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Forest composition and red oak (Quercus sp.) response to elevation gradients across greentree reservoirs

Forest Ecosystems 2023年第5期10卷 607-617页

作者： Cassandra Hug Pradip saud Keith McKnight Douglas C.Osborne College of Forestry Agriculturaland Natural ResourcesUniversity of Arkansas at MonticelloMonticelloAR71656USA USFWS/Lower Mississippi Valley Joint Venture TylerTX75707USA Five Oaks Ag Research and Education Center HumphreyAR72073USA

Elevation gradients within forested wetlands have long been recognized for their role in defining species composition through factors such as hydrology and soil *** reservoirs(GTRs)are leveeimpounded tracts of bottomland hardwood forest flooded throughout the winter months to provide habitat for overwintering *** flooding of GTRs alters the forest composition due to flood frequency,depth,and duration in combination with slight changes in *** evaluate the effect of elevation gradients,soil properties,and management techniques in the overstory species composition and red oak(Quercus spp.)species abundance,we inventoried 662 plots across 12 independent GTRs in eastern *** the lower elevations ranging from 50.98 to 54.99 m above sea level,the importance value index(IVI)was highest for nuttall oak(Quercus texana)and overcup oak(Quercus lyrata),whereas IVI shifted to cherrybark oak(Quercus pagoda)in the higher elevations ranging from 54.99 to 58.00 *** diversity did not differ by elevation gradient,soil property,or management technique within *** diversity,using non-metric multi-dimensional scaling(NMDS)analysis,indicated site-specific variability significantly correlated with the environmental predictors,including elevation(R^(2)=0.57),easting(R^(2)=0.47),soil texture(R^(2)=0.21),and pH(R^(2)=0.12).Red oak species-specific mixed-effects modeling of abundance response using Poisson distribution suggested an inverse correlation of nuttall oak and a direct correlation of cherrybark oak abundance with ***,willow oak(Quercus phellos)abundance was not significantly affected by elevation but was by silt loam soil texture and restoration management *** findings will aid management efforts to reduce the dominance of less desirable species that are prominent under specific environmental conditions and promote the dominance of more desirable *** GTR sustainability is increas

关键词： Bottomland hardwoods Diversity Forested wetland Overstory Red oak Soil Thinning and management

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Applicability of deep neural networks for lithofacies classification from conventional well logs: An integrated approach

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Petroleum Research 2024年第3期9卷 393-408页

作者： saud Qadir Khan Farzain Ud Din Kirmani Mari Petroleum Company Limited IslamabadPakistan Department of Petroleum and Gas Enginering NFC.Institute of Engineering&Technology MultanPakistan

Parametric understanding for specifying formation characteristics can be perceived through conven-tional ***,attributes of reservoir lithology are practiced for hydrocarbon *** logging is conventional approach which is applicable to predict lithology efficiently as compared to geophysical modeling and petrophysical analysis due to cost effectiveness and suitable interpretation ***,manual interpretation of lithology identification through well logging data requires domain expertise with an extended length of time for ***,in this study,Deep Neural Network(DNN)has been deployed to automate the lithology identification process from well logging data which would provide support by increasing time-effective for monitoring *** model has been developed for predicting formation lithology leading to the optimization of the model through the thorough evaluation of the best parameters and hyperparameters including the number of neurons,number of layers,optimizer,learning rate,dropout values,and activation *** of the model is examined by utilizing different evaluation metrics through the division of the dataset into the subdomains of training,validation and ***,an attempt is contributed to remove interception for formation lithology prediction while addressing the imbalanced nature of the associated dataset as well in the training process using class *** is assessed that accuracy is not a true and only reliable metric to evaluate the lithology classification *** model with class weight recognizes all the classes but has low accuracy as well as a low F1-score while LSTM based model has high accuracyas well as a high F1-score.

关键词： Lithology identification Deep learning LSTM Imbalanced dataset Conventional well logs

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A Hybrid Particle Swarm Optimization to Forecast Implied Volatility Risk

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Computers, Materials & Continua 2022年第11期73卷 4291-4309页

作者： Kais Tissaoui Sahbi Boubaker Waleed saud Alghassab Taha Zaghdoudi Jamel Azibi University of Ha’il Applied CollegeHail CitySaudi Arabia University of Tunis El Manar Faculty of Economic Sciences and Management of Tunisthe International Finance GroupTunisTunisia Department of Computer and Network Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21959Saudi Arabia Research Unit on Study of Systems and Renewable Energy National College of Engineering of MonastirUniversity of MonastirMonastirTunisia LAREQUAD&FSEGT University of Tunis El ManarTunisTunisia University of Jendouba Law FacultyManagement and Economic Sciences of JendoubaTunisia

The application of optimization methods to prediction issues is a continually exploring *** line with this,this paper investigates the connectedness between the infected cases of COVID-19 and US fear index from a forecasting *** complex characteristics of implied volatility risk index such as non-linearity structure,time-varying and nonstationarity motivate us to apply a nonlinear polynomial Hammerstein model with known structure and unknown *** use the Hybrid Particle Swarm Optimization(HPSO)tool to identify the model parameters of nonlinear polynomial Hammerstein *** indicate that,following a nonlinear polynomial behaviour cascaded to an autoregressive with exogenous input(ARX)behaviour,the fear index in US financial market is significantly affected by COVID-19-infected cases in the US,COVID-19-infected cases in the world and COVID-19-infected cases in China,*** performance indicators provided by the developed models show that COVID-19-infected cases in the US are particularly powerful in predicting the Cboe volatility index compared to COVID-19-infected cases in the world and China(MAPE(2.1013%);R2(91.78%)and RMSE(0.6363 percentage points)).The proposed approaches have also shown good convergence characteristics and accurate fits of the data.

关键词： Forecasting Cboe’s volatility index COVID-19 pandemic nonlinear polynomial hammerstein model hybrid particle swarm optimization

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Cyberbullying Detection and Recognition with Type Determination Based on Machine Learning

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Computers, Materials & Continua 2023年第6期75卷 5307-5319页

作者： Khalid M.O.Nahar Mohammad Alauthman saud Yonbawi Ammar Almomani Computer Science Department Yarmouk UniversityIrbidJordan Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan Software Engineering Department University of JeddahJeddahKSA Research and Innovation Department Skyline University CollegeP.O.Box 1797SharjahUAE IT Department-Al-Huson University College Al-Balqa Applied UniversityP.O.Box 50IrbidJordan

Social media networks are becoming essential to our daily activities,and many issues are due to this great involvement in our *** is a social media network issue,a global crisis affecting the victims and society as a *** results from a misunderstanding regarding freedom of *** this work,we proposed a methodology for detecting such behaviors(bullying,harassment,and hate-related texts)using supervised machine learning algo-rithms(SVM,Naïve Bayes,Logistic regression,and random forest)and for predicting a topic associated with these text data using unsupervised natural language processing,such as latent Dirichlet *** addition,we used accuracy,precision,recall,and F1 score to assess prior *** show that the use of logistic regression,support vector machine,random forest model,and Naïve Bayes has 95%,94.97%,94.66%,and 93.1%accuracy,respectively.

关键词： Cyberbullying social media naïve bayes support vector machine natural language processing LDA

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A Deep Learning Based Sentiment Analytic Model for the Prediction of Traffic Accidents

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Computers, Materials & Continua 2023年第11期77卷 1599-1615页

作者： Nadeem Malik saud Altaf Muhammad Usman Tariq Ashir Ahmed Muhammad Babar University Institute of Information Technology PMAS Arid Agriculture UniversityRawalpindi46000Pakistan Department of Marketing Operationsand Information SystemAbu Dhabi UniversityAbu Dhabi6844United Arab Emirates College of Computer and Information Sciences Prince Sultan UniversityRiyadh11442Saudi Arabia Robotics and Internet of Things Lab Prince Sultan UniversityRiyadh11442Saudi Arabia

The severity of traffic accidents is a serious global concern,particularly in developing *** the main causes and contributing circumstances may reduce the severity of traffic *** exist many machine learning models and decision support systems to predict road accidents by using datasets from different social media forums such as Twitter,blogs and *** such approaches are popular,there exists an issue of data management and low prediction *** article presented a deep learning-based sentiment analytic model known as Extra-large Network Bi-directional long short term memory(XLNet-Bi-LSTM)to predict traffic collisions based on data collected from social ***,a Tweet dataset has been formed by using an exhaustive keyword-based searching *** the next phase,two different types of features named as individual tokens and pair tokens have been obtained by using POS tagging and association rule *** output of this phase has been forwarded to a three-layer deep learning model for final *** experiment has been performed to test the efficiency of the proposed XLNet-Bi-LSTM *** has been shown that the proposed model achieved 94.2%prediction accuracy.

关键词： Accident XLNet Bi-LSTM association rule mining Twitter

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An updated review on pharmacological activities and phytochemical constituents of evening primrose(genus Oenothera)

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Asian Pacific Journal of Tropical Biomedicine 2017年第11期7卷 1046-1054页

作者： Rebecca Munir Nabil Semmar Muhammad Farman Naseem saud Ahmad Department of Pharmacology University of Health SciencesLahore Pakistan Laboratory of Bioinformatics Biomathematics and Biostatistics Pasteur Institute of Tunis University of Tunis El Manar

Genus Oenothera includes medicinal plants that are distributed throughout the world and are known since ancient times. Popular indications of different species of this genus include treatment of inflammations, diabetes, microbial infections, ulcers, tumors, kidney and liver problems. The plants of this genus are a botanical source for various pharmaceutically active components like sterols, alkaloids, phenolic acids, flavonoids, triterpenoids, saponins, biflavonols and tocopherols. This review article is a compilation of chemical composition and biological activities of the various species of the genus Oenothera.

关键词： Oenothera Medicinal plants Chemical composition Biological activities

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Detection of oxidative stress and DNA damage in freshwater snail Lymnea leuteola exposed to profenofos

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Frontiers of Environmental Science & Engineering 2018年第5期12卷 181-187页

作者： Daoud Ali Huma Ali saud Alifiri Saad Alkahtani Abdullah A Alkahtane Shaik Althaf Huasain Department of Zoology College of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia 2 Department of ChemistryMANITBhopal 462003India

Extensive production and use of organophosphate pesticide in agriculture,has risen concerned about its ecotoxicity and risk assessment of insecticides,which are more ***,the present investigation was aimed to study the induction of oxidative stress and DNA damage by organophosphate insecticide profenofos(PFF)in freshwater snail Lymnea luteola(***).The median lethal value(96 h LC50)of PFF was estimated as 1.26 mg/L for *** in a semi-static system and on the basis of LC50 value three concentrations viz.,0.126(1/10 of LC50,Sublethal I),0.63(1/2 of LC50,Sublethal II)and 0.84 mg/L(2/3 of LC50,Sublethal III)were *** were exposed to above-mentioned concentrations of PFF along with solvent control(acetone)and negative control for 96 *** haemolymph was collected at 24 and 96 h of after *** heamolymph of PFF exposed snail,lipid peroxide,glutathione reduced glutathione S transferase and superoxide dismutase activities at the tested concentrations significantly differ from those in the *** genotoxicity induced in hemocytes of treated snails was measured by alkaline single cell gel electrophoresis *** data of this experiment demonstrated significantly enhancement of oxidative stress and DNA damage in the treated snails as compared to ***,we observed statistically significant correlations of ROS with DNA damage(%tail DNA)(R^(2)=0.9708)for 24 h and DNA damage(R^(2)=0.9665)for 96 *** of the current experiment can be useful in risk evaluation of PFF among aquatic *** study confirmed the use of comet assay for in vivo laboratory experiments using freshwater snail for selecting the toxic potential of industrial chemicals and environmental contaminants.

关键词： Acute toxicity Profenofos ROS oxidative stress DNA damage Lymnea luteola

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Evaluation of visual stress symptoms in age-matched dyslexic, Meares-Irlen syndrome and normal adults

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International Journal of Ophthalmology(English edition) 2016年第4期9卷 617-624页

作者： Mana A.Alanazi saud A.Alanazi Uchechukwu L.Osuagwu Department of Optometry & Vision Science King Saud University Ophthalmic and Visual Optics Laboratory Group Institute of Health and Biomedical Innovation Department of Optometry & Vision Sciences Faculty of Health Queensland University of Technology

AIM： To examine the prevalence of dyslexia and Meares-Irlen syndrome（MIS） among female students and determine their level of visual stress in comparison with normal subjects.·METHODS： A random sample of 450 female medical students of King saud University Riyadh（age range, 18-30y） responded to a wide range of questions designed to accomplish the aims of this study. The detailed questionnaire consisted of 54 questions with 12 questions enquiring on ocular history and demography of participants while 42 questions were on visual symptoms. Items were categorized into critical and non-critical questions（CQ and NCQ） and were rated on four point Likert scale. Based on the responses obtained, the subjects were grouped into normal（control）, dyslexic with or without MIS（Group 1） and subjects with MIS only（Group 2）. Responses were analysed as averages and mean scores were calculated and compared between groups using one way analysis of variance to evaluate total visual stress score（TVSS =NCQ ＋CQ）, critical and non-critical visual stress scores. The relationship between categorical variables such as age, handedness and condition were assessed with Chi-square test.·RESULTS： The completion rate was 97.6% and majority of the respondents（92%） were normal readers, 2%dyslexic and 6% had MIS. They were age-matched. More than half of the participants had visited an eye care practitioner in the last 2y. About 13% were recommendedeye exercises and one participant experienced pattern glare. Hand preference was not associated with any condition but Group 1 subjects（3/9, 33%） were significantly more likely to be diagnosed of lazy eye than Group 2（2/27, 7%） and control（27/414, 7%） subjects. The mean±SD of TVSS responses were 63±14 and it was 44±9for CQ and 19 ±5 for NCQ. Responses from all three variables were normally distributed but the CQ responses were on the average more positive（82%） in Group 2 and less positive（46%） in Group 1 than control. With NCQ,the responses were equally less posi

关键词： dyslexia visual stress symptoms critical questions non-critical questions Meares-Irlen syndrome questionnaire

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Efficient Object Segmentation and Recognition Using Multi-Layer Perceptron Networks

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Computers, Materials & Continua 2024年第1期78卷 1381-1398页

作者： Aysha Naseer Nouf Abdullah Almujally saud S.Alotaibi Abdulwahab Alazeb Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Information System Department Umm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Object segmentation and recognition is an imperative area of computer vision andmachine learning that identifies and separates individual objects within an image or video and determines classes or categories based on their *** proposed system presents a distinctive approach to object segmentation and recognition using Artificial Neural Networks(ANNs).The system takes RGB images as input and uses a k-means clustering-based segmentation technique to fragment the intended parts of the images into different regions and label thembased on their ***,two distinct kinds of features are obtained from the segmented images to help identify the objects of *** Artificial Neural Network(ANN)is then used to recognize the objects based on their *** were carried out with three standard datasets,MSRC,MS COCO,and Caltech 101 which are extensively used in object recognition research,to measure the productivity of the suggested *** findings from the experiment support the suggested system’s validity,as it achieved class recognition accuracies of 89%,83%,and 90.30% on the MSRC,MS COCO,and Caltech 101 datasets,respectively.

关键词： K-region fusion segmentation recognition feature extraction artificial neural network computer vision

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New Optical Soliton Solutions of Nolinear Evolution Equation Describing Nonlinear Dispersion

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Communications in Theoretical Physics 2019年第9期71卷 1063-1068页

作者： saud Owyed M.A.Abdou Abdel-Haleem Abdel-Aty S.Saha Ray Department of Mathematics College of SciencesUniversity of BishaBisha61922P.O.Box344Saudi Arabia Department of Physics College of SciencesUniversity of BishaBisha61922P.O.Box344Saudi Arabia Physics Department Faculty of SciencesAl-Azhar University71524AssiutEgypt Department of Mathematics National Institute of TechnologyRourkela769008OdishaIndia

In this work, we examine two algorithm schemes, namely, Kudryashov expansion and Auxiliary equation method for obtaining new optical soliton solutions of the discrete electrical lattice models in nonlinear scheme(Salerno equation). Our solutions obtained here are include the hyperbolic, rational, and trigonometric functions. Our two used methods are proved to be effective and powerful methods in obtaining the exact solutions of nonlinear evolution equations(NLEEs).

关键词： discrete electrical lattice generalized Kudryashov expansion method auxiliary equation method exact solutions

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