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A new technique for fault diagnosis in transformer insulating oil based on infrared spectroscopy measurements

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High Voltage 2024年第2期9卷 319-335页

作者： Mohamed M.F.darwish Mohamed H.A.Hassan Nagat M.K.Abdel-Gawad Matti Lehtonen Diaa-Eldin A.Mansour Department of Electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Electrical Engineering and Automation School of Electrical EngineeringAalto UniversityEspooFinland Department of Electrical Power Engineering Egypt-Japan University of Science and Technology(E-JUST)New Borg El-Arab CityEgypt Department of Electrical Power and Machines Engineering Faculty of EngineeringTanta UniversityTantaEgypt

Condition monitoring of the insulating system within power transformers has a massive importance according to the electrical utilities.Dissolved gas analysis(DGA)is frequently used for this purpose.However,DGA lacks the necessary level of accuracy to identify all equipment faults,particularly in their initial stages of degradation.Also,it does not have the capability for real-time monitoring and relies on manual sampling and laboratory testing,causing potential delays in fault identification.Additionally,the interpretation of DGA data necessitates specialised expertise,which may pose difficulties for smaller entities that have limited access to resources.Therefore,the contribution of this research is to use infrared spectroscopy measurements as a new effective technique substituting the DGA method for fault diagnosis in insulating oil.The inception faults that were considered in this study were the electrical fault(discharges of high energy)and the thermal fault(300°C

关键词： fault diagnosis spectroscopy

Phenotyping Tomato Root Developmental Plasticity in Response to Salinity in Soil Rhizotrons

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Plant Phenomics 2021年第1期3卷 14-27页

作者： Jacinto Gandullo Safarina Ahmad essam darwish Rumyana Karlova Christa Testerink Section of Plant Physiology and Plant Cell Biology Swammerdam Institute for Life ScienceUniversity of AmsterdamScience Park 9041098 XH AmsterdamNetherlands Departamento de Biología Vegetal y Ecología Área de Fisiología VegetalFacultad de BiologíaUniversidad de SevillaSevilleSpain Plant Physiology Section Agricultural Botany DepartmentFaculty of AgricultureCairo University12613 GizaEgypt Laboratory of Plant Physiology Plant Sciences GroupWageningen University and Research6708PB WageningenNetherlands

Plants have developed multiple strategies to respond to salt stress.In order to identify new traits related to salt tolerance,with potential breeding application,the research focus has recently been shifted to include root system architecture(RSA)and root plasticity.Using a simple but effective root phenotyping system containing soil(rhizotrons),RSA of several tomato cultivars and their response to salinity was investigated.We observed a high level of root plasticity of tomato seedlings under salt stress.The general root architecture was substantially modified in response to salt,especially with respect to position of the lateral roots in the soil.At the soil surface,where salt accumulates,lateral root emergence was most strongly inhibited.Within the set of tomato cultivars,H1015 was the most tolerant to salinity in both developmental stages studied.A significant correlation between several root traits and aboveground growth parameters was observed,highlighting a possible role for regulation of both ion content and root architecture in salt stress resilience.

关键词： soil cultivar breeding

Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

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Computers, Materials & Continua 2024年第6期79卷 4825-4844页

作者： Ahmed H.Alhadethi Ikram Smaoui Ahmed Fakhfakh Saad M.darwish Computer Science and School of Electronics and Telecommunications University of SfaxSfax3029Tunisia LETI Laboratory University of SfaxSfax3029Tunisia Digital Research Center of Sfax Technopark of SfaxSfax3029Tunisia Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandriaEgypt

The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

关键词： Image transmission image compression text hiding Bezier curve Histogram of Oriented Gradients(HOG) LSTM image enhancement Gaussian noise rotation

Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

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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

Database Recovery Technique for Mobile Computing:A Game Theory Approach

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Computers, Materials & Continua 2022年第2期70卷 3205-3219页

作者： Magda M.Madbouly Yasser F.Mokhtar Saad M.darwish Institute of Graduate Studies and Research Alexandria UniversityAlexandriaEgypt Assistant General Manager IT DepartmentEgyptian Petrochemicals Co.AlexandriaEgypt

Contact between mobile hosts and database servers presents many problems in theMobile Database System(MDS).It is harmed by a variety of causes,including handoff,inadequate capacity,frequent transaction updates,and repeated failures,both of which contribute to serious issues with the information system’s consistency.However,error tolerance technicality allows devices to continue performing their functions in the event of a failure.The aim of this paper is to identify the optimal recovery approach from among the available state-of-the-art techniques in MDS by employing game theory.Several of the presented recovery protocols are chosen and evaluated in order to determine the most critical factors affecting the recovery mechanism,such as the number of processes,the time required to deliver messages,and the number of messages logged-in time.Then,using the suggested payout matrix,the game theory strategy is adapted to choose the optimum recovery technique for the specified environmental variables.The NS2 simulatorwas used to carry out the tests and apply the chosen recovery protocols.The experiments validate the proposed model’s usefulness in comparison to other methods.

关键词： Mobile computing game theory decision making mobile database recovery

Type-2 Neutrosophic Set and Their Applications in Medical Databases Deadlock Resolution

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Computers, Materials & Continua 2023年第2期74卷 4417-4434页

作者： Marwan H.Hassan Saad M.darwish Saleh M.Elkaffas Department of Advocacy and Public Speaking Imam Al-Adham University CollegeAnbar55431Iraq Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and Information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt

Electronic patient data gives many advantages,but also new difficulties.Deadlocks may delay procedures like acquiring patient information.Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties.Soft computing-based solutions have been developed to solve this challenge.In a single framework,ambiguous,vague,incomplete,and inconsistent transaction attribute information has received minimal attention.The work presented in this paper employed type-2 neutrosophic logic,an extension of type-1 neutrosophic logic,to handle uncertainty in real-time deadlock-resolving systems.The proposed method is structured to reflect multiple types of knowledge and relations among transactions’features that include validation factor degree,slackness degree,degree of deadline-missed transaction based on the degree of membership of truthiness,degree ofmembership of indeterminacy,and degree ofmembership of falsity.Here,the footprint of uncertainty(FOU)for truth,indeterminacy,and falsity represents the level of uncertainty that exists in the value of a grade of membership.We employed a distributed real-time transaction processing simulator(DRTTPS)to conduct the simulations and conducted experiments using the benchmark Pima Indians diabetes dataset(PIDD).As the results showed,there is an increase in detection rate and a large drop in rollback rate when this new strategy is used.The performance of Type-2 neutrosophicbased resolution is better than the Type-1 neutrosophic-based approach on the execution ratio scale.The improvement rate has reached 10%to 20%,depending on the number of arrived transactions.

关键词： Deadlock recovery type-2 neutrosophic set healthcare databases distributed deadlock detection

Realistic Smile Expression Recognition Approach Using Ensemble Classifier with Enhanced Bagging

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Computers, Materials & Continua 2022年第2期70卷 2453-2469页

作者： Oday A.Hassen Nur Azman Abu Zaheera Zainal Abidin Saad M.darwish University Technical Malaysia Melaka Department of Information TechnologyMelaka76100Malaysia Institute of Graduate Studies and Research University of AlexandriaAlexandriaEl Shatby21526Egypt

A robust smile recognition system could be widely used for many real-world applications.Classification of a facial smile in an unconstrained setting is difficult due to the invertible and wide variety in face images.In this paper,an adaptive model for smile expression classification is suggested that integrates a fast features extraction algorithm and cascade classifiers.Our model takes advantage of the intrinsic association between face detection,smile,and other face features to alleviate the over-fitting issue on the limited training set and increase classification results.The features are extracted taking into account to exclude any unnecessary coefficients in the feature vector;thereby enhancing the discriminatory capacity of the extracted features and reducing the computational process.Still,the main causes of error in learning are due to noise,bias,and variance.Ensemble helps to minimize these factors.Combinations of multiple classifiers decrease variance,especially in the case of unstable classifiers,and may produce a more reliable classification than a single classifier.However,a shortcoming of bagging as the best ensemble classifier is its random selection,where the classification performance relies on the chance to pick an appropriate subset of training items.The suggested model employs a modified form of bagging while creating training sets to deal with this challenge(error-based bootstrapping).The experimental results for smile classification on the JAFFE,CK+,and CK+48 benchmark datasets show the feasibility of our proposed model.

关键词： Ensemble classifier smile expression detection features extraction

Comparison of success rate and intraocular pressure spikes between selective laser trabeculoplasty and micropulse laser trabeculoplasty in African American and Hispanic patients

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International Journal of Ophthalmology(English edition) 2023年第1期16卷 75-80页

作者： Alexander Z Robin Palwasha Syar Dana darwish Catherine Thomas NMPfahler Agni Kakouri Thomas Patrianakos Michael Giovingo Department of Ophthalmology John H.StrogerJr.Hospital of Cook CountyChicagoIL 60612USA Rosalind Franklin University of Medicine and Science North ChicagoIL 60064USA Department of Ophthalmology and Visual Science University of Illinois at ChicagoChicagoIL 60612USA Department of General Surgery University of Texas at HoustonHoustonTX 77030USA

AIM:To examine the efficacy and safety of micropulse laser trabeculoplasty(MLT)versus selective laser trabeculoplasty(SLT)in a large cohort of primarily African American and Hispanic patients.METHODS:A single center retrospective comparative cohort review conducted at Cook County Health facilities that included patients with a diagnosis of open angle glaucoma or ocular hypertension who received an SLT or MLT procedure between January 2017 and May 2021.RESULTS:Totally 131 eyes of 99 patients were analyzed.The 77 eyes received SLT and 54 received MLT.Seven out of 77 eyes in the SLT group(9.1%)and 1 out of 54 eyes in the MLT group(1.9%)had an IOP spike(defined as>5 mm Hg)at either 1h or 1wk after procedure(P=0.05,Chisquared test with Haldane-Anscombe correction).The procedure failure rate at one year was 50%for SLT and 48%for MLT(P=0.31).CONCLUSION:MLT has a significantly lower incidence of pressure spikes and a similar treatment failure rate at 1-year post-procedure,demonstrating that it is a reasonable alternative compared to SLT.

关键词： selective laser trabeculoplasty micropulse laser trabeculoplasty glaucoma open angle glaucoma ocular hypertension

One-Class Arabic Signature Verification: A Progressive Fusion of Optimal Features

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Computers, Materials & Continua 2023年第4期75卷 219-242页

作者： Ansam A.Abdulhussien Mohammad F.Nasrudin Saad M.darwish Zaid A.Alyasseri Centre of Artificial Intelligence Faculty of Information Sciences and TechnologyUniversity Kebangsaan MalaysiaBangi43600Malaysia Information Technology Center Iraqi Commission for Computers and InformaticsBaghdad10009Iraq Institute of Graduate Studies and Research University of Alexandria163 Horreya AvenueEl Shatby21526P.O.Box 832AlexandriaEgypt

Signature verification is regarded as the most beneficial behavioral characteristic-based biometric feature in security and fraud protection.It is also a popular biometric authentication technology in forensic and commercial transactions due to its various advantages,including noninvasiveness,user-friendliness,and social and legal acceptability.According to the literature,extensive research has been conducted on signature verification systems in a variety of languages,including English,Hindi,Bangla,and Chinese.However,the Arabic Offline Signature Verification(OSV)system is still a challenging issue that has not been investigated as much by researchers due to the Arabic script being distinguished by changing letter shapes,diacritics,ligatures,and overlapping,making verification more difficult.Recently,signature verification systems have shown promising results for recognizing signatures that are genuine or forgeries;however,performance on skilled forgery detection is still unsatisfactory.Most existing methods require many learning samples to improve verification accuracy,which is a major drawback because the number of available signature samples is often limited in the practical application of signature verification systems.This study addresses these issues by presenting an OSV system based on multifeature fusion and discriminant feature selection using a genetic algorithm(GA).In contrast to existing methods,which use multiclass learning approaches,this study uses a oneclass learning strategy to address imbalanced signature data in the practical application of a signature verification system.The proposed approach is tested on three signature databases(SID)-Arabic handwriting signatures,CEDAR(Center of Excellence for Document Analysis and Recognition),and UTSIG(University of Tehran Persian Signature),and experimental results show that the proposed system outperforms existing systems in terms of reducing the False Acceptance Rate(FAR),False Rejection Rate(FRR),and Equal Error Rate(ERR).The proposed system achieved 5

关键词： Offline signature verification biometric system feature fusion one-class classifier