Examples of using Linear model in English and their translations into Arabic
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Internal Structure: Linear Model.
Linear models imply simplistic policy approaches.
Two versions of the linear model of innovation are often presented.
Linear model. But we knew there were limits to linear models as well, right?
After 1950 Scheffé's research was concerned with aspects of linear models, particularly the analysis of variance.
We might then run a linear model through that and sort of make predictions based on that.
We did some very simple things,like category models and then we did some more scientific things like, linear models.
And we said how linear models can be even better at predicting patterns of variation in data.
However, it has become evident that building capacity to absorb, diffuse andmaintain new technologies is far more complex and costly than this linear model suggests.
In the linear model, the assumption is that there is no dosage that has no risk of causing cancer.
However, this situation must be takeninto account for further development and integration of a linear model to look content with a nonlinear, develop multiplatform and recommendation services.
Linear models imply that there is one way of causal relation from initial impulse to final outcome, which is innovation.
In a mathematical programming model, if the objective functions and constraints are represented entirely by linear equations,then the model is regarded as a linear model.
Maps showing the correlations between atmospheric variables and annual cases of meningococcal meningitis enable the selection ofrelevant climatic variables for the construction of generalized linear models to forecast meningococcal meningitis intensity from year to year.
Generalized linear models(GLMs) are a framework for modeling response variables that are bounded or discrete. This is used, for example.
Perturb-seq couples CRISPR mediatedgene knockdowns with single-cell gene expression. Linear models are used to calculate the effect of the knockdown of a single gene on the expression of multiple genes.
In a traditional linear model, research is undertaken to generate outputs that may provide leads for further investigation or go to field trials and pilot stages.
Proponents of the circular economy suggest that a sustainable world does not mean a drop in the quality of life for consumers, and can be achieved without loss of revenue or extra costs for manufacturers. The argument is that circularbusiness models can be as profitable as linear models, allowing us to keep enjoying similar products and services.
For example, in a statistical linear model, it is assumed that a relationship is linear in the parameters, but it may be nonlinear in the predictor variables.
Al-Khowaiter defined a circular economy as moving from a linear model, where materials are used and then disposed, to a more circular manner through the reduction of consumption, reuse, and recycle.
The Linear Model of Innovation was an early model designed to understand the relationship of science and technology that begins with basic research that flows into applied research, development and diffusion[1].
The new approach calls for a move away from a linear model of integration, which lays undue emphasis on processes, into a more pragmatic and results-oriented approach to integration.
Linear models of the" push" category tend to emphasize supply-side policies(e.g. investment in training, R & D, and national ICT infrastructures), while" pull" models imply demand-side policies(e.g. market stimulation, user training, or the establishment of uniform standards).
Once the NIS rather than the linear model is adopted as the framework of STI policy, policies need to consider a much broader set of issues.
Linear models imply that there is a direct causal relation from initial impulse to final outcome, which is innovation; the initial impulse can be either of a" supply push" nature, that is, it originates from government initiatives to set up institutions and policies to encourage R & D, or of a" demand pull" nature, that is, the initial impulse comes from the demands and needs existing in the markets.
For the wine industry, we have studied both linear models for standard production and rotary line models with 6 and 9 plates for front-back and collar labelling, with option of tin or PVC cap;
Generalized linear models allow for an arbitrary link function, g, that relates the mean of the response variable(s) to the predictors: E( Y) = g- 1( X B){\displaystyle E( Y) g{ -1}( XB)}. The link function is often related to the distribution of the response, and in particular it typically has the effect of transforming between the(-∞ ,∞ ){\displaystyle(-\infty,\infty)} range of the linear predictor and the range of the response variable.
Many-- even scientists-- assume a linear model, so they will say,"Oh, it will be hundreds of years before we have self-replicating nano-technology assembly or artificial intelligence.".
It is increasingly recognized that the linear model of innovation, which gave prominence to research and development(R & D) as the key phase in innovation(a" technology push" strategy) is failing the exigencies of technological learning.