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Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

Computers, Materials & Continua 2022年第8期72卷 3719-3749页

作者： Mousa Al-Akhras Zainab Darwish Samer Atawneh mohamed habib College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia King Abdullah II School for Information Technology The University of JordanAmman11942Jordan Faculty of Engineering Port Said UniversityPort Said42523Egypt

Association rules’learning is a machine learning method used in finding underlying associations in large datasets.Whether intentionally or unintentionally present,noise in training instances causes overfitting while building the classifier and negatively impacts classification accuracy.This paper uses instance reduction techniques for the datasets before mining the association rules and building the classifier.Instance reduction techniques were originally developed to reduce memory requirements in instance-based learning.This paper utilizes them to remove noise from the dataset before training the association rules classifier.Extensive experiments were conducted to assess the accuracy of association rules with different instance reduction techniques,namely:DecrementalReduction Optimization Procedure(DROP)3,DROP5,ALL K-Nearest Neighbors(ALLKNN),Edited Nearest Neighbor(ENN),and Repeated Edited Nearest Neighbor(RENN)in different noise ratios.Experiments show that instance reduction techniques substantially improved the average classification accuracy on three different noise levels:0%,5%,and 10%.The RENN algorithm achieved the highest levels of accuracy with a significant improvement on seven out of eight used datasets from the University of California Irvine(UCI)machine learning repository.The improvements were more apparent in the 5%and the 10%noise cases.When RENN was applied,the average classification accuracy for the eight datasets in the zero-noise test enhanced from 70.47%to 76.65%compared to the original test.The average accuracy was improved from 66.08%to 77.47%for the 5%-noise case and from 59.89%to 77.59%in the 10%-noise case.Higher confidence was also reported in building the association rules when RENN was used.The above results indicate that RENN is a good solution in removing noise and avoiding overfitting during the construction of the association rules classifier,especially in noisy domains.

关键词： Association rules classification instance reduction techniques classification overfitting noise data cleansing

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Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

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Computers, Materials & Continua 2022年第2期70卷 2761-2775页

作者： Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Muhammad Attique mohamed habib Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Faculty of Engineering Port Said UniversityPort Fuad CityEgypt

In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting firearms.which is why an automated weapon detection system is needed.Various automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good results.However,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection system.These models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance videos.This research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key parameter.The proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur algorithm.The proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 score.The results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are achieved.Speed reached 0.010 s per frame compared to the 0.17 s of the Faster R-CNN.It is promising to be used in the field of security and weapon detection.

关键词： Video surveillance weapon detection you only look once convolutional neural networks

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Cervical Meningocele about 2 Operated Cases

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Open Journal of Modern Neurosurgery 2024年第1期14卷 1-7页

作者： mohamed El Hassimi Cissé Mamadou Salia Diarra N’Famara Sylla Abdoulaye Diop Izoudine Blaise Koumaré Théodore habib Maxime Coulibaly Oumar Diallo Drissa Kanikomo Neurosurgery Department of CHU Mère-Enfant “Le Luxembourg” Bamako Mali Neurosurgery Unit of Army Medico-Surgical Center of Bamako Bamako Mali Neurosurgery Department of CHNU de Fann Dakar Sénégal Neurosurgery Department of CHU Hospital du Mali Bamako Mali Neurosurgery Department of CHU Gabriel Touré Bamako Mali

Cervical meningoceles are the least common forms of spina bifida, representing between 4% to 8% of all spinal dysraphisms. They are not accompanied by neurological deficit in childhood but attached cord syndrome can occur with growth. Surgical treatment, in addition to avoiding rupture and correcting the aesthetic damage, will preserve neurological functions. We report 2 cases that we took care of. They are a 5-month-old infant and a 3-year-old girl. The first presented a 7 cm rounded meningocele pedunculated through the C1 lamina defect. The second presented an 8.6 cm polylobed meningocele pedunculated through the C2 lamina defect. They both underwent surgery with good progress.

关键词： Cervical Meningocele Spinal Dysraphism Spina Bifida

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Robotics in total knee replacement:Current use and future implications

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World Journal of Orthopedics 2024年第6期15卷 489-494页

作者： Majd M Alrayes mohamed Sukeik Department of Trauma and Orthopedics Orthopedic Surgery DepartmentKing Faisal Specialist Hospital and Research CenterRiyadh 11564Saudi Arabia Department of Trauma and Orthopaedics Dr.Sulaiman Al-Habib HospitalKhobar 34423Saudi Arabia

Robotic total knee replacement(TKR)surgery has evolved over the years with the aim of improving the overall 80% satisfaction rate associated with TKR surgery.Proponents claim higher precision in executing the pre-operative plan which results in improved alignment and possibly better clinical outcomes.Opponents suggest longer operative times with potentially higher complications and no superiority in clinical outcomes alongside increased costs.This editorial will summarize where we currently stand and the future implications of using robotics in knee replacement surgery.

关键词： Total knee replacement Robotic Conventional Radiological assessment Financial burden Clinical outcomes

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Enhancing Patient Safety in the Operating Room: A Comprehensive Guide from a Nurse’s Perspective

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Open Journal of Nursing 2024年第6期14卷 252-266页

作者： Aisha mohamed Hussein Operating Room Nurse Dr. Sulaiman Al-Habib Medical Group Bone Joint and Spine Hospital Riyadh Saudi Arabia

Ensuring patient safety within the operating room is a paramount concern in contemporary healthcare, and this guide aims to provide an in-depth exploration of this crucial aspect from the perspective of nurses. Nurses play a pivotal role in supporting surgeons and maintaining a safe environment for patients undergoing various medical procedures.

关键词： Operating Room Patient Safety Nurses

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Salivary C-reactive protein and mean platelet volume as possible diagnostic markers for late-onset neonatal pneumonia

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World Journal of Clinical Pediatrics 2024年第1期13卷 41-51页

作者： Wafaa Ahmed Metwali Abdelrahman mohamed Elmashad Sahar Mohey Eldin Hazzaa Mohammed Al-Beltagi mohamed Basiony Hamza Department of Pediatric Faculty of MedicineTanta UniversityTanta 31511AlgahrbiaEgypt Department of Clinical Pathology Faculty of MedicineTanta UniversityTanta 31511AlgahrbiaEgypt Department of Pediatric University Medical CenterDr.Suliaman Al Habib Medical GroupManama 26671ManamaBahrain Department of Pediatric University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityManama 26671ManamaBahrain

BACKGROUND Neonatal sepsis,a formidable threat to newborns,is a leading cause of neonatal mortality,with late-onset sepsis manifesting after 72 hours post-birth being particularly concerning.Pneumonia,a prevalent sepsis presentation,poses a significant risk,especially during the neonatal phase when lung defenses are compromised.Accurate diagnosis of pneumonia is imperative for timely and effective interventions.Saliva,a minimally invasive diagnostic medium,holds great promise for evaluating infections,especially in infants.AIM To investigate the potential of serum C-reactive protein(CRP),salivary CRP(sCRP),and mean platelet volume(MPV)as diagnostic markers for late-onset neonatal pneumonia(LONP).METHODS Eighty full-term neonates were systematically examined,considering anthropometric measurements,clinical manifestations,radiology findings,and essential biomarkers,including serum CRP,sCRP,and MPV.RESULTS The study reveals noteworthy distinctions in serum CRP levels,MPV,and the serum CRP/MPV ratio between neonates with LONP and healthy controls.MPV exhibited a robust discriminatory ability[area under the curve(AUC)=0.87]with high sensitivity and specificity at a cutoff value of>8.8.Correlations between serum CRP,sCRP,and MPV were also identified.Notably,sCRP demonstrated excellent predictive value for serum CRP levels(AUC=0.89),underscoring its potential as a diagnostic tool.CONCLUSION This study underscores the diagnostic promise of salivary and serum biomarkers,specifically MPV and CRP,in identifying and predicting LONP among neonates.These findings advocate for further research to validate their clinical utility in larger neonatal cohorts.

关键词： Neonatal sepsis Late-onset pneumonia Salivary C-reactive protein Mean platelet volume Diagnostic markers Newborn infections

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Modeling CO_(2)Emission in Residential Sector of Three Countries in Southeast of Asia by Applying Intelligent Techniques

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Computers, Materials & Continua 2023年第3期74卷 5679-5690页

作者： Mohsen Sharifpur mohamed Salem Yonis M Buswig habib Forootan Fard Jaroon Rungamornrat Clean Energy Research Group Department of Mechanical and Aeronautical EngineeringEngineering IIIUniversity of PretoriaPretoriaSouth Africa Department of Medical Research China Medical University HospitalChina Medical UniversityTaichungTaiwanChina School of Electrical and Electronic Engineering Universiti Sains Malaysia(USM)Nibong Tebal14300PenangMalaysia Institute of Sustainable and Renewable Energy ISuRE Faculty of EngineeringUniversityMalaysia Sarawak Department of Renewable Energies Faculty of New Sciences and TechnologiesUniversity of TehranTehranIran Center of Excellence in Applied Mechanics and Structures Department of Civil EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok10330Thailand

Residential sector is one of the energy-consuming districts of countries that causes CO_(2)emission in large extent.In this regard,this sector must be considered in energy policy making related to the reduction of emission of CO_(2)and other greenhouse gases.In the present work,CO_(2)emission related to the residential sector of three countries,including Indonesia,Thailand,and Vietnam in Southeast Asia,are discussed and modeled by employing Group Method of Data Handling(GMDH)and Multilayer Perceptron(MLP)neural networks as powerful intelligent methods.Prior to modeling,data related to the energy consumption of these countries are represented,discussed,and analyzed.Subsequently,to propose a model,electricity,natural gas,coal,and oil products consumptions are applied as inputs,and CO_(2)emission is considered as the model’s output.The obtained R^(2) values for the generated models based on MLP and GMDH are 0.9987 and 0.9985,respectively.Furthermore,values of the Average Absolute Relative Deviation(AARD)of the regressions using the mentioned techniques are around 4.56%and 5.53%,respectively.These values reveal significant exactness of the models proposed in this article;however,making use of MLP with the optimal architecture would lead to higher accuracy.

关键词： CO_(2)emission GMDH MLP intelligent techniques energy consumption

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Gastrointestinal tolerability of organic infant formula compared to traditional infant formula: A systematic review

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World Journal of Clinical Pediatrics 2024年第1期13卷 125-140页

作者： Mohammed Al-Beltagi Nermin Kamal Saeed Adel Salah Bediwy Reem Elbeltagi mohamed Basiony Hamza Department of Pediatric Faculty of MedicineTanta UniversityTanta 31511AlghrabiaEgypt Department of Pediatric University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityDr.Sulaiman Al Habib Medical GroupManama 26671ManamaBahrain Medical Microbiology Section Department of PathologySalmaniya Medical ComplexMinistry of HealthKingdom of BahrainManama 12ManamaBahrain Medical Microbiology Section Department of PathologyIrish Royal College of SurgeonBusaiteen 15503MuharraqBahrain Department of Pulmonology Faculty of MedicineTanta UniversityTanta 31527AlghrabiaEgypt Department of Pulmonology University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityDr.Sulaiman Al Habib Medical GroupManama 26671ManamaBahrain Department of Medicine The Royal College of Surgeons in Ireland-BahrainBusiateen 15503MuharraqBahrain Department of Pediatric Faculty of MedicineTanta UniversityTanta 31511AlgahrbiaEgypt

BACKGROUND Infants'nutrition significantly influences their growth,development,and overall well-being.With the increasing demand for organic infant formula driven by the perception of health benefits and growing awareness of natural feeding options,it is crucial to conduct a comparative analysis of the gastrointestinal tolerability between organic and traditional infant formulas.AIM To provide a concise and precise analysis of the gastrointestinal tolerability of organic infant formula compared to traditional infant formula.Due to limited direct comparisons,the review synthesizes available literature on each formula type,presenting insights into their potential effects on infants'digestive health.METHODS An extensive literature search was conducted,compiling studies on organic and traditional infant formulas,their compositions,and reported effects on gastrointestinal tolerability.We searched academic databases such as PubMed and Google Scholar and specialized nutrition,paediatrics,and infant health journals using relevant keywords till October 1,2023.RESULTS Although specific comparative studies are scarce and formula heterogeneity is a significant limitation,this systematic review provides an in-depth understanding of organic infant formulas'composition and potential benefits.While scientific evidence directly comparing gastrointestinal tolerability is limited,organic formulas strive to use carefully selected organic ingredients to imitate breast milk composition.Potential benefits include improved lipid profiles,higher methionine content,and decreased antibiotic-resistant bacteria levels.Understanding the gastrointestinal tolerability of organic and traditional infant formulas is crucial for parents and healthcare providers to make informed decisions.CONCLUSION Despite limitations in direct comparisons,this systematic review provides insights into the composition and potential benefits of organic infant formulas.It emphasizes the need for further research to elucidate their gastrointestinal effects comprehensiv

关键词： Organic infant formula Traditional infant formula Gastrointestinal tolerability Formula ingredients Digestive health Infant nutrition Organic farming

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SCALAR CURVATURE TYPE PROBLEM ON THE THREE DIMENSIONAL BOUNDED DOMAIN

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Acta Mathematica Scientia 2017年第1期37卷 139-173页

作者： mohamed BEN AYED habib FOURTI Faculte des Sciences Universite de SfaxRoute SoukraSfaxTunisie Institut Preparatoire Aux Etudes d'Ingenieurs Universite de SfaxSfaxTunisie

In this paper we prove an existence result for the nonlinear elliptic problem：-△u = Ku5,u 〉 0 in Ω,u = 0 on Ω,where Ω is a smooth bounded domain of R3 and K is a positive function in Ω.Our method relies on stud... 详细信息

关键词： scalar-curvature critical point limiting Sobolev exponent variational prob-lems with lack of compactness blow up analysis

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An Advanced FMRL Controller for FACTS Devices to Enhance Dynamic Performance of Power Systems

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International Journal of Automation and computing 2011年第3期8卷 309-316页

作者： Abdellatif Naceri habib Hamdaoui mohamed Abid IRECOM Laboratory Department of Electrical Engineering Djillali Liabes University of Sidi Bel-Abbes ICEPS Laboratory Department of Electrical Engineering Djillali Liabes University of Sidi Bel-Abbes

The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It is preferable that the control technique in this system possesses robustness for various fault conditions and disturbances. The used flexible alternating current transmission system （FACTS） in this paper is an advanced super-conducting magnetic energy storage （ASMES）. Many control techniques that use ASMES to improve power system stability have been proposed. While fuzzy controller has proven its value in some applications, the researches applying fuzzy controller with ASMES have been actively reported. However, it is sometimes very difficult to specify the rule base for some plants, when the parameters change. To solve this problem, a fuzzy model reference learning controller （FMRLC） is proposed in this paper, which investigates multi-input multi-output FMRLC for time-variant nonlinear system. This control method provides the motivation for adaptive fuzzy control, where the focus is on the automatic online synthesis and tuning of fuzzy controller parameters （i.e., using online data to continually learn the fuzzy controller that will ensure that the performance objectives are met）. Simulation results show that the proposed robust controller is able to work with nonlinear and nonstationary power system （i.e., single machine-infinite bus （SMIB） system）, under various fault conditions and disturbances.

关键词： Transient power system stability and robustness single machine-infinite bus （SMIB） system flexible alternating currenttransmission system （FACTS） advanced super-conducting magnetic energy storage （ASMES） fuzzy model reference learning controller（FMRLC） adaptive control learning controller.

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