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The major purpose of the traits concept, as we present it here, is to develop an ontologically inclusive traits framework capable of addressing both the resilience of ecological functions and the experiential and relational aspects of human interactions with nature. On the applied side, this would...
Gradients are a mathematical concept that represents the direction and magnitude of the change in a scalar field. In vector fields, gradients are used to determine the direction of the vectors at each point. The gradient of a scalar field is always perpendicular to the ve...
The sign of the vector representing the atmospheric electric field has recently been subject of debate. For the sake of clarity, it is recommended to refer only to a "normal" or "reversed" clear-weather potential gradient.doi:10.1007/BF02247189H. Israël...
is thatgradientis a slope or incline whileslopeis an area of ground that tends evenly upward or downward. As adjectives the difference betweengradientandslope is thatgradientis moving by steps; walking whileslopeis sloping. As a verbslopeis ...
The amplitude is the distance from the equilibrium position of the medium to a compression or a rarefaction. The peak value of sinusoidal AC signals is referred to as amplitude starting from the zero line. The amplitude usually refers to the scalar or vector field size. ...
∇(⋅)∇(⋅) is the gradient function. The code looks different because it moves by the brown vector instead of the green vector, as the Nesterov method only requires evaluating ∇(w+m⋅v)=:g∇(w+m⋅v)=:g instead of ∇(w)∇(w). Therefore in each s...
is not parallel to the shared face normal. So, the resulting face gradient ends up being computed as a mixture of the straight line gradient (corrected for direction) and the average of the cell gradient fields in the neighboring cells. There is a good overview of this in the Ansys Fluent...
Both is correct: The potential of a vector field is a scalar field, whose gradient gives the vector field (supposed there exists a potential for the vector field). If a force has a potential that does not explicitly depend on time, then energy is conserved, i.e., for a particle subject...
moving beyond reliance on predefined rules. A notable achievement during this time was the introduction of backpropagation, a method for training neural networks using gradient descent. Throughout this period, various machine learning algorithms, including k-NN, SVM, anddecision trees, were conceived....