Journal articles on the topic 'Multi level linear modelling'
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Baky, Ibrahim A. "Solving multi-level multi-objective linear programming problems through fuzzy goal programming approach." Applied Mathematical Modelling 34, no. 9 (September 2010): 2377–87. http://dx.doi.org/10.1016/j.apm.2009.11.004.
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Baky, Ibrahim A. "Interactive TOPSIS algorithms for solving multi-level non-linear multi-objective decision-making problems." Applied Mathematical Modelling 38, no. 4 (February 2014): 1417–33. http://dx.doi.org/10.1016/j.apm.2013.08.016.
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Mole, Melissa A., Mark A. Davidson, Ian L. Turner, Kristen D. Splinter, Ian D. Goodwin, and Andrew D. Short. "MODELLING MULTI-DECADAL SHORELINE VARIABILITY AND EVOLUTION." Coastal Engineering Proceedings 1, no. 33 (December 14, 2012): 98. http://dx.doi.org/10.9753/icce.v33.sediment.98.
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A robust and practical methodology for predicting future shoreline behaviour along sandy coastlines would be valuable to a broad range of coastal engineering applications. Present approaches for predicting shoreline evolution range from simple linear trend models, which cannot predict observed complex behaviour, to coupled hydrodynamic / sediment transport models, with seasonal to multi-year forecasting generally beyond present model capabilities. In this work a simple empirical shoreline variability model, ShoreFor (Shoreline Forecast), is investigated using a multi-decadal dataset to assess model performance at daily to decadal timescales. Model performance is assessed at five alongshore locations within an embayed study site that experience varying exposure to the offshore wave climate due to prominent adjacent headlands and display alongshore variable behaviour. To determine model sensitivity to input wave conditions, both the measured offshore and transformed (modelled) nearshore wave data are used and results compared. Strengths and limitations of the ShoreFor model are identified and discussed, along with ongoing model development and planned application of this modelling technique for shoreline forecasting using future water level and wave climate scenarios.
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ABO-SINNA, MAHMOUD A., and AZZA H. AMER. "TOPSIS Approach for Solving Bi-Level Non-Linear Fractional MODM Problems." JOURNAL OF ADVANCES IN MATHEMATICS 13, no. 4 (February 9, 2018): 7353–70. http://dx.doi.org/10.24297/jam.v13i4.6243.
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TOPSIS (technique for order preference similarity to ideal solution) is considered one of the known classical multiple criteria decision making (MCDM) methods to solve bi-level non-linear fractional multi-objective decision making (BL-NFMODM) problems, and in which the objective function at each level is considered nonlinear and maximization type fractional functions. The proposed approach presents the basic terminology of TOPSIS approach and the construction of membership function for the upper level decision variable vectors, the membership functions of the distance functions from the positive ideal solution (PIS) and of the distance functions from the negative ideal solution (NIS). Thereafter a fuzzy goal programming model is adopted to obtain compromise optimal solution of BL-NFMODM problems. The proposed approach avoids the decision deadlock situations in decision making process and possibility of rejecting the solution again and again by lower level decision makers. The presented TOPSIS technique for BL-NFMODM problems is a new fuzzy extension form of TOPSIS approach suggested by Baky and Abo-Sinna (2013) (Applied Mathematical Modelling, 37, 1004-1015, 2013) which dealt with bi -level multi-objective decision making (BL-MODM) problems. Also, an algorithm is presented of the new fuzzy TOPSIS approach for solving BL-NFMODM problems. Finally, an illustrative numerical example is given to demonstrate the approach.
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Kratica, Jozef, Djordje Dugošija, and Aleksandar Savić. "A new mixed integer linear programming model for the multi level uncapacitated facility location problem." Applied Mathematical Modelling 38, no. 7-8 (April 2014): 2118–29. http://dx.doi.org/10.1016/j.apm.2013.10.012.
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Hanewald, Katja, Han Li, and Adam W. Shao. "Modelling multi-state health transitions in China: a generalised linear model with time trends." Annals of Actuarial Science 13, no. 1 (July 2, 2018): 145–65. http://dx.doi.org/10.1017/s1748499518000167.
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AbstractRapid population ageing in China has urged the need to understand health transitions of older Chinese to assist the development of social security programmes and financial products aimed at funding long-term care. In this paper, we develop a new flexible approach to modelling health transitions in a multi-state Markov model that allows for age effects, time trends and age-time interactions. The model is implemented in the generalised linear modelling framework. We apply the model to evaluate health transitions of Chinese elderly using individual-level panel data from the Chinese Longitudinal Healthy Longevity Survey for the period 1998–2012. Our results confirm that time trends and age–time interactions are important factors explaining health transitions in addition to the more commonly used age effects. We document that differences in disability and mortality rates continue to persist between urban and rural older Chinese. We also compute life expectancies and healthy life expectancies based on the proposed model as inputs for the development of aged care and financial services for older Chinese.
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Eyarkai Nambi, Vijayaram, Kuladaisamy Thangavel, Annamalai Manickavasagan, and Sultan Shahir. "Comprehensive ripeness-index for prediction of ripening level in mangoes by multivariate modelling of ripening behaviour." International Agrophysics 31, no. 1 (January 1, 2017): 35–44. http://dx.doi.org/10.1515/intag-2016-0025.
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Abstract Prediction of ripeness level in climacteric fruits is essential for post-harvest handling. An index capable of predicting ripening level with minimum inputs would be highly beneficial to the handlers, processors and researchers in fruit industry. A study was conducted with Indian mango cultivars to develop a ripeness index and associated model. Changes in physicochemical, colour and textural properties were measured throughout the ripening period and the period was classified into five stages (unripe, early ripe, partially ripe, ripe and over ripe). Multivariate regression techniques like partial least square regression, principal component regression and multi linear regression were compared and evaluated for its prediction. Multi linear regression model with 12 parameters was found more suitable in ripening prediction. Scientific variable reduction method was adopted to simplify the developed model. Better prediction was achieved with either 2 or 3 variables (total soluble solids, colour and acidity). Cross validation was done to increase the robustness and it was found that proposed ripening index was more effective in prediction of ripening stages. Three-variable model would be suitable for commercial applications where reasonable accuracies are sufficient. However, 12-variable model can be used to obtain more precise results in research and development applications.
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Niekamp, Rainer, Damijan Markovic, Adnan Ibrahimbegovic, Hermann G. Matthies, and Robert L. Taylor. "Multi‐scale modelling of heterogeneous structures with inelastic constitutive behavior." Engineering Computations 26, no. 1/2 (January 2, 2009): 6–28. http://dx.doi.org/10.1108/02644400910924780.
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PurposeThe purpose of this paper is to consider the computational tools for solving a strongly coupled multi‐scale problem in the context of inelastic structural mechanics.Design/methodology/approachIn trying to maintain the highest level of generality, the finite element method is employed for representing the microstructure at this fine scale and computing the solution. The main focus of this work is the implementation procedure which crucially relies on a novel software product developed by the first author in terms of component template library (CTL).FindingsThe paper confirms that one can produce very powerful computational tools by software coupling technology described herein, which allows the class of complex problems one can successfully tackle nowadays to be extended significantly.Originality/valueThis paper elaborates upon a new multi‐scale solution strategy suitable for highly non‐linear inelastic problems.
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Radics, K., J. Bartholy, and R. Pongrácz. "Modelling studies of wind field on urban environment." Atmospheric Chemistry and Physics Discussions 2, no. 6 (November 11, 2002): 1979–2001. http://dx.doi.org/10.5194/acpd-2-1979-2002.
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Abstract. Increasing load of air pollution in urban environment emphasises the need for detailed evaluation of wind characteristics that significantly affect the air quality of urban areas, especially, in large agglomerations. This paper includes analysis of urban wind climatology and estimation of wind profiles based on measurements of the new urban climate station located at the Eötvös University, observations of the meteorological station network of the Budapest agglomeration area, and multi-level wind measurements near Hegyhátsál. Furthermore, wind field modelling (using the WAsP linear spectral wind flow model) is presented over selected representative complex areas that demonstrates strong dependence between wind, height, topography, and roughness.
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Mandal, Sumit, Simon Annaheim, Martin Camenzind, and René M. Rossi. "Characterization and modelling of thermal protective performance of fabrics under different levels of radiant-heat exposures." Journal of Industrial Textiles 48, no. 7 (February 28, 2018): 1184–205. http://dx.doi.org/10.1177/1528083718760801.
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The investigation of thermal protective performance of fabrics is highly relevant in order to procure and further develop the firefighters' protective clothing. Therefore, this paper aims at investigating the thermal protective performance of fabrics used in firefighters' clothing under different levels of radiant-heat exposures. For this, properties of a set of thermal protective single- and multi-layered fabrics were measured, and these fabrics were tested under radiant-heat exposures using the Method B of ISO 6942:2002 standard. During the testing, fabrics were exposed to low (10 kW/m2), medium (40 kW/m2), and high (80 kW/m2) intensity radiant-heat exposures; and the heat transfer level (i.e., time required to increase the skin temperature of a wearer/firefighter by certain degrees) through these fabrics were calculated to measure their thermal protective performance. The effects of fabric parameters, structures, properties, and radiant-heat intensities on the protective performance were characterized, and fabric properties that significantly affected the protective performance were statistically identified at different level of radiant-heat exposures. It has been found that weight, thickness, thermal resistance, and evaporative resistance can positively affect the protective performance. Also, the significant fabric properties affecting the protective performance vary for single- and multi-layered fabrics. By using these significant properties, the protective performance of single- and multi-layered fabrics were also separately predicted by mathematical models, i.e., multiple linear regression models and multiple logarithmic regression models. As per the findings of this study, multiple linear regression models can effectively be used to predict the thermal protective performance of fabrics. This study will lead towards building a better understanding and prediction of thermal protective performance of fabrics under radiant-heat exposures.
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Dzemydiene, D. "CONCEPTUAL ARCHITECTURE FOR DYNAMIC DOMAIN REPRESENTATION." Mathematical Modelling and Analysis 5, no. 1 (December 15, 2000): 55–66. http://dx.doi.org/10.3846/13926292.2000.9637128.
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This paper considers the representation of knowledge content of a dynamic application domain. The multi‐layered conceptual architecture assembles the models of knowledge representation on a higher level including conceptual models of information structures, dynamic process analysis, and problem solving tasks. The model represents behavioural analysis of the target system based on a piecewise‐linear aggregate approach.
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Giustolisi, O., and D. A. Savic. "Advances in data-driven analyses and modelling using EPR-MOGA." Journal of Hydroinformatics 11, no. 3-4 (July 1, 2009): 225–36. http://dx.doi.org/10.2166/hydro.2009.017.
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Evolutionary Polynomial Regression (EPR) is a recently developed hybrid regression method that combines the best features of conventional numerical regression techniques with the genetic programming/symbolic regression technique. The original version of EPR works with formulae based on true or pseudo-polynomial expressions using a single-objective genetic algorithm. Therefore, to obtain a set of formulae with a variable number of pseudo-polynomial coefficients, the sequential search is performed in the formulae space. This article presents an improved EPR strategy that uses a multi-objective genetic algorithm instead. We demonstrate that multi-objective approach is a more feasible instrument for data analysis and model selection. Moreover, we show that EPR can also allow for simple uncertainty analysis (since it returns polynomial structures that are linear with respect to the estimated coefficients). The methodology is tested and the results are reported in a case study relating groundwater level predictions to total monthly rainfall.
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Uzunova, S., L. Minchev, and I. Uzunov. "Modelling of Aromatic Sulfur Compounds Adsorption from Hydrocarbon Fuels by Biochar Based Adsorbent." IOP Conference Series: Earth and Environmental Science 987, no. 1 (February 1, 2022): 012002. http://dx.doi.org/10.1088/1755-1315/987/1/012002.
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Abstract In this work model fuel containing thiophene, benzothiophene and dibenzothiophene in different concentration combinations were treated with biochar. The quantity of total sulfur into the stock mixed solutions was below 1000 ppm. The adsorbent was prepared by pyrolysis of rice husks. The investigation aimed to use the method of multiple linear regression to derive a mathematical model, describing the adsorption of the three aromatic sulfur compounds from single and multi-component solutions of model fuel. The model describing the adsorption from multi-component solutions, based on the experimental results, has a correlation coefficient of 0.961. It reveals that the degree of desulfurization does not depend on the concentration of thiophene, but only on the concentrations of benzothiophene and dibenzothiophene in the fuel. The model can be used to predict the level of the adsorptive purification of the fuel if the content of benzothiophene and dibenzothiophene in it is known.
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Bhattacharyya, Mainak, David Dureisseix, and Beatrice Faverjon. "Numerical homogenisation based on asymptotic theory and model reduction for coupled elastic-viscoplastic damage." International Journal of Damage Mechanics 29, no. 9 (June 11, 2020): 1416–44. http://dx.doi.org/10.1177/1056789520930785.
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This article deals with damage computation of heterogeneous structures containing locally periodic micro-structures. Such heterogeneous structure is extremely expensive to simulate using classical finite element methods, as the level of discretisation required to capture the micro-structural effects is too fine. The simulation time becomes even higher when dealing with highly non-linear material behaviour, e.g. damage, plasticity and such others. Therefore, a multi-scale strategy is proposed here that facilitates the simulation of non-linear heterogeneous material behaviour in a manner that is computationally feasible. Based on the asymptotic homogenisation theory, this multi-scale technique explores the micro–macro behaviour for elasto-(visco)plasticity coupled with damage. The theory inherently segregates the heterogeneous continua into a macroscopic homogeneous structure and an underlying heterogeneous microscopic periodic unit cell. Several heterogeneous structures have been simulated using the multi-scale method along with a one-dimensional verification with respect to a reference solution. Additionally, a reduced order modelling is used to prevent large memory requirement for storing micro-structural quantities of interest.
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Questa, Harry, Mahdi Mohammadpour, Stephanos Theodossiades, Colin P. Garner, Stephen R. Bewsher, and Günter Offner. "Tribodynamic Modelling of High-Speed Rolling Element Bearings in Flexible Multi-Body Environments." Machines 11, no. 1 (January 11, 2023): 93. http://dx.doi.org/10.3390/machines11010093.
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This study presents a new flexible dynamic model for drive systems comprising lubricated bearings operating under conditions representative of electrified vehicle powertrains. The multi-physics approach importantly accounts for the tribological phenomena at the roller–race conjunction and models their effect on shaft-bearing system dynamics. This is achieved by embedding a non-linear lubricated bearing model within a flexible system level model; this is something which has not, to the authors’ knowledge, been reported on hitherto. The elastohydrodynamic (EHL) film is shown to increase contact deflection, leading to increased contact forces and total bearing stiffness as rotational speeds increase. Results show that for a 68 Nm hub motor operating up to 21,000 rpm, the input bearing EHL film reaches a thickness of 4.15 µm. The lubricant entrainment increases the roller–race contact deflection, causing the contact stiffness to increase non-linearly with speed. The contribution of the lubricant film leads to a 16.6% greater bearing stiffness at 21,000 rpm when compared to conventional dry-bearing modelling methods used in current multi-body dynamic software. This new methodology leads to more accurate dynamic response of high-speed systems necessary for the next generation of electrified vehicles.
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Giustolisi, Orazio. "Using a multi-objective genetic algorithm for SVM construction." Journal of Hydroinformatics 8, no. 2 (March 1, 2006): 125–39. http://dx.doi.org/10.2166/hydro.2006.016b.
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Support Vector Machines are kernel machines useful for classification and regression problems. In this paper, they are used for non-linear regression of environmental data. From a structural point of view, Support Vector Machines are particular Artificial Neural Networks and their training paradigm has some positive implications. In fact, the original training approach is useful to overcome the curse of dimensionality and too strict assumptions on statistics of the errors in data. Support Vector Machines and Radial Basis Function Regularised Networks are presented within a common structural framework for non-linear regression in order to emphasise the training strategy for support vector machines and to better explain the multi-objective approach in support vector machines' construction. A support vector machine's performance depends on the kernel parameter, input selection and ε-tube optimal dimension. These will be used as decision variables for the evolutionary strategy based on a Genetic Algorithm, which exhibits the number of support vectors, for the capacity of machine, and the fitness to a validation subset, for the model accuracy in mapping the underlying physical phenomena, as objective functions. The strategy is tested on a case study dealing with groundwater modelling, based on time series (past measured rainfalls and levels) for level predictions at variable time horizons.
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Nguyen, Binh-Minh, Hung Van Nguyen, Minh Ta-Cao, and Michihiro Kawanishi. "Longitudinal Modelling and Control of In-Wheel-Motor Electric Vehicles as Multi-Agent Systems." Energies 13, no. 20 (October 18, 2020): 5437. http://dx.doi.org/10.3390/en13205437.
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This paper deals with longitudinal motion control of electric vehicles (EVs) driven by in-wheel-motors (IWMs). It shows that the IWM-EV is fundamentally a multi-agent system with physical interaction. Three ways to model the IWM-EV are proposed, and each is applicable to certain control objectives. Firstly, a nonlinear model with hierarchical structure is established, and it can be used for passivity-based motion control. Secondly, a linearized model with rank-1 interconnection matrix is presented for stability analysis. Thirdly, a time-varying state-space model is proposed for optimal control using linear quadratic regulator (LQR). The proposed modellings contribute the new understanding of IWM-EV dynamics from the view point of multi-agent-system theory. By choosing the suitable control theory for each model, the complexity level of system design is maintained constant, no matter what the number of IWMs installed to the vehicle body. The effectiveness of three models and their design approaches are discussed by several examples with Matlab/Carsim co-simulator.
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Burton, Paul, Lyle Gurrin, and Peter Sly. "Extending the simple linear regression model to account for correlated responses: An introduction to generalized estimating equations and multi-level mixed modelling." Statistics in Medicine 17, no. 11 (June 15, 1998): 1261–91. http://dx.doi.org/10.1002/(sici)1097-0258(19980615)17:11<1261::aid-sim846>3.0.co;2-z.
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Barbié, L., I. Ramière, and F. Lebon. "Strategies involving the local defect correction multi-level refinement method for solving three-dimensional linear elastic problems." Computers & Structures 130 (January 2014): 73–90. http://dx.doi.org/10.1016/j.compstruc.2013.10.008.
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Chaudhari, Dvij. "Modelling Road Accident using Poisson regression Models." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4635–40. http://dx.doi.org/10.22214/ijraset.2021.35827.
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The objective of this research is to evaluate the safety of multi-lane urban roads in India. In this paper, a generalised linear modelling technique is applied for the analysis of the Indian Highway's road accident. The features of road, speed, and traffic data are analysed in Surat on four-lane urban roads. A novel approach to the model of accident prediction for an urban highway is being proposed to include daily average travel (ADT) and average spot speed (AS). The model was developed as a reliant variable and significant variables such as chain width, intersection no, ADT, AS, as separate variables for accidents per kilometre.. The results of the model provide a better assessment of accidents on a multilateral urban road. Because road accidents are different, statistical models do not adequately capture the characteristics of each section. As a result, the results of Poisson regression were the opposite of these variables. There was also no statistically significant type of traffic control. Significant statistically at level 0.05. Accident locations were assessed by correlating the severity of the accident with different attributes. This investigation will contribute to improving urban road safety.
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Hryhoriev, Hennadiy. "Path Dependence in Sovereign Debt Modelling: System Dynamics Approach." Scientific Papers NaUKMA. Economics 6, no. 1 (July 30, 2021): 52–58. http://dx.doi.org/10.18523/2519-4739.2021.6.1.52-58.
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The article offers a system dynamic modelling of sovereign debt using the path dependence concept. Using simulation modelling we are trying to find a fixed point in a motion of national sovereign debt towards its equilibrium and to change the existing mental model perception towards sovereign debt by changing the structure of the system.The research reveals the idea of the “debt snowball concept” using recursive dynamic approach. The dynamic linear and nonlinear recursive models of Ukrainian sovereign debt with the appropriate multi – order recursive equations are constructed.The fixed point as an equilibrium value for a country’s sovereign debt stock to GDP ratio with a linear dependence has been built. Finding the initial point for resolving sovereign debt issue is especially actual for national economy under strong fiscal pressure caused by COVID-19 and wartime on the East of the country. For this purpose, the sovereign debt cyclical behaviour was also reproduced using phase plot graphic.The fixed point as an equilibrium value for a country’s sovereign debt stock to GDP ratio with a nonlinear dependence was determined. The main purpose of this part of the analysis was to show the more complicated oscillated behaviour of the system and the multiplicity of possible equilibrium points.The stock and flows SD modelling and simulation analysis of sovereign debt in Ukrainian economy allows to make the conclusion of the inevitability of the sovereign debt existence even on the stable level and with the balanced national budget. JEL classіfіcatіon: E60, H63, H68
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Bernales, A. M., J. A. Antolihao, C. Samonte, F. Campomanes, R. J. Rojas, A. M. dela Serna, and J. Silapan. "MODELLING THE RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND LANDSCAPE PATTERNS OF LAND USE LAND COVER CLASSIFICATION USING MULTI LINEAR REGRESSION MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 851–56. http://dx.doi.org/10.5194/isprs-archives-xli-b8-851-2016.
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The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric “Effective mesh size” was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.
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Bernales, A. M., J. A. Antolihao, C. Samonte, F. Campomanes, R. J. Rojas, A. M. dela Serna, and J. Silapan. "MODELLING THE RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND LANDSCAPE PATTERNS OF LAND USE LAND COVER CLASSIFICATION USING MULTI LINEAR REGRESSION MODELS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 23, 2016): 851–56. http://dx.doi.org/10.5194/isprsarchives-xli-b8-851-2016.
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The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric “Effective mesh size” was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.
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Antonakis, Aristeidis, Mudassir Lone, and Alastair Cooke. "Neural network based dynamic model and gust identification system for the Jetstream G-NFLA." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 6 (May 18, 2016): 1138–53. http://dx.doi.org/10.1177/0954410016648997.
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Artificial neural networks are an established technique for constructing non-linear models of multi-input-multi-output systems based on sets of observations. In terms of aerospace vehicle modelling, however, these are currently restricted to either unmanned applications or simulations, despite the fact that large amounts of flight data are typically recorded and kept for reasons of safety and maintenance. In this paper, a methodology for constructing practical models of aerospace vehicles based on available flight data recordings from the vehicles’ operational use is proposed and applied on the Jetstream G-NFLA aircraft. This includes a data analysis procedure to assess the suitability of the available flight databases and a neural network based approach for modelling. In this context, a database of recorded landings of the Jetstream G-NFLA, normally kept as part of a routine maintenance procedure, is used to form training datasets for two separate applications. A neural network based longitudinal dynamic model and gust identification system are constructed and tested against real flight data. Results indicate that in both cases, the resulting models’ predictions achieve a level of accuracy that allows them to be used as a basis for practical real-world applications.
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Senthil Kumar, Srinivasan, Moranahalli Ponnusamy Sudeshkumar, Chakaravarthy Ezilarasan, Sivaprakasam Palani, and Jayaseelan Veerasundaram. "Modelling and Simulation of Machining Attributes in dry Turning of Aircraft Materials Nimonic C263 using CBN." Manufacturing Review 8 (2021): 30. http://dx.doi.org/10.1051/mfreview/2021030.
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In the current scenario, machinability of the super alloys is of greater importance in an aircraft turbine engine and land-based turbine applications owing to its superior properties. However, the machinability of these alloys is found to be poor owing to its inherent properties. Hence, a predictive model has been developed based on DEFORM 3D to forecast the machining attributes such as cutting force and insert's cutting edge temperature in turning of Nimonic C263 super alloy. The dry turning trials on Nimonic C263 material were carried out based on L27 orthogonal array using CBN insert. Linear regression models were developed to predict the machining attributes. Further, multi response optimization was carried out based on desirability approach for optimizing the machining attributes. The validation test was carried out for optimal parameter values such as cutting speed: 117 m/min, feed rate: 0.055 mm/rev and depth of cut: 0.25 mm. The minimum cutting force of 304N and insert's cutting edge temperature of 468 °C were obtained at optimum level of parameters.The predicted values by FEA and linear regression model were compared with experimental results and found to be closer with minimum percentage error.The minimum percentage error obtained by FEA and linear regression model for the machining attributes (cutting force, temperature) as compared with experimental values were (0.32%, 0.23%) and (2.34%, 1.63%) respectively.
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Dai, Xiaokun, Yang Song, and Taicheng Yang. "Modelling and region stability analysis of wind turbines with battery energy storage system based on switched system with multi-equilibriums." Transactions of the Institute of Measurement and Control 41, no. 6 (March 7, 2019): 1519–27. http://dx.doi.org/10.1177/0142331219832161.
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This paper deals with the modelling and control for wind turbine combined with a battery energy storage system (WT/BESS). A proportional-integral (PI) controller of pitch angle is applied to adjust the output power of WT, and a method for battery scheduling is presented for maintaining the state of charging (SOC) of BESS. When the battery level is below the lower limit, we increase the expected output power of wind turbine through raising the operation point to charge the battery. Considering the effect of charging/discharging, a switched linear system model with two equilibriums is presented firstly for such WT/BESS system. The region stability is analyzed and an approach for estimating the corresponding stable region is also given. The effectiveness of the proposed results is demonstrated by a numerical example.
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Niedoba, Tomasz, Agnieszka Surowiak, and Paulina Pięta. "A multidimensional analysis and modelling of flotation process for selected Polish lithological copper ore types." E3S Web of Conferences 18 (2017): 01005. http://dx.doi.org/10.1051/e3sconf/20171801005.
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The flotation of copper ore is a complex technological process that depends on many parameters. Therefore, it is necessary to take into account the complexity of this phenomenon by choosing a multidimensional data analysis. The paper presents the results of modelling and analysis of beneficiation process of sandstone copper ore. Considering the implementation of multidimensional statistical methods it was necessary to carry out a multi-level experiment, which included 4 parameters (size fraction, collector type and dosage, flotation time). The main aim of the paper was the preparation of flotation process models for the recovery and the content of the metal in products. A MANOVA was implemented to explore the relationship between dependent (β, ϑ, ε, η) and independent (d, t, cd, ct) variables. The design of models was based on linear and nonlinear regression. The results of the variation analysis indicated the high significance of all parameters for the process. The average degree of matching of linear models to experimental data was set at 49% and 33% for copper content in the concentrate and tailings and 47% for the recovery of copper minerals in the both. The results confirms the complexity and stochasticity of the Polish copper ore flotation.
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Parker, Albert. "Minimum 60 years of recording are needed to compute the sea level rate of rise in the Western South Pacific." Nonlinear Engineering 3, no. 1 (March 1, 2014): 1–10. http://dx.doi.org/10.1515/nleng-2013-0011.
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Abstract Sea levels generally oscillate with multi-decadal periodicities worldwide with up to the quasi-60 years detected in many tide gauges. Nevertheless, the most part of the literature on sea levels computes apparent rates of rise of sea levels much larger than the legitimate by using short time windows in selected locations only covering part of a valley-to-peak of this multi-decadal oscillation. It is shown in this paper that along the Pacific coast of Australia the sea levels oscillate with a frequency close to the Southern Ocean Index (SOI) oscillation of 19 years and a lower frequency of about 60 years. The rates of rise of sea levels computed by linear fitting of the data recorded since the early 1990s in selected locations of the Australian Pacific coastline and in the tropical Pacific islands are from a valley of the peak and valley oscillations and are much higher than the legitimate long term values.
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Ielina, Tetiana, Liudmyla Halavska, Daiva Mikucioniene, Rimvydas Milasius, Svitlana Bobrova, and Oksana Dmytryk. "Development of 3D Models of Knits from Multi-Filament Ultra-Strong Yarns for Theoretical Modelling of Air Permeability." Materials 14, no. 13 (June 23, 2021): 3489. http://dx.doi.org/10.3390/ma14133489.
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The work is devoted to the study of the geometric parameters of a knitted loop. It has been found that the optimal model is a loop model detailed at the yarn level, which considers the change in the cross-sectional shape and sets the properties of the porous material in accordance with the internal porosity of the yarn. A mathematical description of the coordinates of the characteristic points of the loop and an algorithm for calculating the coordinates of the control vertices of the second order spline, which determine the configuration of the yarn axes in the loop, are presented in this work. To create 3D models, Autodesk AutoCAD software and Structura 3D software, developed in the AutoLisp programming language, were used. The simulation of the air flow process was carried out in the Autodesk CFD Simulation environment. For the experimental investigation, plane knits from 44 tex × 3 linear density ultra-high molecular weight polyethylene yarns were produced, and their air permeability was tested according to Standard DSTU ISO 9237:2003. The results obtained during the laboratory experiment and simulation differed by less than 5%.
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Bao, Yang, and Jiming Song. "Analysis of electromagnetic non-destructive evaluation modelling using Stratton-Chu formulation-based fast algorithm." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2182 (September 14, 2020): 20190583. http://dx.doi.org/10.1098/rsta.2019.0583.
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The eddy current non-destructive evaluation (NDE) modelling using Stratton-Chu formulation-based fast algorithm is analysed. Stratton-Chu formulations, which have no low frequency breakdown issue, are selected for modelling electromagnetic NDE problems with low frequency and high conductivity approximations. As the main contribution of this article, the robustness and efficiency of the approximations, which result in big savings in both memory and CPU time, are validated and analysed using examples from practical EC testing. The boundary element method (BEM) is used to discretize the integral equations into a linear system of equations: the first order Rao-Wilton-Glisson (RWG) vector basis functions with the flat triangle meshes of the object and pulse basis functions are selected to expand the equivalent surface currents and the normal component of magnetic fields, respectively. Then the multilevel adaptive cross approximation (MLACA) algorithm is applied to accelerate the iterative solution process. The performance and efficiency of adaptively applying a multi-stage (level) algorithm based on the criteria concluded for the operators are shown. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
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Löwner, M. O., and Y. Ghassoun. "THE INFLUENCE OF LEVELS OF DETAIL (LOD0-2) AND BUFFER SIZES ON PARAMETER EFFECTIVENESS FOR FINE DUST DISTRIBUTION MODELLING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W6 (September 12, 2018): 41–48. http://dx.doi.org/10.5194/isprs-annals-iv-4-w6-41-2018.
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<p><strong>Abstract.</strong> Building models represented in CityGML Level of Detail 0 to 2 were used to calculate urban morphological parameters to test their effectiveness of correlation with measured total number concentration of fine dust in Berlin. Land use regression modelling as an alternative to physical based models explains the distribution of urban fine and ultrafine particles applying a multi linear regression model. Descriptive parameters are identified by high correlations with measured fine dust values. Here, different height information and geometry representations from LoD0-LoD2 were used to calculate six parameters associated with the ventilation and advection capacity of an urban environment (‘averaged heights of buildings’, ‘height-width ratio’, ‘porosity’, ‘frontal area index’, and ‘building surfaces’ for wall surfaces and for wall and roof surfaces). Parameters were correlated with measurements of the total number concentration of fine dust in the city of Berlin. Initial results show ambivalent correlations for both, different buffer sizes and implementation of the parameters with building representations in different levels of detail.</p>
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Harvey, Natalie J., Nathan Huntley, Helen F. Dacre, Michael Goldstein, David Thomson, and Helen Webster. "Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters." Natural Hazards and Earth System Sciences 18, no. 1 (January 4, 2018): 41–63. http://dx.doi.org/10.5194/nhess-18-41-2018.
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Abstract. Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational ensemble of simulations. The use of an emulator also identifies the input and internal parameters that do not contribute significantly to simulator uncertainty. Finally, the analysis highlights that the faster, less accurate, configuration of NAME can, on its own, provide useful information for the problem of predicting average column load over large areas.
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Kaewunruen and Tang. "Idealisations of Dynamic Modelling for Railway Ballast in Flood Conditions." Applied Sciences 9, no. 9 (April 29, 2019): 1785. http://dx.doi.org/10.3390/app9091785.
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As the main component of a ballasted railway system, railway ballast is frequently used by the railway industry to enhance constructability and practicality. Numerous studies into train–track interactions focused on ballast modelling and idealisation in completely dry environments, but recent studies have found that, in extreme weather such as floods, water can clog natural ballast beds and change the initial state of their properties. Ballast models used in multi-body simulations have been mostly developed based on the instrumented impact hammering method considering the ballast as a spring/dashpot. The single degree of freedom (SDOF) idealization for ballast enables a non-destructive field testing technique for monitoring of railway components in practice. In this study, the suitability of the idealization of ballast for dynamic characteristics has been evaluated. A series of experiments have been performed with a variety of ballast conditions in flooding levels from 0 to 40 cm, with a frequency range of 0–500 Hz. The results clearly show that the increase in the flood level will result in increasing dynamic damping of more than 50% of dry natural ballast whilst reducing its stiffness and natural frequency. The novel insights are of great significance for exploring the non-linear dynamic traits of ballast in extreme environments, which can be integrated into the coupled train–track analysis that can better express more realistically the dynamic train–track interaction and load transfer mechanism of flooded railway tracks.
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Axelsson, O., V. A. Barker, M. Neytcheva, and B. Polman. "SOLVING THE STOKES PROBLEM ON A MASSIVELY PARALLEL COMPUTER." Mathematical Modelling and Analysis 6, no. 1 (June 30, 2001): 7–27. http://dx.doi.org/10.3846/13926292.2001.9637141.
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We describe a numerical procedure for solving the stationary two-dimensional Stokes problem based on piecewise linear finite element approximations for both velocity and pressure, a regularization technique for stability, and a defect‐correction technique for improving accuracy. Eliminating the velocity unknowns from the algebraic system yields a symmetric positive semidefinite system for pressure which is solved by an inner‐outer iteration. The outer iterations consist of the unpreconditioned conjugate gradient method. The inner iterations, each of which corresponds to solving an elliptic boundary value problem for each velocity component, are solved by the conjugate gradient method with a preconditioning based on the algebraic multi‐level iteration (AMLI) technique. The velocity is found from the computed pressure. The method is optimal in the sense that the computational work is proportional to the number of unknowns. Further, it is designed to exploit a massively parallel computer with distributed memory architecture. Numerical experiments on a Cray T3E computer illustrate the parallel performance of the method.
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Ferragina, Emanuele, Mark Tomlinson, and Robert Walker. "Poverty and Participation in Twenty-First Century Multicultural Britain." Social Policy and Society 16, no. 4 (September 27, 2016): 535–59. http://dx.doi.org/10.1017/s1474746416000440.
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Peter Townsend argued that poverty could be scientifically measured as a ‘breakpoint’ within the income distribution below which participation collapses. This paper stands on Townsend's shoulders in measuring the level of poverty and participation by: (1) broadening his original measurement of participation; (2) using Structural Equation Modelling (SEM) in conjunction with a new dataset including 40,000 households (Understanding Society, 2011; 2013); and (3) taking into account the multi-cultural/ethnic nature of British society. We find that participation – defined as lack of deprivation, social participation and trust – reduces as income falls but stops doing so among the poorest 30 per cent of individuals. This may be indicating a minimum level of participation, a floor rather than a ‘breakpoint’ as suggested by Townsend, which has to be sustained irrespective of how low income is. Respondents with an ethnic minority background manifest lower levels of participation than white respondents but the relationship has a less linear pattern. Moreover, the floor detected for the overall population is also replicated when combining all respondents from ethnic groups.
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Wadoux, Alexandre M. J. C., José Padarian, and Budiman Minasny. "Multi-source data integration for soil mapping using deep learning." SOIL 5, no. 1 (March 22, 2019): 107–19. http://dx.doi.org/10.5194/soil-5-107-2019.
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Abstract. With the advances of new proximal soil sensing technologies, soil properties can be inferred by a variety of sensors, each having its distinct level of accuracy. This measurement error affects subsequent modelling and therefore must be integrated when calibrating a spatial prediction model. This paper introduces a deep learning model for contextual digital soil mapping (DSM) using uncertain measurements of the soil property. The deep learning model, called the convolutional neural network (CNN), has the advantage that it uses as input a local representation of environmental covariates to leverage the spatial information contained in the vicinity of a location. Spatial non-linear relationships between measured soil properties and neighbouring covariate pixel values are found by optimizing an objective function, which can be weighted with respect to a measurement error of soil observations. In addition, a single model can be trained to predict a soil property at different soil depths. This method is tested in mapping top- and subsoil organic carbon using laboratory-analysed and spectroscopically inferred measurements. Results show that the CNN significantly increased prediction accuracy as indicated by the coefficient of determination and concordance correlation coefficient, when compared to a conventional DSM technique. Deeper soil layer prediction error decreased, while preserving the interrelation between soil property and depths. The tests conducted suggest that the CNN benefits from using local contextual information up to 260 to 360 m. We conclude that the CNN is a flexible, effective and promising model to predict soil properties at multiple depths while accounting for contextual covariate information and measurement error.
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Serman, Maja, and Niall J. L. Griffith. "Investigating Melodic Segmentation through the Temporal Multi-Scaling Framework." Musicae Scientiae 7, no. 1_suppl (September 2003): 125–55. http://dx.doi.org/10.1177/10298649040070s107.
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In this paper we approach the subject of modelling and understanding segmentation processes in melodic perception using a temporal multi-scale representation framework. We start with the hypothesis that segmentation depends on the ability of the perceptual system to detect changes in the sensory signal. In particular, we are interested in a model of change detection in music perception that would help us to investigate functional aspects of low-level perceptual processes in music and their universality in terms of the general properties of the auditory system. To investigate this hypothesis, we have developed a temporal multi-scale model that mimics the ability of the listener to detect changes in pitch, loudness and timbre when listening to performed melodies. The model is set within the linear scale-space theoretical framework, as developed for image structure analysis but in this case applied to the temporal processing domain. It is structured in such a way as to enable us to verify the assumption that segmentation is influenced by both the dynamics of signal propagation through a neural map and learning and attention factors. Consequently, the model is examined from two perspectives: 1) the computational architecture which models signal propagation is examined for achieving the effects of the universal, inborn aspects of segmentation 2) the model structure capable of influencing choices of segmentation outcomes is explained and some of its effects are examined in view of the known segmentation results. The results of the presented case studies demonstrate that the model accounts for some effects of perceptual organization of the sensory signal and provides a sound basis for analysing different types of changes and coordination across the melodic descriptors in segmentation decisions.
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Li, Peng, and Di Wu. "A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference." International Journal of Environmental Research and Public Health 18, no. 9 (April 29, 2021): 4760. http://dx.doi.org/10.3390/ijerph18094760.
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The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.
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Elsherif, Mahmoud Medhat, Jon C. Catling, and Steven Frisson. "Two words as one: A multi-naming investigation of the age-of-acquisition effect in compound-word processing." Memory & Cognition 48, no. 4 (November 21, 2019): 511–25. http://dx.doi.org/10.3758/s13421-019-00986-6.
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AbstractPrevious research has shown that early-acquired words are produced faster than late-acquired words. Juhasz and colleagues (Juhasz, Lai & Woodcock, Behavior Research Methods, 47 (4), 1004-1019, 2015; Juhasz, The Quarterly Journal of Experimental Psychology, 1-10, 2018) argue that the Age-of-Acquisition (AoA) loci for complex words, specifically compound words, are found at the lexical/semantic level. In the current study, two experiments were conducted to evaluate this claim and investigate the influence of AoA in reading compound words aloud. In Experiment 1, 48 participants completed a word naming task. Using general linear mixed modelling, we found that the age at which the compound word was learned significantly affected the naming latencies beyond the other psycholinguistic properties measured. The second experiment required 48 participants to name the compound word when the two morphemes were presented with a space in-between (combinatorial naming, e.g. air plane). We found that the age at which the compound word was learned, as well as the AoA of the individual morphemes that formed the compound word, significantly influenced combinatorial naming latency. These findings are discussed in relation to theories of the AoA in language processing.
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Clay-Williams, Robyn, Natalie Taylor, Hsuen P. Ting, Teresa Winata, Gaston Arnolda, Elizabeth Austin, and Jeffrey Braithwaite. "The relationships between quality management systems, safety culture and leadership and patient outcomes in Australian Emergency Departments." International Journal for Quality in Health Care 32, Supplement_1 (January 2020): 43–51. http://dx.doi.org/10.1093/intqhc/mzz105.
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Abstract Objective We aimed to examine whether Emergency Department (ED) quality strategies, safety culture and leadership were associated with patient-level outcomes, after controlling for other organization-level factors, in 32 large Australian hospitals. Design Quantitative observational study, using linear and multi-level modelling to identify relationships between quality management systems at organization level; quality strategies at ED level for acute myocardial infarction (AMI), hip fracture and stroke; clinician safety culture and leadership and patient-level outcomes of waiting time and length of stay. Setting Thirty-two large Australian public hospitals. Participants Audit of quality management processes at organization and ED levels, senior quality manager at each of the 32 participating hospitals, 394 ED clinicians (doctors, nurses and allied health professionals). Main Outcome Measure(s) Within the multi-level model, associations were assessed between organization-level quality measures and ED quality strategies; organization-level quality measures and ED quality strategies and ward-level clinician measures of teamwork climate (TC), safety climate (SC) and leadership for AMI, hip fracture and stroke treatment conditions; and organization-level quality measures and ED quality strategies and ward-level clinician measures of TC, SC and leadership, and ED waiting time and length of stay (performance). Results We found seven statistically significant associations between organization-level quality systems and ED-level quality strategies; four statistically significant associations between quality systems and strategies and ED safety culture and leadership; and nine statistically significant associations between quality systems and strategies and ED safety culture and leadership, and ED waiting time and length of stay. Conclusions Organization-level quality structures influence ED-level quality strategies, clinician safety culture and leadership and, ultimately, waiting time and length of stay for patients. By focusing only on time-based measures of ED performance we risk punishing EDs that perform well on patient safety measures. We need to better understand the trade-offs between implementing safety culture and quality strategies and improving patient flow in the ED, and to place more emphasis on other ED performance measures in addition to time.
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Sena, Boni, Sheikh Ahmad Zaki, Fitri Yakub, Nelidya Md Yusoff, and Mohammad Kholid Ridwan. "Conceptual Framework of Modelling for Malaysian Household Electrical Energy Consumption using Artificial Neural Network based on Techno-Socio Economic Approach." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 3 (June 1, 2018): 1844. http://dx.doi.org/10.11591/ijece.v8i3.pp1844-1853.
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The residential sector was one of the contributors to the increase in the world energy consumption and CO2 emission due to the increase population, economic development, and improved living standard. Developing a reliable model of electrical energy consumption based on techno-socio economic factors was challenging since many assumptions need to be considered. Over the past decade, bottom-up approaches such as multi-linear regression, artificial neural network (ANN), and conditional demand analysis were used for developing mathematical models to investigate interrelated characteristics among techno-socio economic factors. However, the existing models mostly were focused on countries that had different socio-economic level and cultures from the developing countries of the Association of Southeast Asian Nations. Similar studies in that tropical region were very scarce and only limited for linear modelling under the conditions of techno-socio economic factors. In this study, we proposed ANN for developing a model of electrical energy consumption based on techno-socio economic factors for a tropical region, Malaysia. In order to develop the model, quantitative measurement and qualitative assessment were required. The quantitative measurement was based on the monitoring of total electrical energy consumption with a one-minute interval. In contrast, the qualitative assessment utilized a questionnaire survey to assess household characteristics based on techno-socio economic parameters. The objective of this paper was to propose a conceptual framework of the estimation model for household electrical energy consumption with the consideration of techno-socio economic factors using ANN.
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Keaver, Laura, Benshuai Xu, Abbygail Jaccard, and Laura Webber. "Morbid obesity in the UK: A modelling projection study to 2035." Scandinavian Journal of Public Health 48, no. 4 (August 30, 2018): 422–27. http://dx.doi.org/10.1177/1403494818794814.
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Background: Morbid obesity (body mass index ⩾40 kg/m2) carries a higher risk of non-communicable disease and is associated with more complex health issues and challenges than obesity body mass index ≥30kg/m2 and <40kg/m2, resulting in much higher financial implications for health systems. Although obesity trends have previously been projected to 2035, these projections do not separate morbid obesity from obesity. This study therefore complements these projections and looks at the prevalence and development of morbid obesity in the UK. Methods: Individual level body mass index data for people aged >15 years in England, Wales (2004–2014) and Scotland (2008–2014) were collated from national surveys and stratified by sex and five-year age groups (e.g. 15–19 years), then aggregated to calculate the annual distribution of healthy weight, overweight, obesity and morbid obesity for each age and sex group. A categorical multi-variate non-linear regression model was fitted to these distributions to project trends to 2035. Results: The prevalence of morbid obesity was predicted to increase to 5, 8 and 11% in Scotland, England and Wales, respectively, by 2035. Welsh women aged 55–64 years had the highest projected prevalence of 20%. In total, almost five million people are forecast to be classified as morbidly obese across the three countries in 2035. Conclusions: The prevalence of morbid obesity is predicted to increase by 2035 across the three UK countries, with Wales projected to have the highest rates. This is likely to have serious health and financial implications for society and the UK health system.
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Crespi, Pietro, Marco Zucca, Nicola Longarini, and Nicola Giordano. "Seismic Assessment of Six Typologies of Existing RC Bridges." Infrastructures 5, no. 6 (June 26, 2020): 52. http://dx.doi.org/10.3390/infrastructures5060052.
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Over the last few decades, the attention on the safety of existing reinforced concrete (RC) structures has significantly increased. RC bridges, in particular, are highly relevant for strategic importance. In the Italian context, several of these bridges were built around 1960, when engineering practice commonly ignored or underestimated the presence of seismic actions. Therefore, it is fundamental to quantify as accurately as possible their seismic safety level with state-of-the-art analysis techniques. In this paper, an efficient procedure based on the multi-modal pushover analysis approach is proposed for the risk evaluation of several bridges of the Italian highway network. This procedure, tailored for portfolio level assessment, takes into account the non-linear behavior and the complex dynamic response this type of structure with limited computational effort. Three fundamental aspects are defined for the structural modelling of bridges, i.e., materials’ constitutive law, finite element type and nonlinear hinge models. Flexural and shear nonlinearities of piers are included to account for ductile and brittle damage potential. The standardized procedure guarantees consistent comparisons among different bridges of the same network in the form of risk indexes.
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He, Yusheng, Gucheng Zhang, Changzhu Liu, Ming Ruan, Yao Wang, and Changping Mao. "Recognition of Significant Multi-Element Geochemical Signatures of Lower Soil on Hainan Island, China: Implications for Thermal Mineral Water Exploration." Water 14, no. 3 (January 24, 2022): 341. http://dx.doi.org/10.3390/w14030341.
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As an important geothermal resource, thermal mineral water has high resource efficiency and thermal energy efficiency. The aim of this study was to delineate prospective areas of thermal mineral water based on potential thermal mineral water sites and faults. Linear regression was used to process the temperature of 22 known thermal mineral water sites as dependent variables, and 54 indices of the lower soil of multipurpose regional geochemical surveys as independent variables, in the area of intermediate-acid intrusive rocks and sediment degeneration rocks on Hainan Island. Published data were quoted from the National Multi-Purpose Regional Geochemical Survey (Hainan Province, China). According to the regressive modelling of 2197 lower soil samples, 547 potential thermal mineral water sites were delineated after considering 4 factors—geological background, regional structure, interval of dependent variable’s predictive temperature, and boundary of independent variable’s contents—which were compared against 22 known thermal mineral water sites to choose the 2197 lower soil samples, based on the choice of prospective sites of thermal mineral water on Hainan Island. The results showed that the proportion of A1-level sites that were >70 °C constituted 11% of all A1-level prospective sites, reflecting the superiority of east–west or north–east directional regional faults in controlling the distribution of thermal mineral water. This study shows the indications of the multipurpose regional geochemical survey with regards to thermal mineral water, which is one of the most important tourist resources of Hainan Island.
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Runya, Robert Mzungu, Chris McGonigle, Rory Quinn, John Howe, Jenny Collier, Clive Fox, James Dooley, et al. "Examining the Links between Multi-Frequency Multibeam Backscatter Data and Sediment Grain Size." Remote Sensing 13, no. 8 (April 15, 2021): 1539. http://dx.doi.org/10.3390/rs13081539.
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Acoustic methods are routinely used to provide broad scale information on the geographical distribution of benthic marine habitats and sedimentary environments. Although single-frequency multibeam echosounder surveys have dominated seabed characterisation for decades, multifrequency approaches are now gaining favour in order to capture different frequency responses from the same seabed type. The aim of this study is to develop a robust modelling framework for testing the potential application and value of multifrequency (30, 95, and 300 kHz) multibeam backscatter responses to characterize sediments’ grain size in an area with strong geomorphological gradients and benthic ecological variability. We fit a generalized linear model on a multibeam backscatter and its derivatives to examine the explanatory power of single-frequency and multifrequency models with respect to the mean sediment grain size obtained from the grab samples. A strong and statistically significant (p < 0.05) correlation between the mean backscatter and the absolute values of the mean sediment grain size for the data was noted. The root mean squared error (RMSE) values identified the 30 kHz model as the best performing model responsible for explaining the most variation (84.3%) of the mean grain size at a statistically significant output (p < 0.05) with an adjusted r2 = 0.82. Overall, the single low-frequency sources showed a marginal gain on the multifrequency model, with the 30 kHz model driving the significance of this multifrequency model, and the inclusion of the higher frequencies diminished the level of agreement. We recommend further detailed and sufficient ground-truth data to better predict sediment properties and to discriminate benthic habitats to enhance the reliability of multifrequency backscatter data for the monitoring and management of marine protected areas.
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Gogo, Siphiwe, and Innocent Musonda. "The Use of the Exploratory Sequential Approach in Mixed-Method Research: A Case of Contextual Top Leadership Interventions in Construction H&S." International Journal of Environmental Research and Public Health 19, no. 12 (June 14, 2022): 7276. http://dx.doi.org/10.3390/ijerph19127276.
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Quality and rigour remain central to the methodological process in research. The use of qualitative and quantitative methods in a single study was justified here against using a single method; the empirical output from the literature review should direct the current worldview and, subsequently, the methodologies applied in research. It is critical to gather contextual behavioural data from subject matter experts—this helps establish context and confirm the hypotheses arising from the literature, which leads to the refinement of the theory’s applicability for developing a conceptual model. This paper identified the top leaders in construction organisations as subject matter experts. Nine semi-structured interviews were conducted, representing the South African construction industry grading. The output of the refined hypothesis was followed by a survey that targeted n = 182 multi-level senior leaders to gather further perspectives and validate the conceptual model. The outcome resulting from the rigorous validation process adopted—the analysis process, which included Spearman rank correlation, ordinal logistic regression and multinomial generalised linear modelling—demonstrated that the lack of H&S commitment in top leadership persists, despite high awareness of the cruciality of H&S in their organisations. Contextual competence, exaggerated by the local setting, is one source of this deficiency. This paper provides guidelines for using the exploratory sequential approach in mixed-method research to effectively deal with contextual issues based on non-parametric modelling data in top leadership H&S interventions.
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Dimarco, Giacomo, and Giuseppe Toscani. "Social climbing and Amoroso distribution." Mathematical Models and Methods in Applied Sciences 30, no. 11 (October 2020): 2229–62. http://dx.doi.org/10.1142/s0218202520500426.
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We introduce a class of one-dimensional linear kinetic equations of Boltzmann and Fokker–Planck type, describing the dynamics of individuals of a multi-agent society questing for high status in the social hierarchy. At the Boltzmann level, the microscopic variation of the status of agents around a universal desired target, is built up introducing as main criterion for the change of status a suitable value function in the spirit of the prospect theory of Kahneman and Twersky. In the asymptotics of grazing interactions, the solution density of the Boltzmann-type kinetic equation is shown to converge towards the solution of a Fokker–Planck type equation with variable coefficients of diffusion and drift, characterized by the mathematical properties of the value function. The steady states of the statistical distribution of the social status predicted by the Fokker–Planck equations belong to the class of Amoroso distributions with Pareto tails, which correspond to the emergence of a social elite. The details of the microscopic kinetic interaction allow to clarify the meaning of the various parameters characterizing the resulting equilibrium. Numerical results then show that the steady state of the underlying kinetic equation is close to Amoroso distribution even in an intermediate regime in which interactions are not grazing.
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Mauya, Ernest William, Joni Koskinen, Katri Tegel, Jarno Hämäläinen, Tuomo Kauranne, and Niina Käyhkö. "Modelling and Predicting the Growing Stock Volume in Small-Scale Plantation Forests of Tanzania Using Multi-Sensor Image Synergy." Forests 10, no. 3 (March 21, 2019): 279. http://dx.doi.org/10.3390/f10030279.
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Remotely sensed assisted forest inventory has emerged in the past decade as a robust and cost efficient method for generating accurate information on forest biophysical parameters. The launching and public access of ALOS PALSAR-2, Sentinel-1 (SAR), and Sentinel-2 together with the associated open-source software, has further increased the opportunity for application of remotely sensed data in forest inventories. In this study, we evaluated the ability of ALOS PALSAR-2, Sentinel-1 (SAR) and Sentinel-2 and their combinations to predict growing stock volume in small-scale forest plantations of Tanzania. The effects of two variable extraction approaches (i.e., centroid and weighted mean), seasonality (i.e., rainy and dry), and tree species on the prediction accuracy of growing stock volume when using each of the three remotely sensed data were also investigated. Statistical models relating growing stock volume and remotely sensed predictor variables at the plot-level were fitted using multiple linear regression. The models were evaluated using the k-fold cross validation and judged based on the relative root mean square error values (RMSEr). The results showed that: Sentinel-2 (RMSEr = 42.03% and pseudo − R2 = 0.63) and the combination of Sentinel-1 and Sentinel-2 (RMSEr = 46.98% and pseudo − R2 = 0.52), had better performance in predicting growing stock volume, as compared to Sentinel-1 (RMSEr = 59.48% and pseudo − R2 = 0.18) alone. Models fitted with variables extracted from the weighted mean approach, turned out to have relatively lower RMSEr % values, as compared to centroid approaches. Sentinel-2 rainy season based models had slightly smaller RMSEr values, as compared to dry season based models. Dense time series (i.e., annual) data resulted to the models with relatively lower RMSEr values, as compared to seasonal based models when using variables extracted from the weighted mean approach. For the centroid approach there was no notable difference between the models fitted using dense time series versus rain season based predictor variables. Stratifications based on tree species resulted into lower RMSEr values for Pinus patula tree species, as compared to other tree species. Finally, our study concluded that combination of Sentinel-1&2 as well as the use Sentinel-2 alone can be considered for remote-sensing assisted forest inventory in the small-scale plantation forests of Tanzania. Further studies on the effect of field plot size, stratification and statistical methods on the prediction accuracy are recommended.
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Britz, Wolfgang. "Disaggregating Agro-Food Sectors in the GTAP Data Base." Journal of Global Economic Analysis 7, no. 1 (June 24, 2022): 44–75. http://dx.doi.org/10.21642/jgea.070102af.
Full textAbstract:
We discuss the construction of the GTAP-AGROFOOD database for CGE modelling which is consistent with the standard GTAP Data Base Version 10a (Aguiar et al. 2019). GTAP-AGROFOOD departs from the full detail of 141 regions, 65 products and 8 factors in GTAP, by introducing 51 additional agro-food products and sectors in lieu of 11 original GTAP agro-food products, thereby yielding a database with 105 products. Such additional detail can improve and enrich, for instance, analysis of trade, bio-economy or climate change mitigation or adaptation issues. It also eases linkage to other, more detailed data sets, such as for nutrition accounting or irrigation water use. The main data sources used are the FABIO Multi-Regional Input-Output Database (Bruckner et al. 2019) which reports on production, land, seed, feed, and food use, mainly for primary agricultural products, and market balances for dairy products from FAOSTAT. They are combined with TASTE V10a (Pelikan et al. 2020) which provides bilateral trade and tariffs revenues at the level of tariff lines. The balancing methodology which ensures consistency with the GTAP Data Base is based on the linear loss based split utility of CGEBox (Britz 2021).
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Rannik, Ü., N. Altimir, I. Mammarella, J. Bäck, J. Rinne, T. M. Ruuskanen, P. Hari, T. Vesala, and M. Kulmala. "Ozone deposition into a boreal forest over a decade of observations: evaluating deposition partitioning and driving variables." Atmospheric Chemistry and Physics Discussions 12, no. 5 (May 22, 2012): 12715–58. http://dx.doi.org/10.5194/acpd-12-12715-2012.
Full textAbstract:
Abstract. This study scrutinizes a decade-long series of ozone deposition measurements in a boreal forest in search for the signature and relevance of the different deposition processes. Canopy-level ozone flux measurements were analysed for deposition characteristics and partitioning into stomatal and non-stomatal fractions, focusing on growing season day-time data. Ten years of measurements enabled the analysis of ozone deposition variation at different time- scales, including daily to inter-annual variation as well as the dependence on environmental variables and concentration of biogenic volatile organic compounds (BVOC-s). Stomatal deposition was estimated by using multi-layer canopy dispersion and optimal stomatal control modelling from simultaneous carbon dioxide and water vapour flux measurements, non-stomatal was inferred as residual. Also, utilising big-leaf assumption stomatal conductance was inferred from water vapour fluxes for dry canopy conditions. The total ozone deposition was highest during the peak growing season (4 mm s−1) and lowest during winter dormancy (1 mm s−1). During the course of the growing season the fraction of the non-stomatal deposition of ozone was determined to vary from 26 to 44% during day time, increasing from the start of the season until the end of the growing season. By using multi-variate analysis it was determined that day-time total ozone deposition was mainly driven by photosynthetic capacity of the canopy, vapour pressure deficit (VPD), photosynthetically active radiation and monoterpene concentration. The multi-variate linear model explained high portion of ozone deposition variance on daily average level (R2 = 0.79). The explanatory power of the multi-variate model for ozone non-stomatal deposition was much lower (R2 = 0.38). Model calculation was performed to evaluate the potential sink strength of the chemical reactions of ozone with sesquiterpenes in the canopy air space, which revealed that sesquiterpenes in typical amounts at the site were unlikely to cause significant ozone loss in canopy air space. This was also confirmed by the statistical analysis that did not link measured sesquiterpene concentration with ozone deposition. It was concluded that chemical reactions with monoterpenes, or other removal mechanisms such as surface reactions, play a role as ozone non-stomatal sink inside canopy.