN)refers to a procedure that promotes a broad spectrum of aquatic *** can be practically applied in seismic checking,ocean mine identification,resource exploration,pollution checking,and disaster *** confronts many difficulties and issues,such as low bandwidth,node movements,propagation delay,3D arrangement,energy limitation,and high-cost production and arrangement costs caused by antagonistic underwater *** wireless sensor networks(UWSNs)are considered a major issue being encountered in energy management because of the limited battery power of their ***,the harsh underwater environment requires vendors to design and deploy energy-hungry devices to fulfil the communication requirements and maintain an acceptable quality of ***,increased transmission power levels result in higher channel interference,thereby increasing packet *** the facts mentioned above,this research presents a controlled transmission power-based sparsity-aware energy-efficient clustering in *** contributions of this technique is ***,it uses the adaptive power control mechanism to utilize the sensor nodes’battery and reduce channel interference ***,thresholds are defined to ensure successful ***,clustering can be implemented in dense areas to decrease the repetitive transmission that ultimately affects the energy consumption of nodes and interference ***,mobile sinks are deployed to gather information locally to achieve the previously mentioned *** suggested protocol is meticulously examined through extensive simulations and is validated through comparison with other advanced UWSN *** show that the suggested protocol outperforms other procedures in terms of network lifetime and packet delivery ratio.

关键词： UWSNs UASNs QoS

A survey on trust based detection and isolation of malicious nodes in ad-hoc and sensor networks

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Frontiers of Computer Science 2015年第2期9卷 280-296页

作者： Adnan ahmed Kamalrulnizam ABU BAKAR Muhammad ibrahim CHANNA Khalid HASEEB Abdul Waheed KHAN Faculty of Computing Universiti Teknologi Malaysia Johor Bahru 81310 Malaysia Department of Information Technology Quaid-e-Awam University of Engineering Science and Technology Nawabshah 67450 Pakistan

Mobile ad-hoc networks （MANETs） and wireless sensor networks （WSNs） have gained remarkable apprecia- tion and technological development over the last few years. Despite ease of deployment, tremendous applications and significant advantages, security has always been a challeng- ing issue due to the nature of environments in which nodes operate. Nodes＇ physical capture, malicious or selfish behav- ior cannot be detected by traditional security schemes. Trust and reputation based approaches have gained global recog- nition in providing additional means of security for decision making in sensor and ad-hoc networks. This paper provides an extensive literature review of trust and reputation based models both in sensor and ad-hoc networks. Based on the mechanism of trust establishment, we categorize the state- of-the-art into two groups namely node-centric trust mod- els and system-centric trust models. Based on trust evidence, initialization, computation, propagation and weight assign- ments, we evaluate the efficacy of the existing schemes. Fi- nally, we conclude our discussion with identification of some unresolved issues in pursuit of trust and reputation manage- ment.

关键词： trust reputation wireless sensor network mo-bile ad-hoc networks routing node misbehavior

Kernel Granulometric Texture Analysis and Light RES-ASPP-UNET Classification for Covid-19 Detection

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Computers, Materials & Continua 2022年第4期71卷 651-666页

作者： A.Devipriya P.Prabu K.Venkatachalam ahmed Zohair ibrahim Department of Computer Science and Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India Department of Computer Science CHRIST(Deemed to be University)Bangalore560029India Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec Králové50003Hradec KrálovéCzech Republic Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhKSA.P.o.Box:84428Postal Code:11671

This research article proposes an automatic frame work for detectingCOVID -19 at the early stage using chest X-ray image. It is an undeniable factthat coronovirus is a serious disease but the early detection of the virus presentin human bodies can save lives. In recent times, there are so many research solutions that have been presented for early detection, but there is still a lack in needof right and even rich technology for its early detection. The proposed deeplearning model analysis the pixels of every image and adjudges the presence ofvirus. The classifier is designed in such a way so that, it automatically detectsthe virus present in lungs using chest image. This approach uses an imagetexture analysis technique called granulometric mathematical model. Selectedfeatures are heuristically processed for optimization using novel multi scaling deep learning called light weight residual–atrous spatial pyramid pooling(LightRES-ASPP-Unet) Unet model. The proposed deep LightRES-ASPPUnet technique has a higher level of contracting solution by extracting majorlevel of image features. Moreover, the corona virus has been detected usinghigh resolution output. In the framework, atrous spatial pyramid pooling(ASPP) method is employed at its bottom level for incorporating the deepmulti scale features in to the discriminative mode. The architectural workingstarts from the selecting the features from the image using granulometricmathematical model and the selected features are optimized using LightRESASPP-Unet. ASPP in the analysis of images has performed better than theexisting Unet model. The proposed algorithm has achieved 99.6% of accuracyin detecting the virus at its early stage.

关键词： Deep residual learning convolutional neural network COVID-19 X-ray principal component analysis granulo metrics texture analysis