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A Hybrid Neural Network-based Approach for Forecasting Water Demand

Computers, Materials & Continua 2022年第10期73卷 1365-1383页

作者： al-batool al-ghamdi Souad Kamel Mashael Khayyat Department of Computer Science and Artificial Intelligence College of Computer Sciences and EngineeringUniversity of JeddahJeddah 21959Saudi Arabia Department of Computer and Network Engineering College of Computer Sciences and EngineeringUniversity of JeddahJeddah 21959Saudi Arabia Department of Information Systems and Technology College of Computer Sciences and EngineeringUniversity of JeddahJeddah 21959Saudi Arabia

Water is a vital resource.It supports a multitude of industries,civilizations,and agriculture.However,climatic conditions impact water availability,particularly in desert areas where the temperature is high,and rain is scarce.Therefore,it is crucial to forecast water demand to provide it to sectors either on regular or emergency days.The study aims to develop an accurate model to forecast daily water demand under the impact of climatic conditions.This forecasting is known as a multivariate time series because it uses both the historical data of water demand and climatic conditions to forecast the future.Focusing on the collected data of Jeddah city,Saudi Arabia in the period between 2004 and 2018,we develop a hybrid approach that uses Artificial Neural Networks(ANN)for forecasting and Particle Swarm Optimization algorithm(PSO)for tuning ANNs’hyperparameters.Based on the Root Mean Square Error(RMSE)metric,results show that the(PSO-ANN)is an accurate model for multivariate time series forecasting.also,the first day is the most difficult day for prediction(highest error rate),while the second day is the easiest to predict(lowest error rate).Finally,correlation analysis shows that the dew point is the most climatic factor affecting water demand.

关键词： Water demand forecasting artificial neural network multivariate time series climatic conditions particle swarm optimization hybrid algorithm

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A new fractional order 6D chaotic model:Study of model dynamics,system structure graph,electronic circuit realization and fractional control

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Journal of Ocean Engineering and Science 2024年第2期9卷 112-125页

作者： M.Higazy Norah almalki Shabbir Muhammad A.al-ghamdi Department of Mathematics and Statistics College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Physics and Engineering Mathematics Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Research Center for Advanced Materials Science(RCAMS) King Khalid UniversityP.O.Box 9004Abha 61413Saudi Arabia Department of Chemistry College of ScienceKing Khalid UniversityP.O.Box 9004Abha 61413Saudi Arabia Department of Physics Faculty of ScienceKing Abdulaziz UniversityP.O.Box 80203Jeddah 21589Saudi Arabia

A new fractional 6D chaotic model is constructed in this paper.The new fractional 6D chaotic model has six positive parameters plus the fractional order with eight nonlinear terms.The complicated chaotic dy-namics of the new fractional 6D model is presented and analyzed.The basic properties of this model are studied and its chaotic attractors,dissipative feature,symmetry,equilibrium points,Lyapunov Exponents are investigated.The new dynamics of the 6D fractional model is numerically simulated using Matlab software.In addition,utilizing the graph theory tools certain structural characteristics are calculated.An electrical circuit is built to implement the new 5.4 fractional order 6D model.Finally,an active fractional order controller is proposed to control the new model at different fractional orders.The chaos of the new model is very useful and can be used to produce random keys for data encryption.

关键词： Chaotic systems Fractional calculus Lyapunov exponents Chaotic attractors Adjacency matrix Hermitian matrix Electronic circuit realization

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Spatio-temporal coupled mode theory for nonlocal metasurfaces

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Light(Science & Applications) 2024年第2期13卷 267-282页

作者： Adam Overvig Sander A.Mann Andrea alù Photonics Initiative Advanced Science Research CenterCity University of New YorkNew YorkNY10031USA Physics Program Graduate Center of the City University of New YorkNew YorkNY10016USA

Diffractive nonlocal metasurfaces have recently opened a broad range of exciting developments in nanophotonics research and applications,leveraging spatially extended—yet locally patterned—resonant modes to control light with new degrees of freedom.While conventional grating responses are elegantly captured by temporal coupled mode theory,current approaches are not well equipped to capture the arbitrary spatial response observed in the nascent field of nonlocal metasurfaces.Here,we introduce spatio-temporal coupled mode theory(STCMT),capable of elegantly capturing the key features of the resonant response of wavefront-shaping nonlocal metasurfaces.This framework can quantitatively guide nonlocal metasurface design while maintaining compatibility with local metasurface frameworks,making it a powerful tool to rationally design and optimize a broad class of ultrathin optical components.We validate this STCMT framework against full-wave simulations of various nonlocal metasurfaces,demonstrating that this tool offers a powerful semi-analytical framework to understand and model the physics and functionality of these devices,without the need for computationally intense full-wave simulations.We also discuss how this model may shed physical insights into nonlocal phenomena in photonics and the functionality of the resulting devices.As a relevant example,we showcase STCMT’s flexibility by applying it to study and rapidly prototype nonlocal metasurfaces that spatially shape thermal emission.

关键词： theory resonant spatially

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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 users.It hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by consumers.The 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 techniques.Moreover,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive hardware.Computer-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 performance.In this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious activity.The key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft detection.Different advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for classification.The 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 results.The performance evaluation of the proposed model revealed exemplary results across variousmetrics.The 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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Glucokinase regulatory protein rs780094 polymorphism is associated with type 2 diabetes mellitus, dyslipidemia, non-alcoholic fatty liver disease, and nephropathy

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World Journal of Diabetes 2024年第5期15卷 814-817页

作者： Ashraf al Madhoun Department of Genetics and Bioinformatics Dasman Diabetes InstituteDasman 15400Kuwait

In this editorial,we comment on the article by Liu et al published in the recent issue of the World Journal of Diabetes(Relationship between GCKR gene rs780094 polymorphism and type 2 diabetes with albuminuria).Type 2 diabetes mellitus(T2DM)is a chronic disorder characterized by dysregulated glucose homeostasis.The persistent elevated blood glucose level in T2DM significantly increases the risk of developing severe complications,including cardiovascular disease,re-tinopathy,neuropathy,and nephropathy.T2DM arises from a complex interplay between genetic,epigenetic,and environmental factors.Global genomic studies have identified numerous genetic variations associated with an increased risk of T2DM.Specifically,variations within the glucokinase regulatory protein(GCKR)gene have been linked to heightened susceptibility to T2DM and its associated complications.The clinical trial by Liu et al further elucidates the role of the GCKR rs780094 polymorphism in T2DM and nephropathy development.Their findings demonstrate that individuals carrying the CT or TT genotype at the GCKR rs780094 locus are at a higher risk of developing T2DM with albuminuria compared to those with the CC genotype.These findings highlight the importance of genetic testing and risk assessment in T2DM to develop effective preventive strategies and personalized treatment plans.

关键词： Glucokinase regulatory protein rs780094 Type 2 diabetes mellitus Dyslipidemia Non-alcoholic fatty liver disease Nephropathy

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Enhancing the Decomposition of Paper Cups Using Galleria Mellonella and Eisenia Fetida

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Journal of Renewable Materials 2024年第2期12卷 349-367页

作者： Shadi Moqbel Habib al-Ghoul Abd al-Majeed al-Ghzawi Rami Mukbel Civil Engineering Department The University of JordanAmman11942Jordan Department of Chemistry Technical University of MunichMunichGermany Plant Production Jordan University of Science and TechnologyIrbid22110Jordan Basic Medical Veterinary Sciences Jordan University of Science and TechnologyIrbid22110Jordan

The composition of paper cups creates a challenge for the recycling industry,as the paperboard–plastic film composite is hard to separate.Therefore,paper cups are sent to landfills or waste incinerators.This study explores the combined use of red worms(Eisenia fetida)and Greater wax moth(Galleria mellonella)in the biodegradation of paper cups.The study investigates the conditions and combinations that promote using Eisenia fetida and Galleria mellonella for degrading paper cups.The study considered the influence of environmental temperature,the presence of food waste,varying the number of Eisenia fetida worms,and the presence of a Galleria mellonella growth-slowing agent on the degradation process.To achieve the study objectives,the study followed a quantitative approach.The study monitored the degradation of paper cup cuts that were placed in jars containing different combinations of Eisenia fetida worms,Galleria mellonella larvae,food waste,bedding material,and Galleria mellonella growth-slowing agents.The study found that the best operating temperature is 30oC.The study found that using food waste improves the performance of Eisenia fetida worms and Galleria mellonella larvae significantly.The study found that adding a Galleria mellonella growth-slowing agent slightly enhances the degradation of the paper cup.Finally,a numerical model was obtained to simulate the paper cup degradation efficiency.

关键词： Paper cups resource recovery recycling circular economy Galleria mellonella Eisenia fetida

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Corrosion and Scaling Threat in Upstream Oil Operation

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World Journal of Engineering and Technology 2024年第2期12卷 426-437页

作者： Nasir Ullattumpoyil Talal M. al-ghamdi Nasser R. al-Hajri Southern Area Technical Support Department Saudi Aramco Dhahran KSA

Corrosiveness or scaling is an inherent threat to oil operations. The primary cause for this threat is the presence of water having complex geochemical matrix. Unanticipated water production, particularly if it contains unwanted impurities, can significantly impact hydrocarbon production. The current paper discusses the degree of threat posed to oil operation facilities based on the water characteristics. Methodology involved the collection and analysis of water samples from major sources in oil industry such as groundwater, wellheads and seawater. The parameters tested include geochemical, microbiological and pollutants. The lab data was used to develop scaling and corrosion prediction indices such as Langelier Saturation Index (LSI), Ryznar Stability Index (RSI) and Puckorius Scaling Index (PSI). The study indicated varying water chemistry for different sources. Mixing of those waters may lead to ionic saturation and scaling in different facilities. Presence of the SRB and GAB in some water sources also posed threat to water system by forming fouling and corrosion. Seawater used for offshore oilfields water injection to maintain reservoir pressure and improve oil recovery showed scaling tendency, whereas under different reservoir pressure, it can cause corrosion. Some of the samples also had corrosion residuals such as iron, which indicated active corrosion. Current study showed higher alkalinity with high sulfate for one groundwater sample with presence of active corrosion residuals such as dissolved iron and manganese. The study showed positive value for LSI which indicated supersaturation of the water samples with respect to calcium carbonate (CaCO3) and scale forming. Similarly, for RSI and PSI, the value was below six which confirmed the scaling potential for all the samples. Even though the index value was pointing towards scaling potential, the geochemistry, microbiology and presence of other impurities indicated corrosion threat to the oil and gas industrial facilities. The study concluded th

关键词： Formation Water Petroleum Reservoirs Groundwater Saturation Indices Corrosiveness

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Fostering firm innovativeness:Understanding the sequential relationships between human resource practices,psychological empowerment,innovative work behavior,and firm innovative capability

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International Journal of Innovation Studies 2024年第1期8卷 76-91页

作者： Ruba Sami al Daboub Amro al-Madadha Ahmad Samed al-Adwan Business Administration Department Princess Sumaya University for TechnologyAmmanJordan Department of Business Technology Business SchoolHourani Center for Applied Scientific ResearchAl-Ahliyya Amman UniversityAmmanJordan

This study investigated the relationships between human resource(HR)practices,employee psychological empowerment,employee innovative work behavior,and firm innovation capability in the context of the Information and Communication Technology(ICT)sector in Jordan.Employing the Social Exchange Theory(SET)as a guiding framework,this study explored how employee psychological empowerment and innovative work behavior mediated the influence of HR practices on a firm’s innovative capabilities.Drawing on extensive data collected from ICT organizations in Jordan,our analysis had several key findings.A significant positive correlation between HR practices and psychological empowerment was observed.Job design emerged as the most influential factor affecting psychological empowerment,whereas compensation had a weaker impact.Furthermore,we established that psychological empowerment significantly enhanced innovative work behavior,underscoring its role as a catalyst for innovative work behavior within the sector.Finally,our study supported the theory that psychological empowerment influenced a firms’innovation capabilities,emphasizing the pivotal role of employee empowerment in driving firm-level innovation in the Jordanian ICT sector.These findings provide insights for academic and practical audiences,clarifying how HR practices,employee psychological empowerment,and innovative work behavior collectively influenced firm innovation capability within the unique context of the Jordanian ICT sector.

关键词： Human resources practices Psychological empowerment Innovative work behavior Firm innovative capability Social exchange theory Job design

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Deep eutectic solvents:Green multi-task agents for sustainable super green hydrogen technologies

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Journal of Energy Chemistry 2024年第5期92卷 357-382页

作者： Raiyan al-Farsi Maan Hayyan Renewable Energy Engineering Program Faculty of Engineering and TechnologyMuscat UniversityMuscat 130Oman Chemical Engineering Program Faculty of Engineering and TechnologyMuscat UniversityMuscat 130Oman

While reliance on renewable energy resources has become a reality, there is still a need to deploy greener and more sustainable methods in order to achieve sustainable development goals. Indeed, green hydrogen is currently believed to be a reliable solution for global warming and the pollution challenges arising from fossil fuels, making it the resilient fuel of the future. However, the sustainability of green hydrogen technologies is yet to be achieved. In this context, generation of green hydrogen with the aid of deep eutectic solvents(DESs) as green mixtures has been demonstrated as a promising research area. This systematic review article covers green hydrogen generation through water splitting and biomass fermentation when DESs are utilized within the generation process. It also discusses the incorporation of DESs in fuel cell technologies. DESs can play a variety of roles such as solvent, electrolyte, or precursor;colloidal suspension and reaction medium;galvanic replacement, shape-controlling, decoration, or extractive agent;finally oxidant. These roles are relevant to several methods of green hydrogen generation, including electrocatalysis, photocatalysis, and fermentation. As such, it is of utmost importance to screen potential DES formulations and determine how they can function in and contribute throughout the green hydrogen mobility stages. The realization of super green hydrogen generation stands out as a pivotal milestone in our journey towards achieving a more sustainable form of development;DESs have great potential in making this milestone achievable. Overall, incorporating DESs in hydrogen generation constitutes a promising research area and offers potential scalability for green hydrogen production, storage,transport, and utilization.

关键词： Watersplitting Biohydrogen Super green hydrogen Electrocatalysis Photocatalysis Fuel cell Power-to-X

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Cloud Datacenter Selection Using Service Broker Policies:A Survey

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 1-41页

作者： Salam al-E’mari Yousef Sanjalawe Ahmad al-Daraiseh Mohammad Bany Taha Mohammad aladaileh Department of Information Security Faculty of ITUniversity of PetraAmman11196Jordan Department of Cybersecurity School of ITAmerican University of Madaba(AUM)Amman11821Jordan Department of Computer Science School of ITAmerican University of Madaba(AUM)Amman11821Jordan Department of Data Science and Artificial Intelligence School of ITAmerican University of Madaba(AUM)Amman11821Jordan

Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC selection.Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service quality.To tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)demands.Amidst numerous CSB policies,their implementation grapples with challenges like costs and availability.This article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current policies.The foremost objective is to pinpoint research gaps and remedies to invigorate future policy development.Additionally,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers alike.Employing synthetic analysis,the article systematically assesses and compares myriad DC selection techniques.These analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their needs.In summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC performance.By emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain.

关键词： Cloud computing cloud service broker datacenter selection quality-of-service user request

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