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UNet Based onMulti-Object Segmentation and Convolution Neural Network for Object Recognition

Computers, Materials & Continua 2024年第7期80卷 1563-1580页

作者： Nouf abdullah Almujally Bisma Riaz Chughtai Naif Al Mudawi Abdulwahab Alazeb Asaad Algarni Hamdan A.Alzahrani Jeongmin Park Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Information Technology Department College of Computing and InformaticsSaudi Electronic UniversityRiyadh13316Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Republic of Korea

The recent advancements in vision technology have had a significant impact on our ability to identify multiple objects and understand complex *** technologies,such as augmented reality-driven scene integration,robotic navigation,autonomous driving,and guided tour systems,heavily rely on this type of scene *** paper presents a novel segmentation approach based on the UNet network model,aimed at recognizing multiple objects within an *** methodology begins with the acquisition and preprocessing of the image,followed by segmentation using the fine-tuned UNet ***,we use an annotation tool to accurately label the segmented *** labeling,significant features are extracted from these segmented objects,encompassing KAZE(Accelerated Segmentation and Extraction)features,energy-based edge detection,frequency-based,and blob *** the classification stage,a convolution neural network(CNN)is *** comprehensive methodology demonstrates a robust framework for achieving accurate and efficient recognition of multiple objects in *** experimental results,which include complex object datasets like MSRC-v2 and PASCAL-VOC12,have been *** analyzing the experimental results,it was found that the PASCAL-VOC12 dataset achieved an accuracy rate of 95%,while the MSRC-v2 dataset achieved an accuracy of 89%.The evaluation performed on these diverse datasets highlights a notably impressive level of performance.

关键词： UNet segmentation blob fourier transform convolution neural network

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Spatio-temporal clustering analysis of COVID-19 cases in Johor

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Infectious Disease Modelling 2024年第2期9卷 387-396页

作者： Fong Ying Foo Nuzlinda Abdul Rahman Fauhatuz Zahroh Shaik abdullah Nurul Syafiah Abd Naeeim School of Mathematical Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia

At the end of the year 2019,a virus named SARS-CoV-2 induced the coronavirus disease,which is very contagious and quickly spread around the *** new infectious disease is called *** areas,such as the economy,social services,education,and healthcare system,have suffered grave consequences from the invasion of this deadly ***,a thorough understanding of the spread of COVID-19 is required in order to deal with this outbreak before it becomes an infectious *** this research,the daily reported COVID-19 cases in 92 sub-districts in Johor state,Malaysia,as well as the population size associated to each sub-district,are used to study the propagation of COVID-19 disease across space and time in *** time frame of this research is about 190 days,which started from August 5,2021,until February 10,*** clustering technique known as spatio-temporal clustering,which considers the spatio-temporal metric was adapted to determine the hot-spot areas of the COVID-19 disease in Johor at the sub-district *** results indicated that COVID-19 disease does spike in the dynamic populated sub-districts such as the state's economic centre(Bandar Johor Bahru),and during the festive *** findings empirically prove that the transmission rate of COVID-19 is directly proportional to human mobility and the presence of *** the other hand,the result of this study will help the authority in charge in stopping and preventing COVID-19 from spreading and become worsen at the national level.

关键词： Disease mapping COVID-19Hot-spot areas Sub-district level Spatio-temporal clustering Scan statistics

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A gated recurrent unit model to predict Poisson’s ratio using deep learning

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 123-135页

作者： Fahd Saeed Alakbari Mysara Eissa Mohyaldinn Mohammed Abdalla Ayoub Ibnelwaleed A.Hussein Ali Samer Muhsan Syahrir Ridha abdullah Abduljabbar Salih Petroleum Engineering Department Universiti Teknologi PETRONAS32610Bandar Seri IskandarPerakMalaysia Institute of Hydrocarbon Recovery Universiti Teknologi PETRONAS32610Bandar Seri IskandarPerakMalaysia Gas Processing Center College of EngineeringQatar UniversityP.O.Box 2713DohaQatar Department of Chemical Engineering College of EngineeringQatar UniversityP.O.Box 2713DohaQatar Mechanical Engineering Department Universiti Teknologi PETRONAS32610Bandar Seri IskandarPerakMalaysia

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand *** models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical *** this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error *** GRU model showed the proper trends,and the model data ranges were wider than previous *** GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other *** GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,*** group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

关键词： Static Poisson’s ratio Deep learning Gated recurrent unit(GRU) Sand control Trend analysis Geomechanical properties

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Peat properties of a tropical forest reserve adjacent to a fire-break canal

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Journal of Forestry Research 2024年第1期35卷 155-167页

作者： Dayang Nur Sakinah Musa Mohd Zahirasri Mohd Tohir Xinyan Huang Luqman Chuah abdullah Mohamad Syazaruddin Md Said Muhammad Firdaus Sulaiman Safety Engineering Interest Group(SEIG) Department of Chemical and Environmental EngineeringFaculty of EngineeringUniversiti Putra Malaysia43400 UPM SerdangSelangorMalaysia International Tropical Forestry Programme Faculty of Tropical ForestryUniversiti Malaysia SabahSabahMalaysia Department of Land Management Faculty of AgricultureUniversiti Putra MalaysiaSelangorMalaysia Research Centre for Fire Safety Engineering Department of Building Environment and Energy EngineeringThe Hong Kong Polytechnic UniversityHong KongPeople’s Republic of China

Tropical peat comprises decomposed dead plant material and acts like a sponge to absorb water,making it fully ***,drought periods dry it readily and increases its vulnerability to *** fires emit greenhouse gases and particles contributing to haze,and prevention by constructing fire-break canals to reduce fire spread into forest reserves is *** paper aims to determine peat physical and chemical properties near a fire-break canal at different fire frequency *** sampling was conducted at two forest reserves in Malaysia which represent low fire frequency and high fire frequency *** results show that peat properties were not affected by the construction of a fire-break canal,however lignin and cellulose content increased significantly from the distance of the canal in both *** study concluded that fire frequency did not significantly influence peat properties except for *** higher fibre content in the high frequency area did not influence moisture content nor the ability to regain ***,fire frequency might contribute differently to changes in physical and chemical properties,hence management efforts to construct fire-break canals and restoration efforts should protect peatlands from further *** findings will benefit future management and planning for forest reserves.

关键词： Peat fire Peat properties Fire-break canals Forest reserves

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Stiffness Characteristics of a Basic Nonlinear Air Spring Model

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World Journal of Engineering and Technology 2024年第3期12卷 455-465页

作者： abdullah S. Alsuwaiyan Department of Mechanical Engineering College of Engineering Qassim University Buraydah Saudi Arabia

This study predicts the characteristics of a compressible polytropic air spring model. A second-order nonlinear autonomous air spring model is presented. The proposed model is based on the assumption that polytropic processes occur. Isothermal and isentropic compression and expansion of the air within the spring chambers are the two scenarios that are taken into consideration. In these situations, the air inside the spring chambers compresses and expands, resulting in nonlinear spring restoring forces. The MATLAB/Simulink software environment is used to build a numerical simulation model for the dynamic behavior of the air spring. To quantify the values of the stiffnesses of the proposed models, a numerical solution is run over time for various values of the design parameters. The isentropic process case has a higher dynamic air spring stiffness than the isothermal process case, according to the results. The size of the air spring chamber and the area of the air spring piston influence the air spring stiffness in both situations. It is demonstrated that the stiffness of the air spring increases linearly with increasing piston area and decreases nonlinearly with increasing air chamber length. As long as the ratio of the vibration’s amplitude to the air spring’s chamber length is small, there is good agreement in both scenarios between the linearized model and the full nonlinear model. This implies that linear modeling is a reasonable approximation of the complete nonlinear model in this particular scenario.

关键词： Air Spring Dynamic Stiffness State Space Polytropic Modeling Isentropic Process Isothermal Process

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Influence of cerium ions on structure-dependent magnetic properties of Ba-Sr M-type hexaferrite nanocrystals

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Journal of Rare Earths 2024年第2期42卷 364-372,I0005页

作者： Ram A.Pawar Sunil M.Patange P.M.Dighe Sher Singh Meena abdullah GAl-Sehemi Mehboobali Pannipara Santosh S.Jadhav Department of Physics ArtsCommerce and Science CollegeAhmednagar413711MaharashtraIndia Department of Physics Shri Krishna MahavidyalayaGunjotiDistOsmanabad413606MaharashtraIndia Padmashri Vikhe Patil College of Arts Science and CommercePravaranagarA/P.Loni(Kd)Tal.RahataDistAhmednagar413713MaharashtraIndia Solid State Physics Division Bhabha Atomic Research CentreMumbai400085MaharashtraIndia Department of Chemistry King Khalid UniversityAbha61413Saudi Arabia Department of Physics D.S.M's ArtsCommerce and Science CollegeJintur431509MaharashtraIndia

The present study is a systematic effort to investigate the structure-sensitive magnetic parameters of Ce^(3+) substituted Ba-Sr hexaferrite nanocrystals chemically formulated as Ba_(0.5)Sr_(0.5)Ce_(x)Fe_(12-x)O_(19) where x=0.0-0.2 with Δx=*** hexaferrite powders were prepared using the sol-gel self-ignition route and structurally characterized by means of powder X-ray diffraction and Fourier transform infrared *** creation of the M-type hexaferrite phase within the synthesized samples was revealed from the Rietveld refinement of the X-ray *** occurrence of a secondary phase of CeO_(2) was revealed within the hexaferrites for the substitution,x> *** refined X-ray diffraction data were utilized to compute the lattice parameters,X-ray density,and lattice parameter *** crystal structure plotted from the refined XRD data reveals the occupancy of the ions at different lattice *** XPS data of the hexaferrite were analyzed to confirm the oxidation states of the constituent *** nanocrystalline nature of the hexaferrites was revealed from the crystallite sizes calculated using Scherer's *** analysis of FTIR spectra confirms that only a fraction of Ce^(3+)accommodated in the lattice and the remaining Ce content reside in the form of the CeO_(2) *** morphology of the hexaferrites was analyzed from the FESEM profiles of the ferrite *** magnetic behavior study was performed by analyzing the Curie temperature,hysteresis loops,and hyperfine interactions by means of susceptibility,V.S.M,and Mossbauer spectroscopy,*** hexaferrites with increasing coercivity,decreasing saturation magnetization,and decreasing Curie temperature are reported in the *** substituted Ce^(3+)ions inhibit the grain growth and create lattice imperfections giving rise to hexaferrites with tuned magnetic parameters suitable for different applications.

关键词： Ba-Sr hexaferrite Ce^(3+)substitution XPS Saturation magnetization Coercivity M?ssbauer spectroscopy

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Semantic Segmentation and YOLO Detector over Aerial Vehicle Images

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Computers, Materials & Continua 2024年第8期80卷 3315-3332页

作者： Asifa Mehmood Qureshi Abdul Haleem Butt Abdulwahab Alazeb Naif Al Mudawi Mohammad Alonazi Nouf abdullah Almujally Ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Cognitive Systems Lab University of BremenBremen28359Germany

Intelligent vehicle tracking and detection are crucial tasks in the realm of highway ***,vehicles come in a range of sizes,which is challenging to detect,affecting the traffic monitoring system’s overall *** learning is considered to be an efficient method for object detection in vision-based *** this paper,we proposed a vision-based vehicle detection and tracking system based on a You Look Only Once version 5(YOLOv5)detector combined with a segmentation *** model consists of six *** the first step,all the extracted traffic sequence images are subjected to pre-processing to remove noise and enhance the contrast level of the *** pre-processed images are segmented by labelling each pixel to extract the uniform regions to aid the detection phase.A single-stage detector YOLOv5 is used to detect and locate vehicles in *** detection was exposed to Speeded Up Robust Feature(SURF)feature extraction to track multiple *** on this,a unique number is assigned to each vehicle to easily locate them in the succeeding image frames by extracting them using the feature-matching ***,we implemented a Kalman filter to track multiple *** the end,the vehicle path is estimated by using the centroid points of the rectangular bounding box predicted by the tracking *** experimental results and comparison reveal that our proposed vehicle detection and tracking system outperformed other state-of-the-art *** proposed implemented system provided 94.1%detection precision for Roundabout and 96.1%detection precision for Vehicle Aerial Imaging from Drone(VAID)datasets,respectively.

关键词： Semantic segmentation YOLOv5 vehicle detection and tracking Kalman filter SURF

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Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment

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Computers, Materials & Continua 2024年第4期79卷 1157-1185页

作者： Sapiah Sakri Shakila Basheer Zuhaira Muhammad Zain Nurul Halimatul Asmak Ismail Dua’Abdellatef Nassar Manal abdullah Alohali Mais Ayman Alharaki Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia

Background:Sepsis,a potentially fatal inflammatory disease triggered by infection,carries significant healthimplications *** detection is crucial as sepsis can rapidly escalate if left *** in deep learning(DL)offer powerful tools to address this ***:Thus,this study proposeda hybrid CNNBDLSTM,a combination of a convolutional neural network(CNN)with a bi-directional long shorttermmemory(BDLSTM)model to predict sepsis *** the proposed model provides a robustframework that capitalizes on the complementary strengths of both architectures,resulting in more accurate andtimelier ***:The sepsis prediction method proposed here utilizes temporal feature extraction todelineate six distinct time frames before the onset of *** time frames adhere to the sepsis-3 standardrequirement,which incorporates 12-h observation windows preceding sepsis *** models were trained usingthe Medical Information Mart for Intensive Care III(MIMIC-III)dataset,which sourced 61,522 patients with 40clinical variables obtained from the IoT medical *** confusion matrix,the area under the receiveroperating characteristic curve(AUCROC)curve,the accuracy,the precision,the F1-score,and the recall weredeployed to evaluate ***:The CNNBDLSTMmodel demonstrated superior performance comparedto the benchmark and other models,achieving an AUCROC of 99.74%and an accuracy of 99.15%one hour beforesepsis *** results indicate that the CNNBDLSTM model is highly effective in predicting sepsis onset,particularly within a close proximity of one ***:The results could assist practitioners in increasingthe potential survival of the patient one hour before sepsis onset.

关键词： Temporal derivatives hybrid deep learning predicting sepsis onset MIMIC III machine learning(ML) deep learning

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Discoid meniscus:Treatment considerations and updates

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World Journal of Orthopedics 2024年第6期15卷 520-528页

作者： Waleed Albishi Amjad Albaroudi Abdulrahman M Alaseem Sarah Aljasser Ibrahim Alshaygy abdullah Addar Department of Orthopedic Surgery College of MedicineKing Saud UniversityRiyadh 11362Saudi Arabia

A discoid meniscus is a morphological abnormality wherein the meniscus loses its normal‘C’*** most patients are asymptomatic,patients might still present with symptoms such as locking,pain,swelling,or giving *** resonance imaging is usually needed for confirmation of *** on a constellation of factors,including clinical and radiological,different approaches are chosen for the management of discoid *** purpose of this review is to outline the treatment of discoid meniscus,starting from conservative approach,to the different surgical options for this *** PubMed and Google Scholar databases were used for this *** discussing the treatment of discoid meniscus from 2018 to 2023 were *** there were 369 studies retrieved,and after removal of studies using the exclusion criteria,26 studies were included in this *** such as stability,presence of tear,and morphology can help with surgical *** approaches have been used to treat discoid meniscus,where the choice is tailored for each patient ***,factors that may positively impact patient outcomes include male sex,body mass index<18.5,age at symptom onset<25 years,and duration of symptoms<24 *** conventional approach is partial meniscectomy with or without repair;however,recently,there has been an increased emphasis on discoid-preserving techniques such as meniscoplasty,meniscopexy,and meniscal allograft transplantation.

关键词： Discoid meniscus Saucerization Partial meniscectomy Meniscoplasty Meniscopexy Meniscal allograft transplantation Arthroscopy Knee

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Estimate the Prevalence of Helicobacter pylori Infection among Diabetes & Non-Diabetes Mellitus Patients and Its Correlation with Malignant Gastritis Patients Attending in Lower Shabelle Region (Somalia)

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Journal of Biosciences and Medicines 2024年第4期12卷 38-48页

作者： abdullah Al-Mamari Saleem Almiyah Department of Biological Sciences Faculty of Science Ibb University Ibb Yemen Faculty of Dentistry Lower Shabelle University Mogadishu Somalia

Background: Several conducted studies have reported a higher and more frequent Helicobacter pylori infection rate in type 2 diabetes mellitus (T2DM). The aim of this study was to estimation the prevalence of H. pylori and its association between H. pylori infection and T2DM. Materials and Methods: A sectional-cross study was conducted based on 200 patients studded with socioeconomic characteristics through a questionnaire & H. pylori was diagnosed by serum anti-H. pylori immunoglobulin G (IgG) and IgA. Furthermore, patients were investigated for fasting blood glucose (FBG) levels, glycosylated hemoglobin (HbA1c), serum cholesterol, and other biochemistry parameters. Results: The findings showed The prevalence of Hp positive infection was significantly higher in the total sample was 134 with (67%). While 66 out of 200 patients with (33%) was H. pylori negative infection. of H. pylori. Further, the mean values were statistically significant for diabetes with H. pylori infection for IgG > 300 titer and IgA > 250 titer, regarding, HbA1C (7.52 ± 0.41) (P Conclusions: The current study revealed that H. pylori prevalence infections were significantly higher in diabetic patients studied compared to non-diabetic patients. Furthermore, T2DM patients infected with H. pylori positive reported a higher prevalence rate of symptoms than H. pylori negative.

关键词： Diabetes Helicobacter pylori Infection Prevalence Immunoglobulin G Gastritis

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