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120 results for “Dynamic Models”
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Review ArticleOpen accessPhrase in the titleDynamic Models of Rigid Memory MechanismsFlorian Ion Tiberiu PetrescuRigid memory mechanisms have played an important role in the history of mankind, contributing greatly to the industrial, economic, social changes in society, thus leading to a real evolution of mankind. Used in automated tissue wars, in cars as distribution mechanisms, automated machines, mechanical transmissions, robots and mechatronics, precision devices and medical devices, these mechanisms have been real support for … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 4 · 22 Nov 2018 · 7,257 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDynamic Models for Rigid Memory MechanismsRelly Victoria Virgil PetrescuThe paper presents a dynamic model that works with variable internal damping, applicable directly to rigid memory mechanisms. If the problem of elasticity is generally solved, the problem of system damping is not clear and well-established. It is usually considered a constant "c" value for the internal damping of the system and sometimes the same value c and for the … …Journal of Mechatronics and Robotics, Vol. 3, Issue 1 · 6 May 2019 · 5,981 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDeveloping and Testing Dynamic Models for HVAC Systems Using System Identification ApproachNabil Nassif, Jasmine Buford, Taher M. Abu-LebdehThis paper proposes integrated modeling and optimization methods for a chilled water HVAC system using a system identification approach. Two multiple input-single output models are developed to find the supply air temperature and fan power of the investigated chilled water air handling unit AHU. To test the proposed models, actual data are collected from existing HVAC systems. Different fan and … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 15 Mar 2017 · 7,710 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleThe Possibility of Cyclical Behavior in a Class of Dynamic ModelsAnjan MukherjiThe study investigates conditions under which endogenous cyclic behavior may be observed within the context of Predator-Prey (Lotka-Volterra) Models. The analysis also establishes conditions under which such behavior is non-existent and hence establishes conditions for global convergence to the interior equilibrium, whenever it exists. The results are then applied to two diverse sets of economic exercises and shows how the … …American Journal of Applied Sciences, Vol. 2, Issue 13 · 9 Dec 2005 · 7,600 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComputational Techniques for Stability Analysis of a Class of Dynamic Economic ModelsGeorge E. Halkos, Kyriaki D. TsilikaModern microeconomics and macroeconomics study dynamic phenomena. Dynamics could predict future states of an economy based on its structural characteristics. Dynamic models in discrete time discrete state economic systems may take the form of one single linear difference equation or a system of linear difference equations. In this study we use Xcas and Mathematica as software tools in order to … …American Journal of Applied Sciences, Vol. 9, Issue 12 · 12 Dec 2012 · 7,379 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIsolated Malay Digit Recognition Using Pattern Recognition Fusion of Dynamic Time Warping and Hidden Markov ModelsS.A.R. Al-Haddad, S.A. Samad, A. Hussain, K.A. IshakThis paper is presents a pattern recognition fusion method for isolated Malay digit recognition using Dynamic Time Warping (DTW) and Hidden Markov Model (HMM). The aim of the project is to increase the accuracy percentage of Malay speech recognition. This study proposes an algorithm for pattern recognition fusion of the recognition models. The endpoint detection, framing, normalization, Mel Frequency Cepstral … …American Journal of Applied Sciences, Vol. 5, Issue 6 · 30 Jun 2008 · 7,049 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleParsimonious Var Models For Air Pollution Dynamic AnalysisFontanella lara, Granturco mariagraziaWe discuss a framework to obtain temporal predictions for an evolving spatial field regularly sampled in time at arbitrary spatial locations. Difficulties caused by large data sets and the modelling of complicated spatio-temporal interactions limit the effectiveness of traditional space-time statistical models. In this study, we propose the use of a flexible approach to deal with large and small time-scale … …Journal of Mathematics and Statistics, Vol. 1, Issue 4 · 31 Dec 2005 · 6,181 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 413 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnxiety-Focused Classification Using Smartphone-Based Gait Analysis and Deep Learning ModelsMinchan Kang, Gou-Sung Degbey, Hyunhwa Lee et al.Mood disorders, such as anxiety, significantly impact individual well-being and present challenges to healthcare systems globally. Traditional screening methods, including self-administered symptom questionnaires, provide valuable insights into symptoms but may miss dynamic fluctuations. This study explores the potential of smartphone inertial sensors and deep learning models for anxiety risk classification. Using gait data from 36 participants, collected via smartphone accelerometers … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 821 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDFCite