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Correlation between the skull base fracture and the incidence of intracranial hemorrhage in patients with traumatic brain injury

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中华创伤杂志(英文版) 2019年第5期22卷 286-289页

作者： Ahmad Faried Danny Halim Ingrid Ayke Widjaya Rendy Febrian Badri syailendra fii sulaiman Muhammad Z Arifin BandungInjuryResearchUnit FacultyofMedicineUniversitasPadjadjaranBandungIndonesiaDepartmentofNeurosurgeryFacultyofMedicineUniversitasPadjadjaranDr.HasanSadikinHospitalBandungIndonesiaDepartmentofNeurosurgeryFacultyofMedicineUniversitasPadjadjaranDr.HasanSadikinHospitalBandungIndonesiaDepartmentofNeurosurgeryFacultyofMedicineUniversitasPadjadjaranDr.HasanSadikinHospitalBandungIndonesiaDepartmentofNeurosurgeryFacultyofMedicineUniversitasPadjadjaranDr.HasanSadikinHospitalBandungIndonesiaDepartmentofNeurosurgeryFacultyofMedicineUniversitasPadjadjaranDr.HasanSadikinHospitalBandungIndonesi DepartmentofNeurosurgery FacultyofMedicineUniversitasPadjadjaranDr.HasanSadikinHospitalBandungIndonesia

Purpose: A head injury (HI) may cause a skull fracture, which may or may not be associated with injury to the brain. In essence, a skull base fracture (SBF) is a linear fracture at the base of the skull. Loss of consciousness and Glasgow coma score (GCS) may vary depending on an associated intracranial pathology. The pathomechanism is believed to be caused by high energy impact directly to the mastoid and supraorbital bone or indirectly from the cranial vault. Aim of this study is to define the correlation between SBF and intracranial hemorrhage (ICH) in patients with HI. Methods: Analysis of data obtained from a retrospective review of medical records and from a systematized database pertaining to diagnostic criteria of SBF patients based only on clinical symptoms associated with ICH caused by HI treated in the Department of Neurosurgery at Dr. Hasan Sadikin Hospital, Bandung, Indonesia from January 1, 2012 to December 31, 2017. The exclusion criteria included age less than 15 years and no head computed tomography (CT) scan examination provided. Results: A total of 9006 patients were included into this study in which they were divided into 3 groups: group 1, HI with no ICH; group 2, HI with single ICH and group 3, HI with multiple ICH. In all the SBF cases, SBF at anterior fossa accounted for 69.40% of them, which were mostly accompanied with mild HI (64.70%). Severity of HI and site of SBF correlated with the existence of traumatic brain lesions on CT scan, thus these factors were able to predict whether there were traumatic brain lesions or not. Most of the patients with epidural hemorrhage (EDH) has single traumatic lesion on CT scan, whereas most of the patients with cerebral contusion (CC) has multiple traumatic lesions on CT scan. On patients with both traumatic brain injury and SBF, most of the patients with anterior fossa SBF has EDH; whereas most of the patients with middle fo

关键词： Skull base fracture Intracranial hemorrhage Traumatic brain injury

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Voids size distribution in gelled waxy crude oil under dynamic and static cooling

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Petroleum Research 2024年第1期9卷 109-114页

作者： Girma T.Chala Shaharin A.sulaiman Department of Mechanical Engineering(Well Engineering) International College of Engineering and ManagementP.O.Box 2511C.P.O Seeb 111MuscatOman Department of Mechanical Engineering Universiti Teknologi PETRONASBandar Seri Iskandar37500TronohPerakMalaysia

Waxy crude oil is known for its high wax contents that can potentially result in gelling following sufficient cooling of the transportation line in the subsea bed at offshore *** gelling over the entire lines requires an accurately predicted restart pressure to restart the clogged and idle ***,the common way of predicting the restart pressure has been reported to result in over-designed and predicted piping *** research findings evidenced the formation of voids which would reduce the restart pressure *** study conducted in this paper is aimed at investigating the voids size distribution in gelled crude oil across and along transportation *** of experiments simulating crude oil transportation during both static and dynamic cooling were *** gelled crude oil below the pour point temperature was then scanned using a Magnetic Resonance Imaging(MRI)system to detect the voids *** resulting voids at each scanning cross-section were quantified,and their distributions were *** was observed that dynamic cooling had minimal impacts on the voids size difference along the pipeline with the difference in voids areas within 10 mm^(2) to be twice and uniform for the entire flow rates ***,voids size in statically cooled waxy crude oil was found to be highly distributed with a maximum of 6 voids size distribution in 10 mm2 *** low-end temperature had the highest size difference while the difference was decreasing with higher end *** study shows that the voids amount in dynamically cooled waxy crude oil could also be estimated with lower numbers of cross-sectional voids ***,the higher cross-sectional voids detection is recommended while estimating voids in statically cooled waxy crude oil.

关键词： Gelled crude oil Voids size distribution Dynamic cooling Static cooling

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An Effective Hybrid Model of ELM and Enhanced GWO for Estimating Compressive Strength of Metakaolin-Contained Cemented Materials

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1521-1555页

作者： Abidhan Bardhan Raushan Kumar Singh Mohammed Alatiyyah sulaiman Abdullah Alateyah Department of Civil Engineering National Institute of Technology PatnaPatnaIndia Department of Computer Engineering and Applications GLA UniversityMathuraIndia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science College of Science and ArtsQassim UniversityUnaizahSaudi Arabia

This research proposes a highly effective soft computing paradigm for estimating the compressive strength(CS)of metakaolin-contained cemented *** proposed approach is a combination of an enhanced grey wolf optimizer(EGWO)and an extreme learning machine(ELM).EGWO is an augmented form of the classic grey wolf optimizer(GWO).Compared to standard GWO,EGWO has a better hunting mechanism and produces an optimal *** EGWO was used to optimize the ELM structure and a hybrid model,ELM-EGWO,was *** train and validate the proposed ELM-EGWO model,a sum of 361 experimental results featuring five influencing factors was *** on sensitivity analysis,three distinct cases of influencing parameters were considered to investigate the effect of influencing factors on predictive *** consequences show that the constructed ELM-EGWO achieved the most accurate precision in both training(RMSE=0.0959)and testing(RMSE=0.0912)*** outcomes of the ELM-EGWO are significantly superior to those of deep neural networks(DNN),k-nearest neighbors(KNN),long short-term memory(LSTM),and other hybrid ELMs constructed with GWO,particle swarm optimization(PSO),harris hawks optimization(HHO),salp swarm algorithm(SSA),marine predators algorithm(MPA),and colony predation algorithm(CPA).The overall results demonstrate that the newly suggested ELM-EGWO has the potential to estimate the CS of metakaolin-contained cemented materials with a high degree of precision and robustness.

关键词： Metakaolin-contained cemented materials compressive strength extreme learning machine grey wolf optimizer swarm intelligence uncertainty analysis artificial intelligence

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Randomization Strategies in Image Steganography Techniques:A Review

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Computers, Materials & Continua 2024年第8期80卷 3139-3171页

作者： AFM Zainul Abadin Rossilawati sulaiman Mohammad Kamrul Hasan Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia(UKM)BangiSelangor43600Malaysia Department of Information and Communication Engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Image steganography is one of the prominent technologies in data hiding *** system performance mostly depends on the embedding *** goal is to embed strictly confidential information into images without causing perceptible changes in the original *** randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an *** implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this *** review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego *** fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and ***,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.

关键词： Information hiding image steganography randomized embedding techniques payload capacity imperceptibility

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Credit Card Fraud Detection Using Improved Deep Learning Models

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Computers, Materials & Continua 2024年第1期78卷 1049-1069页

作者： Sumaya S.sulaiman Ibraheem Nadher Sarab M.Hameed Computer Science Department Al-Mustansiriya UniversityBaghdad10001Iraq Computer Science Department University of BaghdadBaghdad10001Iraq Faculty of Basic Education Al-Mustansiriya UniversityBaghdad10001Iraq

Fraud of credit cards is a major issue for financial organizations and *** fraudulent actions become more complex,a demand for better fraud detection systems is *** learning approaches have shown promise in several fields,including detecting credit card ***,the efficacy of these models is heavily dependent on the careful selection of appropriate *** paper introduces models that integrate deep learning models with hyperparameter tuning techniques to learn the patterns and relationships within credit card transaction data,thereby improving fraud *** deep learning models:AutoEncoder(AE),Convolution Neural Network(CNN),and Long Short-Term Memory(LSTM)are proposed to investigate how hyperparameter adjustment impacts the efficacy of deep learning models used to identify credit card *** experiments conducted on a European credit card fraud dataset using different hyperparameters and three deep learning models demonstrate that the proposed models achieve a tradeoff between detection rate and precision,leading these models to be effective in accurately predicting credit card *** results demonstrate that LSTM significantly outperformed AE and CNN in terms of accuracy(99.2%),detection rate(93.3%),and area under the curve(96.3%).These proposed models have surpassed those of existing studies and are expected to make a significant contribution to the field of credit card fraud detection.

关键词： Card fraud detection hyperparameter tuning deep learning autoencoder convolution neural network long short-term memory resampling

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Trends in Event Understanding and Caption Generation/Reconstruction in Dense Video:A Review

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Computers, Materials & Continua 2024年第3期78卷 2941-2965页

作者： Ekanayake Mudiyanselage Chulabhaya Lankanatha Ekanayake Abubakar sulaiman Gezawa Yunqi Lei Department of Computer Science Xiamen UniversityXiamen361005China Main Library Wayamba University of Sri LankaKuliyapitiya60200Sri Lanka School of Information Engineering Sanming UniversitySanming365004China

Video description generates natural language sentences that describe the subject,verb,and objects of the targeted *** video description has been used to help visually impaired people to understand the *** is also playing an essential role in devolving human-robot *** dense video description is more difficult when compared with simple Video captioning because of the object’s interactions and event *** learning is changing the shape of computer vision(CV)technologies and natural language processing(NLP).There are hundreds of deep learning models,datasets,and evaluations that can improve the gaps in current *** article filled this gap by evaluating some state-of-the-art approaches,especially focusing on deep learning and machine learning for video caption in a dense *** this article,some classic techniques concerning the existing machine learning were *** provides deep learning models,a detail of benchmark datasets with their respective *** paper reviews various evaluation metrics,including Bilingual EvaluationUnderstudy(BLEU),Metric for Evaluation of Translation with Explicit Ordering(METEOR),WordMover’s Distance(WMD),and Recall-Oriented Understudy for Gisting Evaluation(ROUGE)with their pros and ***,this article listed some future directions and proposed work for context enhancement using key scene extraction with object detection in a particular ***,how to improve the context of video description by analyzing key frames detection through morphological image ***,the paper discusses a novel approach involving sentence reconstruction and context improvement through key frame object detection,which incorporates the fusion of large languagemodels for refining *** ultimate results arise fromenhancing the generated text of the proposedmodel by improving the predicted text and isolating objects using various *** keyframes identify dense ev

关键词： Video description video to text video caption sentence reconstruction

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On the interaction phenomena to the nonlinear generalized Hietarinta-type equation

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Journal of Ocean Engineering and Science 2024年第1期9卷 89-97页

作者： Usman Younas T.A.sulaiman Jingli Ren A.Yusuf State Key Laboratory of Power Grid Environmental Protection/Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450001China Faculty of Science Federal University DutseJigawaNigeria Department of Computer Engineering Biruni University IstanbulTurkey

In this paper,we describe the nonlinear behavior of a generalized fourth-order Hietarinta-type equa-tion for dispersive waves in(2+1)*** various wave formations are retrieved by using Hirota’s bilinear method(HBM)and various test function *** Hirota method is a widely used and robust mathematical tool for finding soliton solutions of nonlinear partial differential equa-tions(NLPDEs)in a variety of disciplines like mathematical physics,nonlinear dynamics,oceanography,engineering sciences,and others requires bilinearization of nonlinear *** different wave structures in the forms of new breather,lump-periodic,rogue waves,and two-wave solutions are *** addi-tion,the physical behavior of the acquired solutions is illustrated in three-dimensional,two-dimensional,density,and contour profiles by the assistance of suitable *** on the obtained results,we can assert that the employed methodology is straightforward,dynamic,highly efficient,and will serve as a valuable tool for discussing complex issues in a diversity of domains specifically ocean and coastal *** have also made an important first step in understanding the structure and physical be-havior of complex structures with our findings *** believe this research is timely and relevant to a wide range of engineering *** results obtained are useful for comprehending the fundamental scenarios of nonlinear sciences.

关键词： Hirota’s bilinear method Lump-periodic solutions Breather waves Rouge waves Multi-waves

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New lump interaction complexitons to the(2+1)-dimensional Korteweg-de Vries equation with electrostatic wave potential in plasmas

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Journal of Ocean Engineering and Science 2024年第2期9卷 173-177页

作者： Tukur Abdulkadir sulaiman Abdullahi Yusuf Alrazi Abdeljabbar Mustafa Bayram Department of Computer Engineering Biruni UniversityIstanbulTurkey Department of Mathematics Federal University DutseJigawaNigeria Department of Mathematics Near East University TRNCMersin 10Turkey Department of Mathematics Khalifa University for Science and TechnologyAbu DhabiUAE

A soliton is a packet of self-reinforcing waves that maintains its structure when moving at a constant *** are caused by the cancellation of the medium’s nonlinear and dispersive *** plas-mas,the bilinear form of Hirota will be utilized to investigate the(2+1)-dimensional Korteweg-de Vries equation with electrostatic wave *** for complexiton lump interaction have been *** throw further light on the physical qualities of the recorded data,certain 3-dimensional and contour plots are presented to illustrate the interaction elements of these solutions.

关键词： (2+1)-dimensional Korteweg-de Vries equation Multi waves solutions Brether waves solutions Numerical simulations

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Epigenetic control on transcription of vernalization genes and whole-genome gene expression profile induced by vernalization in common wheat

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Plant Diversity 2024年第3期46卷 386-394页

作者： Yunzhen Li Liujie Jin Xinyu Liu Chao He Siteng Bi sulaiman Saeed Wenhao Yan National Key Laboratory of Crop Genetic Improvement Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhan 430070China

Vernalization is necessary for winter wheat to ***,it is unclear whether vernalization is also required for spring wheat,which is frequently sown in fall,and what molecular mechanisms underlie the vernalization response in wheat *** this study,we examined the molecular mechanisms that regulate vernalization response in winter and spring wheat *** this purpose,we determined how major vernalization genes(VRN1,VRN2,and VRN3)respond to vernalization in these varieties and whether modifications to histones play a role in changes in gene *** also identified genes that are differentially regulated in response to vernalization in winter and spring wheat *** found that in winter wheat,but not in spring wheat,VRN1 expression decreases when returned to warm temperature following *** finding may be associated with differences between spring and winter wheat in the levels of tri-methylation of lysine 27 on histone H3(H3K27me3)and tri-methylation of lysine 4 on histone H3(H3K4me3)at the VRN1 *** of winter wheat transcriptomes before and after vernalization revealed that vernalization influences the expression of several genes,including those involved in leucine catabolism,cysteine biosynthesis,and flavonoid *** findings provide new candidates for further study on the mechanism of vernalization regulation in wheat.

关键词： Wheat Vernalization VRN1 Histone modification Regulate network

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Contemporary Study for Detection of COVID-19 Using Machine Learning with Explainable AI

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Computers, Materials & Continua 2024年第7期80卷 1075-1104页

作者： Saad Akbar Humera Azam sulaiman Sulmi Almutairi Omar Alqahtani Habib Shah Aliya Aleryani Department of Computer Science University of KarachiKarachi75270Pakistan Department of Computing Faculty of Engineering Science and TechnologyHamdard UniversityKarachi75540Pakistan Department of Health Informatics College of Applied Medical SciencesQassim UniversityQassim51452Saudi Arabia Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia

The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic *** this article,a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplored dataset obtained from a private hospital for detecting COVID-19,pneumonia,and normal conditions in chest X-ray images(CXIs)is proposed coupled with Explainable Artificial Intelligence(XAI).Our study leverages less preprocessing with pre-trained cutting-edge models like InceptionV3,VGG16,and VGG19 that excel in the task of feature *** methodology is further enhanced by the inclusion of the t-SNE(t-Distributed Stochastic Neighbor Embedding)technique for visualizing the extracted image features and Contrast Limited Adaptive Histogram Equalization(CLAHE)to improve images before extraction of ***,an AttentionMechanism is utilized,which helps clarify how the modelmakes decisions,which builds trust in artificial intelligence(AI)*** evaluate the effectiveness of the proposed approach,both benchmark datasets and a private dataset obtained with permissions from Jinnah PostgraduateMedical Center(JPMC)in Karachi,Pakistan,are *** 12 experiments,VGG19 showcased remarkable performance in the hybrid dataset approach,achieving 100%accuracy in COVID-19 *** classification and 97%in distinguishing normal ***,across all classes,the approach achieved 98%accuracy,demonstrating its efficiency in detecting COVID-19 and differentiating it fromother chest disorders(Pneumonia and healthy)while also providing insights into the decision-making process of the models.

关键词： COVID-19 detection deep neural networks support vector machine CXIs InceptionV3 VGG16 VGG19 t-SNE embedding CLAHE attention mechanism XAI

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