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Assessing model parameters sensitivity and uncertainty of streamflow,sediment,and nutrient transport using SWAT

Information Processing in Agriculture 2019年第1期6卷 61-72页

作者： abdullah o.dakhlalla Prem B.Parajuli Department of Agricultural and Biological Engineering Mississippi State UniversityMississippi StateMS 39762United States

The objectives of this study were to(1)simulate streamflow,total sediment(TS),total phosphorus(TP),and total nitrogen(TN)loads;and(2)use the sequential uncertainty fitting(SUFI-2)algorithm to quantify the model parameter sensitivity and uncertainty in simulating streamflow,TS,TP,and TN loads using Soil and Water Assessment(SWAT)model in Big Sunflower River watershed(BSRW).The model was calibrated from 1996 to 2003 and validated from 2004 to 2010 for daily streamflow,TS load,TP load,and TN *** model performed well simulating daily streamflow(R^2=0.58-0.75,NSE=0.47-0.75),TS load(R^2=0.50-0.72,NSE=0.47-0.66),and TP load(R^2=0.79-0.82,NSE=0.73-0.77),and the model performance was slightly low for TN load(R^2=0.13-0.31,NSE=0.09 to 0.07).This study determined that parameter uncertainty was greatest for simulating TN load(p-factor=0.48,r-factor=1.25)and that parameter uncertainty was lowest for simulating streamflow(p-factor=0.70-0.78,r-factor=1.18-1.19).output uncertainty was much greater during peak streamflow and peak pollutant loads compared to periods of low streamflow and low pollutant *** sensitivity analyses found that streamflow was most sensitive to Manning’s roughness coefficient for the main channel(CH_N2),TS load was most sensitive the peak rate adjustment factor for sediment routing in the tributary channels(ADJ_PKR),TP load was most sensitive to the Phosphorus enrichment ratio for loading with sediments(ERoRGP),and TN load was most sensitive to the denitrification exponential rate coefficient(CDN).Uncertainty was found to be much greater during peak streamflow and peak pollutant loads compared to periods of low streamflow and low pollutant loads.

关键词： Model parameters Sensitivity Uncertainty SWAT Pollutant loads

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Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

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Computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah abdullah Al-Johany Sanaa abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz Alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

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Potential role of tubulin glutamylation in neurodegenerative diseases

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Neural Regeneration Research 2024年第6期19卷 1191-1192页

作者： abdullah Md.Sheikh Shatera Tabassum Department of Laboratory Medicine Shimane University Faculty of MedicineShimaneJapan

The differentiation of neuronal stem cells into mature neurons is a complex process that involves both structural and functional *** cells undergo differentiation,there are notable functional changes,including the expression of various transcription factors,cytokines,and ***,structural changes occur as the cells develop various processes from the cell body and establish synaptic contacts with other cells.

关键词： diseases degenerative cytokines

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A Novel Intrusion Detection Model of Unknown Attacks Using Convolutional Neural Networks

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Computer Systems Science & Engineering 2024年第2期48卷 431-449页

作者： abdullah Alsaleh Department of Information Engineering Florence UniversityFlorenceItaly Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia

With the increasing number of connected devices in the Internet of Things(IoT)era,the number of intrusions is also *** intrusion detection system(IDS)is a secondary intelligent system for monitoring,detecting and alerting against malicious *** is important in developing advanced security *** study reviews the importance of various techniques,tools,and methods used in IoT detection and/or prevention ***,it focuses on machine learning(ML)and deep learning(DL)techniques for *** paper proposes an accurate intrusion detection model to detect traditional and new attacks on the Internet of *** speed up the detection of recent attacks,the proposed network architecture developed at the data processing layer is incorporated with a convolutional neural network(CNN),which performs better than a support vector machine(SVM).Processing data are enhanced using the synthetic minority oversampling technique to ensure learning *** nearest class mean classifier is applied during the testing phase to identify new *** results using the AWID dataset,which is one of the most common open intrusion detection datasets,revealed a higher detection accuracy(94%)compared to SVM and random forest methods.

关键词： Internet of Vehicles intrusion detection machine learning unknown attacks data processing layer

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Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

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Computers, Materials & Continua 2024年第4期79卷 735-759页

作者： Wael M.S.Yafooz abdullah Alsaeedi Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user ***, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

关键词： Mobile apps issues play store user comments deep learning LSTM bidirectional LSTM

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Interplay of serum biomarkers bilirubin andγ-glutamyltranspeptidase in predicting cardiovascular complications in type-2 diabetes mellitus

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World Journal of Diabetes 2024年第6期15卷 1074-1078页

作者： Ebtesam abdullah Al-Suhaimi abdullah Ahmed Al-Rubaish Scientific Research and Innovation Imam Abdulrahman Bin Faisal UniversityDammam 31441Saudi Arabia King Abdulaziz and his Companions Foundation for Giftedness and Creativity“Mawhiba” Riyadh 11372Saudi Arabia College of Medicine Imam Abdulrahman Bin Faisal UniversityDammam 31441Saudi Arabia

This editorial synthesizes insights from a series of studies examining the interplay between metabolic and oxidative stress biomarkers in cardiovascular disease(CVD),focusing particularly on type-2 diabetes mellitus(T2DM)and acute coronary syndrome(ACS).The central piece of this synthesis is a study that investigates the balance between oxidative stress and antioxidant systems in the body through the analysis of serum bilirubin andγ-glutamyltranspeptidase(γ-GGT)levels in T2DM patients with *** study highlights serum bilirubin as a protective antioxidant factor,while elevatedγ-GGT levels indicate increased oxidative stress and correlate with major adverse cardiovascular *** to this,other research contributions revealγ-GGT’s role as a risk factor in ACS,its association with cardiovascular mortality in broader populations,and its link to metabolic syndrome,further elucidating the metabolic dysregulation in *** collective findings from these studies underscore the critical roles ofγ-GGT and serum bilirubin in cardiovascular health,especially in the context of T2DM and *** providing a balanced view of the body’s oxidative and antioxidative mechanisms,these insights suggest potential pathways for targeted interventions and improved prognostic assessments in patients with T2DM and *** synthesis not only corroborates the pivotal role ofγ-GGT in cardiovascular pathology but also introduces the protective potential of antioxidants like bilirubin,illuminating the complex interplay between T2DM and heart *** studies collectively underscore the critical roles of serum bilirubin andγ-GGT as biomarkers in cardiovascular health,particularly in T2DM and ACS contexts,offering insights into the body’s oxidative and antioxidative *** synthesis of research supports the potential of these biomarkers in guiding therapeutic strategies and improving prognostic assessments for patients with T2DM and some CVD.

关键词： Type-2 diabetes mellitus Acute coronary syndrome Serum biomarkers γ-glutamyltranspeptidase Bilirubin Cardiovascular disease

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Time series analysis of L-band PALSAR-2 images in Istanbul and Kocaeli,Turkey

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Big Earth Data 2024年第3期8卷 467-493页

作者： Sadra Karimzadeh abdullah Can Zulfikar Masashi Matsuoka Department of Remote Sensing and GIS University of TabrizTabrizIran Department of Architecture and Building Engineering Tokyo Institute of TechnologyYokohamaJapan Disaster Management Institute Istanbul Technical UniversityMaslakIstanbulTurkey

ABSTRACT Conducting long measurements of infrastructure deformation is a critical engineering *** methods are both timeconsuming and expensive,limiting their use for large-scale *** synergy of synthetic aperture radar(SAR)and geographic information systems(GIS)offers a complementary *** study focuses on the feasibility of using time series analysis of L-band PALSAR-2 images to discover land displacements in Istanbul and Kocaeli,significant industrial and residential areas in ***-2 phase and intensity information were *** phase analysis,14 L-band images from 2014 to 2021 were taken into *** baseline subset(SBAS)analysis was performed using 44 pairs,and results of the velocity,coherence and back-scattering values are *** of all pairs and their correlations were *** Component Analysis(PCA)reduced the dimension of coherence pairs,enhancing feature extraction and the final geocoded velocity map revealed a fastest subsidence rate of−58 mm/yr and a mean subsidence of−20 mm/*** findings were confirmed through mean vertical velocity from Sentinel-1 datasets and field *** results showed that immature land subsidence in the mentioned areas are growing slowly,which can be taken as a serious risk in future.

关键词： InSAR time series PALSAR-2 SAR intensity infrastructure deformation

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Appropriate Combination of Crossover operator and Mutation operator in Genetic Algorithms for the Travelling Salesman Problem

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Computers, Materials & Continua 2024年第5期79卷 2399-2425页

作者： Zakir Hussain Ahmed Habibollah Haron abdullah Al-Tameem Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Kingdom of Saudi Arabia Faculty of Computing Universiti Teknologi MalaysiaJohor Bahru81310Malaysia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Kingdom of Saudi Arabia

Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization *** a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter *** uses a crossover operator to create better offspring chromosomes and thus,converges the ***,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal ***,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization *** this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB *** experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the *** GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.

关键词： Travelling salesman problem genetic algorithms crossover operator mutation operator comprehensive sequential constructive crossover insertion mutation

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Unraveling the role of NiSnPH@ooH/CC perovskite hydroxide for efficient electrocatalytic oxidation of methanol to formate

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Nano Research 2024年第4期17卷 2388-2399页

作者： Jing Shao Yusheng Fang Xiaobing Wu Muhammad Imran abdullah Youkun Tao College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China School of Science Harbin Institute of TechnologyShenzhen 518055China

The sluggish kinetics of oxygen evolution reaction(oER)is the key tailback for hydrogen production from the water *** oER with thermodynamically auspicious methanol oxidation reaction(MoR)can significantly boost the H_(2) and value-added products ***,it is currently challenging to achieve a synergistic manipulation of product selectivity and performance for MoR ***,we report NiSnPH@ooH/CC(CC=carbon cloth)perovskite hydroxide nanosphere as an efficient MoR electrocatalyst with high activity,stability,and selectivity towards methanol oxidation to formate.A surface amorphous layer of defect rich NiooH was generated in operando by selective Sn leaching with stable perovskite hydroxide bulk structure,which mitigates the oxidative power and optimizes the local coordination environment of the active NiooH *** situ Raman combined with electrochemical studies further confirm the key active species,NiooH,generated in operando enhance the MoR and blocking the over oxidation of methanol to Co_(2).As a result,NiSnPH@ooH/CC effectively masks the oER and attains>99%selectivity with 100%Faradic efficiency for *** results of this study show the advances of NiSnPH@ooH/CC as an efficient electrocatalyst for MoR and also suggest its potential applications for various small organic molecules oxidation.

关键词： perovskite hydroxide small organic molecules nickel oxy(hydroxide) value-added products methanol oxidation reaction

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Machine Learning Enabled Novel Real-Time IoT Targeted DoS/DDoS Cyber Attack Detection System

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Computers, Materials & Continua 2024年第9期80卷 3655-3683页

作者： abdullah Alabdulatif Navod Neranjan Thilakarathne Mohamed Aashiq Department of Cybersecurity College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of ICT Faculty of TechnologyUniversity of ColomboColombo00700Sri Lanka Department of Computer Science and Engineering Faculty of EngineeringSouth Eastern University of Sri LankaOluvil32360Sri Lanka

The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber *** the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of *** IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT *** this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS *** CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSo)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)*** proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in *** inv

关键词： Machine learning Internet of Things(IoT),DoS,DDoS cybersecurity intrusion prevention network security,feature optimization,sustainability

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