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One-year rotational relapse frequency following conventional circumferential supracrestal fiberotomy

World Journal of Clinical Cases 2020年第2期8卷 284-293页

作者： Reham al-Jasser Thikriat al-Jewair Abdulaziz al-Rasheed Department of Periodontics and Community Dentistry College of DentistryKing Saud UniversityRiyadh 11545Saudi Arabia Graduate Program Director in Orthodontics School of Dental MedicineState University of New YorkBuffaloNY 14214United States

BACKGROUND Relapse following orthodontic treatment has been a common problem that can occur due to several factors. It was suggested that surgical circumferential supracrestal fiberotomy(CSF) is an effective measure to reduce this ***, very few studies have reported the amount of relapse that occurs *** To assess the frequency of rotational relapse on anterior teeth 1 year following *** Eleven adults(six male and five female) with a mean age of 23 years(standard deviation = 5.2), who had a total of 90 rotated anterior teeth, were included in this study. CSF was performed after comprehensive orthodontic treatment involving the use of full-fixed preadjusted edgewise appliances(Victory Series APC, 3 M,United States) with a 0.022-inch slot and Roth prescription brackets(Ovation;DENTSPLY GAC, Bohemia, New York, United States) and placement of a fixed lingual retainer from canine to canine in both arches using a 0.016 Australian wire(AJ Wilcock, Australia). Degrees of rotational correction and relapse were measured on three sets of casts [pretreatment, post-treatment(at the debond visit), and 1-year post-treatment]. Rotational relapse was categorized as follows:Unnoticeable relapse(0°), barely noticeable relapse(1°-3°), noticeable relapse(4°-9°), and clearly noticeable relapse(≥ 10°). The percent relapse that had occurred 1 year after teeth were aligned to their ideal position was calculated. Data were analyzed by dental arch type and tooth *** Mean rotational correction was 14.05° during posttreatment. Mean relapse at 1-year follow-up was 1.1°(10.8%). More than half(n = 52, 57.8%) of teeth were categorized as having unnoticeable relapse(0°). Of the remaining teeth, 31(34.5%) had barely noticeable relapse(1°-3°), 6(6.6%) had noticeable relapse(4°-9°), and only one(1.1%) had clearly noticeable relapse(> 10°). When analyzed by arch, 54.5%(n = 6) of the relapsed maxillary teeth had barely noticeable relapse(1°-3°). While most of the ma

关键词： Fiberotomy Surgery Orthodontics Adult Relapse Periodontics

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RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad al-Ahmadi Jalal al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

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Smart Mina: LoRaWAN Technology for Smart Fire Detection Application for Hajj Pilgrimage

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Computer Systems Science & Engineering 2022年第1期40卷 259-272页

作者： Mohammad al Mojamed Computer Science Department Computing College-AlqunfudahUMM Al-QURA UniversityMeccaSaudi Arabia

The Long-Range Wide Area Network(LoRaWAN)is one of the used communication systems that serve and enables the deployment of the Internet of Things(IoT),which occasionally transmit small size *** part of the Low Power Wide Area Network(LPWAN),LoRaWAN is characterized by its ability for low power *** addition,it is built to provide more extended coverage and higher capacity with minimum *** this paper,we investigate the feasibility and scalability of LoRaWAN for the Mina area using a realistic network ***,known as the world’s largest tent city,is a valley located in the east of Makkah city and surrounded by *** accommodates up to 3 million pilgrims annually and contains more than 100000 *** performance was evaluated based on a fire detection-like *** simulations were conducted using the OMNeT++simulator and Flora model to determine the delivery ratio,collision,and SF distribution for the simulated sce-nario with a network consisting of up to ten thousand end *** conducted simulations show a promising result for LoRaWAN technology for Mina *** showed a consistent performance for LoRaWAN in most simulated scenarios when a high success ratio was achieved.

关键词： LoRa LoRaWAN LPWAN IOT flora smart city Mina

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A Class of Maximal Functions with Oscillating Kernels

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Acta Mathematica Sinica,English Series 2007年第11期23卷 2003-2016页

作者： Ahmad al-SalMAN Department of Mathematics Yarmouk UniversityIrbidJordan

The author studies the L^p mapping properties of a class of maximal functions that are related to oscillatory singular integral operators. Lp estimates, as well as the corresponding weighted estimates of such maximal ... 详细信息

关键词： oscillatory singular integrals maximal functions weighted L^p bounds power weights,parametric Marcinkiewicz integral operators Morrey spaces

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Parabolic Marcinkiewicz Integrals along Surfaces on Product Domains

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Acta Mathematica Sinica,English Series 2011年第1期27卷 1-18页

作者： Ahmad al-SalMAN Department of Mathematics and Statistics Sultan Qaboos University P.O. Box 36 A1-Khod 123 Muscat Sultanate of Oman

Abstract In this paper, parabolic Marcinkiewicz integral operators along surfaces on the product domain Rn ×RM （n, m ≥2） are introduced. Lp bounds of such operators are obtained under weak conditions on the kernels.

关键词： Parabolic Marcinkiewicz integral operators parabolic maximal functions Fourier transform rough kernels

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Metaheuristic Optimization with Deep Learning Enabled Smart Grid Stability Prediction

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Computers, Materials & Continua 2023年第6期75卷 6395-6408页

作者： Afrah al-Bossly Department of Mathematics College of Science and Humanities in Al-KharjPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Due to the drastic increase in global population as well as economy,electricity demand becomes considerably *** recently developed smart grid(SG)technology has the ability to minimize power loss at the time of power *** learning(ML)and deep learning(DL)models can be effectually developed for the design of SG stability *** article introduces a new Social Spider Optimization with Deep Learning Enabled Statistical Analysis for Smart Grid Stability(SSODLSA-SGS)pre-diction ***,class imbalance data handling process is performed using Synthetic minority oversampling technique(SMOTE)*** SSODLSA-SGS model involves two stages of pre-processing namely data nor-malization and ***,the SSODLSA-SGS model derives a deep belief-back propagation neural network(DBN-BN)model for the pre-diction of SG ***,social spider optimization(SSO)algorithm can be applied for determining the optimal hyperparameter values of the DBN-BN *** design of SSO algorithm helps to appropriately modify the hyperparameter values of the DBN-BN model.A series of simulation analyses are carried out to highlight the enhanced outcomes of the SSODLSA-SGS *** extensive comparative study reported the enhanced performance of the SSODLSA-SGS algorithm over the other recent techniques interms of several measures.

关键词： Smart grids stability prediction deep learning statistical analysis social spider optimization

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Dynamical analysis and anti-synchronization of a new 6D model with self-excited attractors

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Applied Mathematics(A Journal of Chinese Universities) 2023年第1期38卷 27-43页

作者： Saad Fawzi al-Azzawi Ahmed S.al-Obeidi Department of Mathematics College of Computer Science and MathematicsUniversity of MosulMosul 41002Iraq

A novel 6D dissipative model with an unstable equilibrium point is introduced *** of the dynamic characteristics of the proposed model were explored via analyses and numerical simulations including critical points,stability,Lyapunov exponents,time phase portraits,and circuit ***,anti-synchronization phenomena were implemented on the new ***,the error dynamics is ***,four different controllers are adopted to stabilize this error relying on the nonlinear control technique with two main ways:linearization and Lyapunov stability *** comparison with previous works,the present controllers realize anti-synchronization based on another method/linearization ***,a comparison between the two ways was *** simulation results show the effectiveness and accuracy of the first analytical strategy.

关键词： 6D hyperchaotic system self-excited attractor anti-synchronization Lyapunov stability theory

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Parameter-Tuned Deep Learning-Enabled Activity Recognition for Disabled People

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Computers, Materials & Continua 2023年第6期75卷 6287-6303页

作者： Mesfer al Duhayyim Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversityAl-Aflaj16273Saudi Arabia

Elderly or disabled people can be supported by a human activity recognition(HAR)system that monitors their activity intervenes and pat-terns in case of changes in their behaviors or critical events have *** automated HAR could assist these persons to have a more indepen-dent *** appropriate and accurate data regarding the activity is the most crucial computation task in the activity recognition *** the fast development of neural networks,computing,and machine learning algorithms,HAR system based on wearable sensors has gained popularity in several areas,such as medical services,smart homes,improving human communication with computers,security systems,healthcare for the elderly,mechanization in industry,robot monitoring system,monitoring athlete train-ing,and rehabilitation *** this view,this study develops an improved pelican optimization with deep transfer learning enabled HAR(IPODTL-HAR)system for disabled *** major goal of the IPODTL-HAR method was recognizing the human activities for disabled person and improve the quality of *** presented IPODTL-HAR model follows data pre-processing for improvising the quality of the ***,EfficientNet model is applied to derive a useful set of feature vectors and the hyperparameters are adjusted by the use of Nadam ***,the IPO with deep belief network(DBN)model is utilized for the recognition and classification of human *** utilization of Nadam optimizer and IPO algorithm helps in effectually tuning the hyperparameters related to the EfficientNet and DBN models *** experimental validation of the IPODTL-HAR method is tested using benchmark *** comparison study highlighted the betterment of the IPODTL-HAR model over recent state of art HAR approaches interms of different measures.

关键词： Human activity recognition disabled person artificial intelligence computer vision deep learning

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Experimental investigation of the effects of various parameters on viscosity reduction of heavy crude by oil-water emulsion

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Petroleum Science 2015年第1期12卷 170-176页

作者： Talal al-Wahaibi Yahya al-Wahaibi Abdul-Aziz R.al-Hashmi Farouq S.Mjalli Safiya al-Hatmi Petroleum & Chemical Engineering Department College of Engineering Sultan Qaboos University

The effects of water content, shear rate, temperature, and solid particle concentration on viscosity reduction （VR） caused by forming stable emulsions were investigated using Omani heavy crude oil. The viscosity of the crude oil was initially measured with respect to shear rates at different temperatures from 20 to 70℃. The crude oil exhibited a shear thinning behavior at all the temperatures. The strongest shear thinning was observed at 20℃. A non-ionic water soluble surfactant （Triton X-100） was used to form and stabilize crude oil emulsions. The emulsification process has significantly reduced the crude oil viscosity. The degree of VR was found to increase with an increase in water content and reach its maximum value at 50 % water content. The phase inversion from oil- oil emulsion occurred at 30 in-water emulsion to water-in- % water content. The results indicated that the VR was inversely proportional to temperature and concentration of silica nanoparticles. For water-in-oil emulsions, VR increased with shear rate and eventually reached a plateau at a shear rate of around 350 s^-1. This was attributed to the thinning behavior of the continuous phase. The VR of oil-in-water emulsions remained almost constant as the shear rate increased due to the Newtonian behavior of water, the continuous phase.

关键词： Viscosity reduction Phase inversion Non-newtonian fluid Oil-in-water emulsions Heavy crude oil

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Daily number of bee louse （Braula coeca） in honey bee （Apis mellifera carnica and A. m. syriaca） colonies maintained under semi-arid conditions

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Insect Science 2008年第6期15卷 563-567页

作者： Shahera Zaitoun Abd al-Majeed al-Ghzawi Department of Plant Production and Protection Faculty of Agricultural Technology AI-Balqa' Applied University Al-Salt Department of Plant Production Faculty of Agriculture Jordan University of Science and Technology Irbid 22110 Jordan

Experimental work was conducted at two apiaries located in Irbid district and in Shuna North, Jordan, during the years 2004-2006. The aims of these investigations were to estimate the seasonal changes in the infestation rates of the bee louse （Braula sp.） and to develop an easy and rapid method of estimating the infestation rate on workers with bee Braula. Two major honey bee subspecies are reared in Jordan; Apis mellifera carnica and Apis mellifera syriaca were used in this study. The results showed that the infestation rate began to increase rapidly in May, reaching the season＇s maximum rate of 16.2%, 15.8% and 17.4% forA. m. carnica and 22.6%, 23.9% and 22.9% forA. m. syriaca in December of 2004, 2005 and 2006, respectively. The maximum adult numbers of bees were found in April and June, whereas the minimum for the year was in January in both honey bee subspecies colonies during the study period. The actual population of the bee louse could be estimated by counting the daily dropped lice and multiplying by a factor of 158. This factor is valid for the experimental colonies of both subspecies kept for 3 years under semi-arid Mediterranean conditions.

关键词： Apis mellifera carnica Apis mellifera syriaca Braula honeybee Jordan

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