Search Results for weight

... to a physicist and make wrong predictions based on those features. Engel Clough and Driver (1985) also noted that pupils apply to liquids the experience they have developed with solids, for which weight vertically acts downwards. This is an idea that is often accompanied by a lack of “differentiation between...

... with its characteristic length to the power 1.5, which implies that in comparison to the smaller animals, the bones of larger animals are thicker than anticipated based on the idea of linear scaling. In humans, the weight of the brain shows allometric growth compared to body weight. In a newborn, the brain...

...-objective optimization problem in practice. To make a trade-off between multiple objectives, the solution approach can be classified into two categories: aggregating weight function methods and Pareto-based optimization methods. Herein, note that the multi-objective optimization problem can also...

... ) T R ( u − u s ) where Q ∈ R n × R n and R ∈ R m × R m are positive definite weighting matrices which determine the weights on the deviation of the state and input from the steady-state. At a sampling time t_k, MPC uses...

... , z ) . The pixels in both kinds of matrices were scaled to [0, 1] as the comparison aimed at the relative difference of the two solar flux distributions. The weight was introduced here for the area of interest to allow better identification results. In this work, for the flux value...

... radiation availability. Considering these points, Santibañez-Aguilar et al. (2020) developed a mathematical formulation for the optimal design of a PV manufacturing value chain taking into account uncertainty in electricity cost, inflation, and the weighted average cost of capital. This proposed...

... be difficult to draw conclusions from them as they tend to weight all studies identically and the intervention effects are often characterized in a categorical way (e.g., positive or negative) without consideration for the numeric magnitude of those effects. Statistical approaches to synthesizing effects...

... , and x_s are the vectors containing the predictions from the DNN models, actual process variables, and the desired set-point values for C_A and T, respectively. Q_c is a weighting matrix that weighs the importance of the process variables, k...

...-Newtonian thinking identified by IRT. Network Analysis A network is formed by a collection of nodes connected by edges to form a graph. The edges may be directed or un-directed. The edges may also be weighted to indicate some features of the interaction. Note that the term edge comes from graph theory...

... structure of these materials also make them ideal candidates for miniature, light weight and flexible optoelectronic device applications ( Stanford et al., 2018 ). Such unconventional mechanical strains can lead to unusual electronic and optical properties, which makes the study of their mechanical...

... to that of ( 9.4 ). The output is computed from the hidden state using a feedforward neural network layer, given by (9.6) y k = α ( θ y , x h x d e c , k h + θ y ) where θ y , x h and θ_y denote the weight matrix and bias vector...

... of the potential difference ( Kenworthy, 1941 ), and the definitions of mass, force and weight ( Iona, 1944 ). All three articles discussed the consistency, completeness and correctness of the concept definition, which have been inherited in the follow-up research, although some studies only addressed one or two...

... of the leak-off rate U. (12.23) U = 2 C leak t − τ ( z ) Now that the hybrid model structure and its components have been defined, and the training data are available, we initialized the parameters of DNN (i.e., weight W and bias B) and began the Levenberg...

...-time change in the weight of a small adsorbent particle in the presence of a step change in CO₂ partial pressure. The latter measures the step response of CO₂ concentration output, which yields the breakthrough curve. It not only provides the maximum loading of the adsorptive...