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Development of multiple soft computing models for estimating organic and inorganic constituents in coal 认领 引用 被引量：10
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作者 M.Onifade A.I.Lawal +4 位作者 J.Abdulsalam B.Genc S.Bada K.O.Said A.R.Gbadamosi 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2021年第3期483-494,共12页
The distribution of the various organic and inorganic constituents and their influences on the combustion of coal has been comprehensively studied.However,the combustion characteristics of pulverized coal depend not o... The distribution of the various organic and inorganic constituents and their influences on the combustion of coal has been comprehensively studied.However,the combustion characteristics of pulverized coal depend not only on rank but also on the composition,distribution,and combination of the macerals.Unlike the proximate and ultimate analyses,determining the macerals in coal involves the use of sophisticated microscopic instrumentation and expertise.In this study,an attempt was made to predict the amount of macerals(vitrinite,inertinite,and liptinite)and total mineral matter from the Witbank Coalfields samples using the multiple input single output white-box artificial neural network(MISOWB-ANN),gene expression programming(GEP),multiple linear regression(MLR),and multiple nonlinear regression(MNLR).The predictive models obtained from the multiple soft computing models adopted are contrasted with one another using difference,efficiency,and composite statistical indicators to examine the appropriateness of the models.The MISOWB-ANN provides a more reliable predictive model than the other three models with the lowest difference and highest efficiency and composite statistical indicators. 展开更多
关键词 Multiple soft computing models Coal Organic and inorganic constituents
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Real-time prediction of ship motions based on the reservoir computing model 认领 引用
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作者 Yu Yang Tao Peng +1 位作者 Shijun Liao Jing Li 《Journal of Ocean Engineering and Science》 SCIE CSCD 2025年第3期379-395,共17页
Real-time prediction of ship motions is crucial for ensuring the safety of offshore activities.In this study,we investigate the performance of the reservoir computing(RC)model in predicting the motions of a ship saili... Real-time prediction of ship motions is crucial for ensuring the safety of offshore activities.In this study,we investigate the performance of the reservoir computing(RC)model in predicting the motions of a ship sailing in irregular waves,comparing it with the long short-term memory(LSTM),bidirectional LSTM(BiLSTM),and gated recurrent unit(GRU)networks.The model tests are carried out in a towing tank to generate the datasets for training and testing the machine learning models.First,we explore the performance of machine learning models trained solely on motion data.It is found that the RC model outperforms the L STM,BiL STM,and GRU networks in both accuracy and efficiency for predicting ship motions.Besides,we investigate the performance of the RC model trained using the historical motion and wave elevation data.It is shown that,compared with the RC model trained solely on motion data,the RC model trained on the motion and wave elevation data can significantly improve the motion prediction accuracy.This study validates the effectiveness and efficiency of the RC model in ship motion prediction during sailing and highlights the utility of wave elevation data in enhancing the RC model’s prediction accuracy. 展开更多
关键词 Ship motion Real-time prediction Machine learning Reservoir computing model
Data-Driven Materials Science Using Machine Learning and Computational Modeling 认领 引用
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作者 Manjodh Kaur Princy Randhawa +4 位作者 Jitendra Jaiswal Deepak Dubal Ravindra N.Bulakhe Deepanraj Balakrishnan Nithesh Naik 《Computers, Materials & Continua》 SCIE EI 2026年第8期90-124,共35页
This review emphasizes the growing role of artificial intelligence(AI)in transforming the materials discovery process into a data-driven and autonomous approach.It systematically traces the evolution of scientific par... This review emphasizes the growing role of artificial intelligence(AI)in transforming the materials discovery process into a data-driven and autonomous approach.It systematically traces the evolution of scientific paradigms in materials science and examines how machine learning,generative models,and AI agents are revolutionizing the design,screening,and optimization of materials.A key contribution is a detailed,step-by-step machine learning framework that guides researchers through data collection,preprocessing,feature engineering,model development,and validation,utilizing publicly available materials databases and computational tools.Additionally,the review discusses the latest advances in generative AI and autonomous research systems,highlighting their potential to enable inverse design and closed-loop experiments.It includes a tutorial case study on sodium-ion battery materials to demonstrate practical application in formation energy prediction via machine learning,along with comparisons to high-throughput screening accuracy using density functional theory(DFT).The article also addresses current challenges such as data limitations,model interpretability,and physics-based approaches.Overall,this publication serves as both a conceptual and practical guide for integrating AI into materials research,aiming to accelerate the discovery process and improve efficiency. 展开更多
关键词 Artificial intelligence materials science materials discovery energy materials computational modeling
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Computational and Experimental Modeling of Curved Crack Effects on the Dynamic Response of Plate Structures 认领 引用
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作者 Yousef Lafi A.Alshammari Muhammad Khan Hilal Doganay Kati 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期252-278,共27页
Cracks can severely degrade the integrity and service performance of plate structures.Although most existing studies focus on identifying straight crack patterns using dynamic response data,curved crack paths have rec... Cracks can severely degrade the integrity and service performance of plate structures.Although most existing studies focus on identifying straight crack patterns using dynamic response data,curved crack paths have received far less attention,despite being more realistic in practice and having a stronger influence on structural behaviour.This study presents a computational and experimental framework for analyzing and identifying curved crack paths in cantilever plate structures based on dynamic response characteristics.Curved crack paths are modelled using second-order polynomial equations.Finite Element Analysis(FEA)is employed to evaluate the effects of polynomial coefficients and crack end abscissa(xend)on natural frequency and resonance amplitude,while experimental modal analysis(EMA)on damping ratio.Forward and inverse identification models are then developed using linear regression(LR)and artificial neural networks(ANN)to predict dynamic response characteristics and estimate crack path.Results show that the quadratic coefficient(a)and linear coefficient(b)of the crack path have the most decisive influence on the plate’s vibration characteristics,whereas the constant term(c)has a negligible effect.Also,the crack paths with greater curvature and inclination,represented by higher a and b coefficients,especially at smaller end abscissae(xend),tend to reduce natural frequencies and increase vibration amplitudes and damping ratios.In contrast,smoother,less curved cracks exhibit the opposite behaviour.These curved crack geometries cause greater stiffness degradation by altering both axial and shear stiffness.Consequently,local flexibility and energy dissipation increase due to enhanced crack-surface interaction and localised deformation.The proposed computational models are experimentally validated using 15 fabricated plates with different curved crack profiles,demonstrating high prediction accuracy.Overall,the study enhances the computational identification and characterization of curved cracks in plate structures,contributing to improved damage assessment and structural health monitoring(SHM)based on dynamic response. 展开更多
关键词 Curved crack paths computational modeling dynamic response analysis finite element analysis(FEA) artificial neural networks
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Computational models for solid-state sintering in metal extrusion additive manufacturing:Trends,challenges,and future directions 认领 引用
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作者 Judice Cumbunga Saïd Abboudi Dominique Chamoret 《Additive Manufacturing Frontiers》 CAS CSCD 2026年第1期57-87,共31页
Solid-state sintering is a crucial thermal post-processing step in metal extrusion additive manufacturing(MExAM),influencing the microstructural evolution,densification,and final properties of fabricated components.Ho... Solid-state sintering is a crucial thermal post-processing step in metal extrusion additive manufacturing(MExAM),influencing the microstructural evolution,densification,and final properties of fabricated components.However,accurately simulating this process remains challenging due to its inherently multiscale and multiphysics nature.This comprehensive and critical review examines the main computational approaches developed to model solidstate sintering in the MExAM context,ranging from nano-to macrostructure scales,including molecular dynamics,kinetic Monte Carlo,discrete element methods,phase-field models,and continuum-based methods.For each,we detail the underlying mathematical formulations,numerical strategies,and implementation environments.Their capabilities and limitations are evaluated in terms of scale resolution,physical accuracy,and computational demands.Particular attention is given to challenges such as the coupling of thermal,mechanical,and diffusive phenomena,as well as the difficulty of bridging disparate spatial and temporal scales.In response to these limitations,emerging trends such as Physics-informed machine learning(PIML)offer promising avenues to enhance predictive accuracy,improve computational efficiency,and streamline simulation workflows.By integrating conventional modeling techniques with data-driven approaches,the field is moving toward faster and more reliable predictions of sintering behavior,advancing the goals of the MExAM initiative.The insights presented aim to guide future research focused on optimizing sintering processes for broader industrial applications and improved material performance. 展开更多
关键词 Metal extrusion additive manufacturing Solid-state sintering Computational modeling Multiscale simulation Multiphysical couplings Physics-informed machine learning
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The promise of cardiomyocyte computational models for drug safety 认领 引用
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作者 Lei Wang Blanca Rodriguez 《Military Medical Research》 SCIE CAS CSCD 2026年第4期682-685,共4页
Dear Editor,Drug development stands at a crossroads.Traditional animal testing for cardiac safety faces growing scientific and ethical challenges,while computational alternatives are demonstrating valuable predictive ... Dear Editor,Drug development stands at a crossroads.Traditional animal testing for cardiac safety faces growing scientific and ethical challenges,while computational alternatives are demonstrating valuable predictive capabilities.Cardiomyocyte computational models,rooted in concepts developed over 6 decades ago,now represent a mature and viable approach for pharmaceutical research,particularly when integrated with modern experi-mental platforms.This letter reviews the application of cardiac electrophysiology models in drug safety evaluation,a field where they offer transformative potential.We focus specifically on cardiac electrical activity relevant to drug safety,leaving the equally important domain of cardiac mechanics for future discussion. 展开更多
关键词 Cardiomyocyte computational models Drug safety testing Cardiac electrophysiology In silico clinical trials Artificial intelligence(AI)
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Guest Editorial for the Special Issue on Advanced Computational Modeling and Simulations for Engineering Structures and Multifunctional Materials:Bridging Theory and Practice 认领 引用
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作者 S.M.Anas Rayeh Nasr Al-Dala’ien 《Computers, Materials & Continua》 SCIE EI 2026年第7期2268-2273,共6页
1 Introduction The growing use of computational modelling, simulation tools, and data-driven methods has changedhe way engineering structures and advanced materials are studied and designed. With the increasing availa... 1 Introduction The growing use of computational modelling, simulation tools, and data-driven methods has changedhe way engineering structures and advanced materials are studied and designed. With the increasing availability of high-performance computing, artificial intelligence, and multi-scale simulation techniques,computational modelling is no longer limited to purely theoretical studies. It has now emerged as a practical design aid, allowing researchers to predict material behavior, understand complex interactions, and support engineering decisions across different material and structural scales. These developments have helped in narrowing the gap between theoretical studies and practical engineering applications. 展开更多
关键词 engineering structures practical design aid advanced materials understand complex inte computational modelling simulation tools predict material behavior artificial intelligence
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Applications of Artificial Intelligence in Cardiac Electrophysiology and Clinical Diagnosis with Magnetic Resonance Imaging and Computational Modeling Techniques 认领 引用 被引量：1
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作者 ZHAN Heqin HAN Guilail +1 位作者 WEI Chuan'an LI Zhiqun 《Journal of Shanghai Jiaotong university(Science)》 EI 2025年第1期53-65,共13页
The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely exp... The underlying electrophysiological mechanisms and clinical treatments of cardiovascular diseases,which are the most common cause of morbidity and mortality worldwide,have gotten a lot of attention and been widely explored in recent decades.Along the way,techniques such as medical imaging,computing modeling,and artificial intelligence(AI)have always played significant roles in above studies.In this article,we illustrated the applications of AI in cardiac electrophysiological research and disease prediction.We summarized general principles of AI and then focused on the roles of AI in cardiac basic and clinical studies incorporating magnetic resonance imaging and computing modeling techniques.The main challenges and perspectives were also analyzed. 展开更多
关键词 artificial intelligence(AI) magnetic resonance imaging computing modeling cardiovascular disease
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Failure Analyses of Cylindrical Lithium-Ion Batteries Under Dynamic Loading Based on Detailed Computational Model 认领 引用 被引量：1
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作者 Huifeng Xi Guicheng Zhao +3 位作者 Shuo Wang Junkui Li Linghui He Bao Yang 《Acta Mechanica Solida Sinica》 SCIE EI CSCD 2025年第3期526-538,共13页
Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runa... Electric vehicles,powered by electricity stored in a battery pack,are developing rapidly due to the rapid development of energy storage and the related motor systems being environmentally friendly.However,thermal runaway is the key scientific problem in battery safety research,which can cause fire and even lead to battery explosion under impact loading.In this work,a detailed computational model simulating the mechanical deformation and predicting the short-circuit onset of the 18,650 cylindrical battery is established.The detailed computational model,including the anode,cathode,separator,winding,and battery casing,is then developed under the indentation condition.The failure criteria are subsequently established based on the force–displacement curve and the separator failure.Two methods for improving the anti-short circuit ability are proposed.Results show the three causes of the short circuit and the failure sequence of components and reveal the reason why the fire is more serious under dynamic loading than under quasi-static loading. 展开更多
关键词 18,650 lithium-ion battery Detailed computational model Deformation Fracture mode Failure criteria
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Unveiling micro-scale mechanisms of in-situ silicon alloying for tailoring mechanical properties in titanium alloys:Experiments and computational modeling 认领 引用
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作者 Sisi Tang Li Li +3 位作者 Jinlong Su Yuan Yuan Yong Han Jinglian Fan 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2025年第17期150-163,共14页
Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the... Titanium-silicon(Ti-Si)alloy system shows significant potential for aerospace and automotive applications due to its superior specific strength,creep resistance,and oxidation resistance.For Si-containing Ti alloys,the sufficient content of Si is critical for achieving these favorable performances,while excessive Si addition will result in mechanical brittleness.Herein,both physical experiments and finite element(FE)simulations are employed to investigate the micro-mechanisms of Si alloying in tailoring the mechanical properties of Ti alloys.Four typical states of Si-containing Ti alloys(solid solution state,hypoeutectoid state,near-eutectoid state,hypereutectoid state)with varying Si content(0.3-1.2 wt.%)were fabricated via in-situ alloying spark plasma sintering.Experimental results indicate that in-situ alloying of 0.6 wt.%Si enhances the alloy’s strength and ductility simultaneously due to the formation of fine and uniformly dispersed Ti5Si3particles,while higher content of Si(0.9 and 1.2 wt.%)results in coarser primary Ti5Si3agglomerations,deteriorating the ductility.FE simulations support these findings,highlighting the finer and more uniformly distributed Ti5Si3particles contribute to less stress concentration and promote uniform deformation across the matrix,while agglomerated Ti5Si3particles result in increased local stress concentrations,leading to higher chances of particle fracture and reduced ductility.This study not only elucidates the micro-mechanisms of in-situ Si alloying for tailoring the mechanical properties of Ti alloys but also aids in optimizing the design of high-performance Si-containing Ti alloys. 展开更多
关键词 Titanium alloy Spark plasma sintering Micro-scale deformation behavior Mechanical property tailoring Computational modeling
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A Data-Driven Systematic Review of the Metaverse in Transportation:Current Research,Computational Modeling,and Future Trends 认领 引用
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作者 Cecilia Castro Victor Leiva Franco Basso 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第8期1481-1543,共63页
Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieve... Metaverse technologies are increasingly promoted as game-changers in transport planning,connectedautonomous mobility,and immersive traveler services.However,the field lacks a systematic review of what has been achieved,where critical technical gaps remain,and where future deployments should be integrated.Using a transparent protocol-driven screening process,we reviewed 1589 records and retained 101 peer-reviewed journal and conference articles(2021–2025)that explicitly frame their contributions within a transport-oriented metaverse.Our reviewreveals a predominantly exploratory evidence base.Among the 101 studies reviewed,17(16.8%)apply fuzzymulticriteria decision-making,36(35.6%)feature digital-twin visualizations or simulation-based testbeds,9(8.9%)present hardware-in-the-loop or field pilots,and only 4(4.0%)report performance metrics such as latency,throughput,or safety under realistic network conditions.Over time,the literature evolves fromearly conceptual sketches(2021–2022)through simulation-centered frameworks(2023)to nascent engineering prototypes(2024–2025).To clarify persistent gaps,we synthesize findings into four foundational layers—geometry and rendering,distributed synchronization,cryptographic integrity,and human factors—enumerating essential algorithms(homogeneous 4×4 transforms,Lamport clocks,Raft consensus,Merkle proofs,sweep-and-prune collision culling,Q-learning,and real-time ergonomic feedback loops).A worked bus-fleet prototype illustrates how blockchain-based ticketing,reinforcement learning-optimized traffic signals,and extended reality dispatch can be integrated into a live digital twin.This prototype is supported by a threephase rollout strategy.Advancing the transport metaverse from blueprint to operation requires open data schemas,reproducible edge–cloud performance benchmarks,cross-disciplinary cyber-physical threat models,and city-scale sandboxes that apply their mathematical foundations in real-world settings. 展开更多
关键词 Artificial intelligence blockchain computational modeling digital twins extended reality fuzzy MCDM machine learning metaverse reinforcement learning
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An improved memristor model for brain-inspired computing 认领 引用 被引量：2
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作者 周二瑞 方粮 +1 位作者 刘汝霖 汤振森 《Chinese Physics B》 SCIE EI CAS CSCD 2017年第11期537-543,共7页
Memristors, as memristive devices, have received a great deal of interest since being fabricated by HP labs. The forgetting effect that has significant influences on memristors＇ performance has to be taken into accou... Memristors, as memristive devices, have received a great deal of interest since being fabricated by HP labs. The forgetting effect that has significant influences on memristors＇ performance has to be taken into account when they are employed. It is significant to build a good model that can express the forgetting effect well for application researches due to its promising prospects in brain-inspired computing. Some models are proposed to represent the forgetting effect but do not work well. In this paper, we present a novel window function, which has good performance in a drift model. We analyze the deficiencies of the previous drift diffusion models for the forgetting effect and propose an improved model. Moreover,the improved model is exploited as a synapse model in spiking neural networks to recognize digit images. Simulation results show that the improved model overcomes the defects of the previous models and can be used as a synapse model in brain-inspired computing due to its synaptic characteristics. The results also indicate that the improved model can express the forgetting effect better when it is employed in spiking neural networks, which means that more appropriate evaluations can be obtained in applications. 展开更多
关键词 memristor drift diffusion model synaptic brain-inspired computing
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Computational Modeling of the Prefrontal-Cingulate Cortex to Investigate the Role of Coupling Relationships for Balancing Emotion and Cognition 认领 引用 被引量：2
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作者 Jinzhao Wei Licong Li +3 位作者 Jiayi Zhang Erdong Shi Jianli Yang Xiuling Liu 《Neuroscience Bulletin》 SCIE CAS CSCD 2025年第1期33-45,共13页
Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite ... Within the prefrontal-cingulate cortex,abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions,contributing to the development of mental disorders such as depression.Despite this understanding,the neural circuit mechanisms underlying this phenomenon remain elusive.In this study,we present a biophysical computational model encompassing three crucial regions,including the dorsolateral prefrontal cortex,subgenual anterior cingulate cortex,and ventromedial prefrontal cortex.The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes.The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks.Furthermore,our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex,and network functionality was restored through intervention in the dorsolateral prefrontal cortex.This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression. 展开更多
关键词 Prefrontal-cingulate cortex Computational modeling Coupling relationships Depression Emotion and cognition
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Advances and challenges in the mechanics of biological soft tissues:test methods,modeling,and applications 认领 引用 被引量：1
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作者 Wei Kang Lingyan Li +4 位作者 Haoyu Song Yanfei Li Min Zhang Lizhen Wang Yubo Fan 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2025年第9期251-283,共33页
The mechanical properties of biological soft tissues play a critical role in the study of biomechanics and the development of protective measures against human injury.Various testing techniques at different scales hav... The mechanical properties of biological soft tissues play a critical role in the study of biomechanics and the development of protective measures against human injury.Various testing techniques at different scales have been employed to characterize the mechanical behavior of soft tissues,which is essential for developing accurate tissue simulants and numerical models.This review comprehensively explores the mechanical properties of soft tissues,examining experimental methods,mechanical models,numerical simulations,and the progress in materials that mimic the mechanical performance of soft tissues.Finally,it reviews the damage and protection of human tissues under kinetic impacts,anticipating the future construction of soft tissue surrogate targets.The aim is to provide a systematic theoretical foundation and the latest advancements in the field,addressing the design,preparation,and quantitative modeling of biomimetic materials,thereby promoting the in-depth development of soft tissue mechanics and its applications. 展开更多
关键词 Soft tissue mechanics Mechanical behavior Computational modeling Soft tissue simulation material
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A spinal circuit model with an asymmetric cervical-lumbar layout for limb coordination and gait control in quadrupeds 认领 引用 被引量：1
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作者 Qinghua ZHU Fang HAN Qingyun WANG 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2025年第8期1433-1450,I0006-I0009,共18页
In quadrupeds,the cervical and lumbar circuits work together to achieve the speed-dependent gait expression.While most studies have focused on how local lumbar circuits regulate limb coordination and gaits,relatively ... In quadrupeds,the cervical and lumbar circuits work together to achieve the speed-dependent gait expression.While most studies have focused on how local lumbar circuits regulate limb coordination and gaits,relatively few studies are known about cervical circuits and even less about locomotor gaits.We use the previously published models by Danner et al.(DANNER,S.M.,SHEVTSOVA,N.A.,FRIGON,A.,and RYBAK,I.A.Computational modeling of spinal circuits controlling limb coordination and gaits in quadrupeds.e Life,6,e31050(2017))as a basis,and modify it by proposing an asymmetric organization of cervical and lumbar circuits.First,the model reproduces the typical speed-dependent gait expression in mice and more biologically appropriate locomotor parameters,including the gallop gait,locomotor frequencies,and limb coordination of the forelimbs.Then,the model replicates the locomotor features regulated by the M-current.The walk frequency increases with the M-current without affecting the interlimb coordination or gaits.Furthermore,the model reveals the interaction mechanism between the brainstem drive and ionic currents in regulating quadrupedal locomotion.Finally,the model demonstrates the dynamical properties of locomotor gaits.Trot and bound are identified as attractor gaits,walk as a semi-attractor gait,and gallop as a transitional gait,with predictable transitions between these gaits.The model suggests that cervical-lumbar circuits are asymmetrically recruited during quadrupedal locomotion,thereby providing new insights into the neural control of speed-dependent gait expression. 展开更多
关键词 locomotor control cervical-lumbar asymmetrical spinal circuit computational modeling ionic current gait
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Explicit ARL Computational for a Modified EWMA Control Chart in Autocorrelated Statistical Process Control Models 认领 引用 被引量：1
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作者 Yadpirun Supharakonsakun Yupaporn Areepong Korakoch Silpakob 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第10期699-720,共22页
This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving ... This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems. 展开更多
关键词 Statistical process control average run length modified EWMA control chart autocorrelated data SARMA process computational modeling real-time monitoring
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A Unified Framework of the Cloud Computing Service Model 认领 引用 被引量：2
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作者 Wen-Lung Shiau Chao-Ming Hsiao 《Journal of Electronic Science and Technology》 CAS 2013年第2期150-160,共11页
After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtuali... After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application. 展开更多
关键词 Cloud computing service model conceptual framework evolution information system.
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Feasibility of Using Optimal Control Theory and Training-Performance Model to Design Optimal Training Programs for Athletes 认领 引用
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作者 Yi Yang Che-Yu Lin 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第6期2767-2783,共17页
In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training pr... In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training programs.The purpose of the present study is to develop a novel method by the combined use of optimal control theory and a training-performance model for designing optimal training programs,with the hope of helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The training-performance model used in the proposed optimal control framework is a conceptual extension of the Banister impulse-response model that describes the dynamics of performance,training load(served as the control variable),fitness(the overall positive effects on performance),and fatigue(the overall negative effects on performance).The objective functional of the proposed optimal control framework is to maximize the fitness and minimize the fatigue on the competition day with the goal of maximizing the performance on the competition day while minimizing the cumulative training load during the training course.The Forward-Backward Sweep Method is used to solve the proposed optimal control framework to obtain the optimal solutions of performance,training load,fitness,and fatigue.The simulation results show that the performance on the competition day is higher while the cumulative training load during the training course is lower with using optimal control theory than those without,successfully showing the feasibility and benefits of using the proposed optimal control framework to design optimal training programs for helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The present feasibility study lays the foundation of the combined use of optimal control theory and training-performance models to design personalized optimal training programs in real applications in athletic training and sports science for helping athletes achieve the best performances in competitions while prevent overtraining and the risk of overuse injuries. 展开更多
关键词 Banister impulse-response model athletic training and performance coaching education physical fitness sports science computational and mathematical modeling
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AN IMPROVED MODEL FOR COMPUTING SOLUTION DYNAMICS OF NATURAL PRODUCTS WITH 13C NUCLEAR MAGNETIC RELAXATION 认领 引用
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作者 Yan Wu YANG Ang JI Bing Lin HE Institute of Polymer Chemistry,Nankai University,Tianjin 300071Xin YAN Xiao Long XU De Hun WANG Bao Gong QIAN Wuhan Institute of Physics,The Chinese Academy of Sciences,Wuhan 430071 《Chinese Chemical Letters》 SCIE EI CAS 1993年第10期903-906,共4页
The fully anisotropic molecular overall tumbling model with methyl conformation jumps internal rotation among three equivalent sites is proposed,the overall tumbling rotation rates and the methyl internal rotation rat... The fully anisotropic molecular overall tumbling model with methyl conformation jumps internal rotation among three equivalent sites is proposed,the overall tumbling rotation rates and the methyl internal rotation rates of ponicidin are computed with this model from ~C relaxation parameters. 展开更多
关键词 exp RI C NUCLEAR MAGNETIC RELAXATION AN IMPROVED MODEL FOR COMPUTING SOLUTION DYNAMICS OF NATURAL PRODUCTS WITH
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Universal resources for quantum computing 认领 引用 被引量：1
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作者 Dong-Sheng Wang 《Communications in Theoretical Physics》 SCIE CAS CSCD 2023年第12期57-74,共18页
Unravelling the source of quantum computing power has been a major goal in the field of quantum information science.In recent years,the quantum resource theory(QRT)has been established to characterize various quantum ... Unravelling the source of quantum computing power has been a major goal in the field of quantum information science.In recent years,the quantum resource theory(QRT)has been established to characterize various quantum resources,yet their roles in quantum computing tasks still require investigation.The so-called universal quantum computing model(UQCM),e.g.the circuit model,has been the main framework to guide the design of quantum algorithms,creation of real quantum computers etc.In this work,we combine the study of UQCM together with QRT.We find,on one hand,using QRT can provide a resource-theoretic characterization of a UQCM,the relation among models and inspire new ones,and on the other hand,using UQCM offers a framework to apply resources,study relation among these resources and classify them.We develop the theory of universal resources in the setting of UQCM,and find a rich spectrum of UQCMs and the corresponding universal resources.Depending on a hierarchical structure of resource theories,we find models can be classified into families.In this work,we study three natural families of UQCMs in detail:the amplitude family,the quasi-probability family,and the Hamiltonian family.They include some well known models,like the measurement-based model and adiabatic model,and also inspire new models such as the contextual model that we introduce.Each family contains at least a triplet of models,and such a succinct structure of families of UQCMs offers a unifying picture to investigate resources and design models.It also provides a rigorous framework to resolve puzzles,such as the role of entanglement versus interference,and unravel resource-theoretic features of quantum algorithms. 展开更多
关键词 quantum resource computing model quantum algorithm
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