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Ru/NiMnB spherical cluster pillar for highly proficient green hydrogen electrocatalyst at high current density

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Journal of Energy Chemistry 2025年第1期100卷 397-408页

作者： Md Ahasan habib Shusen Lin Mehedi Hasan Joni Sumiya Akter Dristy Rutuja Mandavkar Jae-Hun Jeong Jihoon Lee Department of Electronic Engineering College of Electronics and Information Kwangwoon University

Advanced OER/HER electrocatalytic alternatives are crucial for the wide adaptation of green hydrogen ***,Ru/NiMnB spherical cluster pillar （SCP）,denoted as Ru/NiMnB,is synthesized using a combination of electro-deposition and hydrothermal *** investigation of Ru doping in the NiMnB matrix revealed significant improvements in electrocatalytic *** Ru/NiMnB SCPs demonstrate superior OER/HER activity with low overpotentials of 150 and 103 mV at 50mA/cm2in 1 M KOH,making them highly competitive with state-of-the-art ***,the Ru/NiMnB SCPs exhibit a low 2-E cell voltage of 2.80 V at ultra-high current density of 2,000 m A/cm2in 1 M KOH,outperforming the standard benchmark electrodes of RuO2||Pt/C,thereby positioning Ru/NiMnB as one of the best bifunctional *** SCPs exhibit exceptional high-current characteristics,stability and corrosion resistance,as evidenced by continuous operation at 1,000 mA/cm2high-current density for over 150 h in 6 M KOH at elevated temperatures under harsh industrial *** a small amount of Ru incorporation significantly enhances the electrocatalytic performances of NiMnB,attributed to increased active sites and improved intrinsic properties such as conductivity,adsorption/desorption capability and reaction ***,Ru/NiMnB SCPs present a promising bi-functional electrode concept for efficient green H2production.

关键词： Potassium hydroxide

Pseudo-linear inertial navigation algorithm

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Chinese Journal of Aeronautics 2021年第2期34卷 191-200页

作者： habib GHANBARPOURASL Department of Mechcitronics University of Turkish Aeronautical AssociationAnkara 06790Turkey

A new method is illustrated for processing the output of a set of triad orthogonal rate gyros and accelerometers to reconstruct vehicle navigation parameters(attitude, velocity, and position). The paper introduces two vectors with dimensions 4×1 as velocity and position *** navigation equations for strapdown systems are nonlinear but after using these parameters, the navigation equations are converted into a pseudo-linear system. The new set of navigation equations has an analytical solution and the state transition matrix is used to solve the linear timevarying differential equations through time series. The navigation parameters are updated using the new formulation for strapdown navigation equations. Finally, the quaternions of velocity and position are converted into the original position and velocity vectors. The combination of the coning motion and a translational oscillatory trajectory is used to evaluate the accuracy of the proposed algorithm. The simulations show significant improvement in the accuracy of the inertial navigation system, which is achieved through the mentioned algorithm.

关键词： Inertial navigation algorithm Integrating algorithm Position quaternion Pseudo-linear inertial navigation equation Quaternions Velocity quaternion

Smart COVID-3D-SCNN: A Novel Method to Classify X-ray Images of COVID-19

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Computer Systems Science & Engineering 2022年第6期41卷 997-1008页

作者： ahed Abugabah Atif Mehmood Ahmad Ali A.L Zubi Louis Sanzogni College of Technological Innovation Zayed UniversityAbuDhabi CampusUAE School of Artificial Intelligence Xidian UniversityXian710071China Computer Science Department Community CollegeKing Saud UniversityP.O.Box 28095Riyadh 11437Saudi Arabia Nathan campus Griffith UniversityBrisbaneAustralia

The outbreak of the novel coronavirus has spread worldwide,and millions of people are being *** or detection classification is one of the first application areas of deep learning,which has a significant contribution to medical image *** classification detection,one or more images(detection)are usually used as input,and diagnostic variables(such as whether there is a disease)are used as *** novel coronavirus has spread across the world,infecting millions of ***-stage detection of critical cases of COVID-19 is essential.X-ray scans are used in clinical studies to diagnose COVID-19 and Pneumonia *** extracting the discriminative features through these modalities,deep convolutional neural networks(CNNs)are used.A siamese convolutional neural network model(COVID-3D-SCNN)is proposed in this study for the automated detection of COVID-19 by utilizing X-ray *** extract the useful features,we used three consecutive models working in parallel in the proposed *** acquired 575 COVID-19,1200 non-COVID,and 1400 pneumonia images,which are publicly *** our framework,augmentation is used to enlarge the *** findings suggest that the proposed method outperforms the results of comparative studies in terms of accuracy 96.70%,specificity 95.55%,and sensitivity 96.62%over(COVID-19 ***-COVID19 ***).

关键词： Convolutional neural network classification X-ray deep learning

Early Diagnosis of Alzheimer’s Disease Based on Convolutional Neural Networks

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Computer Systems Science & Engineering 2022年第10期43卷 305-315页

作者： Atif Mehmood ahed Abugabah Ahmed Ali AlZubi Louis Sanzogni College of Technological Innovation Zayed UniversityAbu Dhabi CampusFF2-0-056UAE Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Nathan Campus Griffith UniversityBrisbaneAustralia

Alzheimer’s disease(AD)is a neurodegenerative disorder,causing the most common dementia in the elderly *** AD patients are rapidly increasing in each year and AD is sixth leading cause of death in *** resonance imaging(MRI)is the leading modality used for the diagnosis of *** learning based approaches have produced impressive results in this *** early diagnosis of AD depends on the efficient use of classification *** address this issue,this study proposes a system using two convolutional neural networks(CNN)based approaches for an early diagnosis of AD *** the proposed system,we use segmented MRI *** data samples of three classes include 110 normal control(NC),110 mild cognitive impairment(MCI)and 105 AD subjects are used in this *** data is acquired from the ADNI database and gray matter(GM)images are obtained after the segmentation of MRI subjects which are used for the classification in the proposed *** proposed approaches segregate among NC,MCI,and *** testing both methods applied on the segmented data samples,the highest performance results of the classification in terms of accuracy on NC *** are 95.33%and 89.87%,*** proposed methods distinguish between NC *** and MCI *** patients with a classification accuracy of 90.74%and 86.69%.The experimental outcomes prove that both CNN-based frameworks produced state-of-the-art accurate results for testing.

关键词： Alzheimer’s disease neural networks intelligent systems gray matter

Phylogenetic and morphometric relationships between two species of genus Auxis from the South China Sea and Java Sea

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Acta Oceanologica Sinica 2016年第10期35卷 76-82页

作者： habib Ahasan Environmental and Life Sciences Programme Faculty of ScienceUniversiti Brunei DarussalamJalan TungkuGadong BE 1410Brunei Darussalam Department of Fisheries and Marine Science Noakhali Science and Technology UniversitySonapur-3814NoakhaliBangladesh Universiti Teknologi Brunei Jalan TungkuGadong BE 1410Brunei Darussalam

This study was aimed at examining the phylogenetic and morphometric relationship of frigate tuna（Auxis thazard） and bullet tuna（Auxis rochei） using mt DNA D-loop（control） region sequences and truss measurements,respectively. Maximum-likelihood（ML） tree and median-joining network showed that haplotypes from Auxis populations grouped separately. Discriminant function analyses and non-metric multidimensional scaling of morphometric data showed that bullet and frigate tuna were differed mainly with respect to truss measurements on the anterior region, suggesting adaptation to different diets available in different environments. Historic demographic analyses of sequence data showed that both bullet and frigate tuna had not undergone a significant sudden population expansion recently. Non-significant value of Tajimas＇ s D and Fu＇s F_S were indicated an effective large and stable population size for longer period of both species in South China Sea and Java Sea species. This study gives first report on the complementary relationship between morphometric and genetic analysis in stock discrimination of genus Auxis.

关键词： phylogenetic relationship mtDNA D-loop morphometric analysis Auxis thazard Auxis rochei

A BOUNDARY INTEGRAL METHOD FOR COMPUTING ELASTIC MOMENT TENSORS FOR ELLIPSES AND ELLIPSOIDS

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Journal of Computational Mathematics 2007年第1期25卷 2-12页

作者： habib Ammari HyeonbaeKang HyundaeLee Centre de Mathématiques Appliquées CNRS UMR 7641 and Ecole Polytechnique91128 Palaiseau CedexFrance Department of Mathematical Sciences and RIM Seoul National UniversitySeoul 151-747Korea

The concept of elastic moment tensor occurs in several interesting contexts, in particular in imaging small elastic inclusions and in asymptotic models of dilute elastic composites. In this paper, we compute the elastic moment tensors for ellipses and ellipsoids by using a systematic method based on layer potentials. Our computations reveal an underlying elegant relation between the elastic moment tensors and the single layer potential.

关键词： Elastic moment tensor Explicit formulae Integral equations.

RFID Adaption in Healthcare Organizations:An Integrative Framework

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Computers, Materials & Continua 2022年第1期70卷 1335-1348页

作者： ahed Abugabah Louis Sanzogni Luke Houghton Ahmad Ali AlZubi Alaa Abuqabbeh College of Technical Innovation Zayed UniversityAbu DhabiUAE Nathan Campus Griffith UniversityAustralia Department of Computer Science King Saud UniversityRiyadhSaudi Arabia Golden Gate University San FranciscoCaliforniaUSA

Radio frequency identification(RFID),also known as electronic label technology,is a non-contact automated identification technology that recognizes the target object and extracts relevant data and critical characteristics using radio frequency *** equipment information management is an important part of the construction of a modern hospital,as it is linked to the degree of diagnosis and care,as well as the hospital’s benefits and *** aim of this study is to create an integrated view of a theoretical framework to identify factors that influence RFID adoption in healthcare,as well as to conduct an empirical review of the impact of organizational,environmental,and individual factors on RFID adoption in the healthcare *** contrast to previous research,the current study focuses on individual factors as well as organizational and technological factors in order to better understand the phenomenon of RFID adoption in healthcare,which is characterized as a dynamic and challenging work *** research fills a gap in the current literature by describing how user factors can influence RFID adoption in healthcare and how such factors can lead to a deeper understanding of the advantages,uses,and impacts of RFID in *** proposed study has superior performance and effective results.

关键词： RFID healthcare information technology user factors

Real-time Privacy Preserving Framework for Covid-19 Contact Tracing

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Computers, Materials & Continua 2022年第1期70卷 1017-1032页

作者： Akashdeep Bhardwaj Ahmed A.Mohamed Manoj Kumar Mohammed Alshehri ahed Abugabah School of Computer Science University of Petroleum&Energy Studies(UPES)Dehradun248007India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Information Technology Faculty of Computer and InformationAssiut UniversityAssiut71515Egypt Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Department of Information System College of Technological InnovationZayed UniversityAbu DhabiUnited Arab Emirates

The recent unprecedented threat from COVID-19 and past epidemics,such as SARS,AIDS,and Ebola,has affected millions of people in multiple *** have shut their borders,and their nationals have been advised to *** variety of responses to the pandemic has given rise to data privacy *** prevention and control strategies as well as disease control measures,especially real-time contact tracing for COVID-19,require the identification of people exposed to *** tracing frameworks use mobile apps and geolocations to trace ***,while the motive may be well intended,the limitations and security issues associated with using such a technology are a serious cause of *** are growing concerns regarding the privacy of an individual’s location and personal identifiable information(PII)being shared with governments and/or health *** study presents a real-time,trust-based contact-tracing framework that operateswithout the use of an individual’sPII,location sensing,or gathering GPS *** focus of the proposed contact tracing framework is to ensure real-time privacy using the Bluetooth range of individuals to determine others within the *** research validates the trust-based framework using Bluetooth as practical and *** our proposed methodology,personal information,health logs,and location data will be secure and not *** research analyzes 100,000 tracing dataset records from 150 mobile devices to identify infected users and active users.

关键词： Privacy contact tracing mobile apps Bluetooth Covid epidemic

LogUAD: Log Unsupervised Anomaly Detection Based on Word2Vec

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Computer Systems Science & Engineering 2022年第6期41卷 1207-1222页

作者： Jin Wang Changqing Zhao Shiming He Yu Gu Osama Alfarraj ahed Abugabah School of Computer and Communication Engineering Changsha University of Science&TechnologyChangsha410114China Department of Chemistry Institute of Inorganic and Analytical ChemistryGoethe-UniversityFrankfurt60438Germany Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Zayed University CTIAbu Dhabi144534United Arab Emirates

System logs record detailed information about system operation and areimportant for analyzing the system's operational status and performance. Rapidand accurate detection of system anomalies is of great significance to ensure system stability. However, large-scale distributed systems are becoming more andmore complex, and the number of system logs gradually increases, which bringschallenges to analyze system logs. Some recent studies show that logs can beunstable due to the evolution of log statements and noise introduced by log collection and parsing. Moreover, deep learning-based detection methods take a longtime to train models. Therefore, to reduce the computational cost and avoid loginstability we propose a new Word2Vec-based log unsupervised anomaly detection method (LogUAD). LogUAD does not require a log parsing step and takesoriginal log messages as input to avoid the noise. LogUAD uses Word2Vec togenerate word vectors and generates weighted log sequence feature vectors withTF-IDF to handle the evolution of log statements. At last, a computationally effi-cient unsupervised clustering is exploited to detect the anomaly. We conductedextensive experiments on the public dataset from Blue Gene/L (BGL). Experimental results show that the F1-score of LogUAD can be improved by 67.25%compared to LogCluster.

关键词： Log anomaly detection log instability word2Vec feature extraction