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Ensuring Secure Platooning of Constrained Intelligent and Connected Vehicles Against Byzantine Attacks:A Distributed MPC Framework

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Engineering 2024年第2期33卷 35-46页

作者： Henglai Wei Hui Zhang Kamal AI-haddad Yang Shi Department of Mechanical Engineering University of VictoriaVictoriaBC V8W 3P6Canada School of Transportation Science and Engineering Beihang UniversityBeijing 100191China École de Technologie Supérieure University of QuebecMontrealQC H3C 1K3Canada

This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine *** introduce a resilient distributed model-predictive platooning control framework for such *** framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among ***,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable *** approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust ***,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network *** analysis demonstrates the recursive feasibility of the DMPC ***,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and *** results verify the effectiveness of our theoretical findings.

关键词： Model predictive control Resilient control Platoon control Intelligent and connected vehicle Byzantine attacks

Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi al-MEKHLAFI Shiguang LIU College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network(CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation knowledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

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 *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** 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 ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-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 *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** 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 *** performance evaluation of the proposed model revealed exemplary results across *** 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

Developing a Model for Parkinson’s Disease Detection Using Machine Learning algorithms

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Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif al Mudawi Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost

The optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function

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Petroleum 2024年第1期10卷 68-84页

作者： Firas A.A.al-Kabbawi Independent scholar Livingston Scotland UNITED KINGDOM

The main objective of this study is to develop the optimal semi-analytical modeling for the infiniteconductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function. The available semi-analytical infinite-conductivity models（ICMs） for horizontal well under rectangular bounded reservoir in literature were developed by applying superposition of pressures in space（SPS）. A new instantaneous source function（i.e., instantaneous uniform-flux segmentary source function under bounded reservoir） is derived to be used instead of SPS to develop the optimal semi-analytical *** new semi-analytical ICM is verified with ICM of Schlumberger [1] and with previous semi-analytical ICMs in terms of bottom hole pressure（BHP） profile and inflow rate distribution along the wellbore. The model is also validated with real horizontal wells in terms of inflow rate distribution along the wellbore. The results show that the developed model gives the optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir. Besides that, high computationalefficiency and high-resolution of wellbore discretization have been achieved（i.e., wellbore segment number could be tens of hundreds depending on solution requirement）. The results also show that at pseudosteady state（PSS） flow regime, inflow rate distribution along the wellbore by previous semi-analytical ICMs is stabilized U-shaped as performance of inflow rate distribution at late radial flow regime. Therefore, the previous semi-analytical ICMs are incorrectly modeling inflow rate distribution at PSS flow regime due to the negative influence of applying SPS. The optimal semi-analytical ICM is in a general form and real time domain,and can be applicable for 3D horizontal well and 2D vertical fracture well under infinite and rectangular bounded reservoirs, of uniform-flux and infinite-conductivity wellbore conditions at any time of

关键词： Infinite-conductivity model Horizontal well performance Semi-analytical modeling Rectangular bounded reservoir Instantaneous source functions Flow regimes

Degradation pathways of amino acids during thermal utilization of biomass: a review

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Frontiers of Chemical Science and Engineering 2024年第7期18卷 67-95页

作者： Mubarak al-Kwradi Mohammednoor altarawneh Department of Chemical and Petroleum Engineering United Arab Emirates UniversityAl-Ain 15551United Arab Emirates

Amino acids are important nitrogen carriers in biomass and entail a broad spectrum of industrial uses,most notably as food additives,pharmaceutical ingredients,and raw materials for bio-based *** detailed information in regard to the fragmentation of amino acids is essential to comprehend the nitrogen transformation chemistry at conditions encountered during hydrothermal and pyrolytic degradation of *** underlying aim of this review is to survey literature studies pertinent to the complex structures of amino acids,their formation yields from various categories of biomass,and their fragmentation routes at elevated temperatures and in the aqueous *** predominant degradation reactions ensue in the decomposition of amino acids,namely deamination and ***,minor differences in structure can greatly affect the fate for each amino ***,amino acids,being nitrogen-rich compounds,play pivotal roles across various *** is a growing interest in producing varied types and configurations of amino *** fermentation appears to a viable approach to produce amino acids at an industrial *** innovative method under investigation is catalytic synthesis using renewable biomass as *** a method taps into the inherent nitrogen in biomass sources like chitin and proteins,eliminating the need for external nitrogen *** environmentally friendly approach is in line with green chemistry principles and has been gathering momentum in the scientific community.

关键词： amino acids pyrolysis biomass nitrogen mechanisms bioenergy

The use of green infrastructure and irrigation in the mitigation of urban heat in a desert city

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Building Simulation 2024年第5期17卷 679-694页

作者： Kai Gao Shamila haddad Riccardo Paolini Jie Feng Muzahim altheeb Abdulrahman AI Mogirah Abdullatif Bin Moammar Mattheos Santamouris School of Built Environment Faculty of ArtsDesign and ArchitectureUniversity of New South WalesSydneyNSW 2052Australia Royal Commission of Riyadh City RiyadhSaudi Arabia Institute of Future Cities Chinese University of Hong KongHong KongChina Department of Building Environment and Energy Engineering The Hong Kong Polytechnic UniversityHong KongChina

Severe urban heat,a prevalent climate change consequence,endangers city residents ***-based mitigation strategies are commonly employed to address this ***,the Middle East and North Africa are under investigated in terms of heat mitigation,despite being one of the regions most vulnerable to climate *** study assesses the feasibility and climatic implications of wide-scale implementation of green infrastructure(GI)for heat mitigation in Riyadh,Saudi Arabia—a representative desert city characterized by low vegetation coverage,severe summer heat,and *** research forecasting model(WRF)is used to simulate GI cooling measures in Riyadh’s summer condition,including measures of increasing vegetation coverage up to 60%,considering irrigation and vegetation types(tall/short).In Riyadh,without irrigation,increasing GI fails to cool the city and can even lead to warming(0.1 to 0.3℃).Despite irrigation,Riyadh’s overall GI cooling effect is 50% lower than GI cooling expectations based on literature meta-analyses,in terms of average peak hour temperature *** study highlights that increased irrigation substantially raises the rate of direct soil evaporation,reducing the proportion of irrigation water used for transpiration and thus diminishing ***,water resource management must be tailored to these specific considerations.

关键词： green infrastructure evapotranspiration cooling desert city irrigation urban overheating

Charged Particles Capture Cross-section by a Weakly Charged Schwarzschild Black Hole

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Research in Astronomy and Astrophysics 2024年第8期24卷 141-146页

作者： A.M.al Zahrani A.al-Jama Physics Department King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia

We study the capture cross-section of charged particles by a weakly charged Schwarzschild black *** dependence of the maximum impact parameter for capture on the particle’s energy is investigated numerically for different values of the electromagnetic coupling strength between the particle and the black *** capture cross-section is then *** show that the capture cross-section is independent of the electromagnetic coupling for ultra-relativistic *** astrophysical implications of our results are discussed.

关键词： stars black holes-accretion-accretion disks-black hole physics

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 ***,paper cups are sent to landfills or waste *** study explores the combined use of red worms(Eisenia fetida)and Greater wax moth(Galleria mellonella)in the biodegradation of paper *** study investigates the conditions and combinations that promote using Eisenia fetida and Galleria mellonella for degrading paper *** 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 *** achieve the study objectives,the study followed a quantitative *** 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 *** study found that the best operating temperature is *** study found that using food waste improves the performance of Eisenia fetida worms and Galleria mellonella larvae *** study found that adding a Galleria mellonella growth-slowing agent slightly enhances the degradation of the paper ***,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