Moreover, the program will be incorporated in the regular school curriculum, enabling all adolescents to participate in the program, maximizing high program attendance and minimizing measurement attrition rates.
As most participants' level of literacy was expected to be low (based on advice from family members), the program maximized the use of materials and equipment that incorporated visual (images) and auditory content that minimized the use of reading and writing.
The Coach Program maximizes human resources and family-centred care by formally integrating an individual whom the patient identifies as their primary support into their health care team.
In this way, a targeted peer-tutoring program maximizes the benefits of limited resources by significantly improving the performance of struggling students in an introductory course, by increasing retention of STEM majors, and by helping peer tutors develop teaching skills and further mastery in a STEM field.
While narrow targeting of the subsidy almost certainly reduces the budgetary cost of the program and maximizes the benefits to the favored group, those benefits are likely to come at the expense of other groups.
An ideal management program maximizes hydrocarbon production and minimizes the cost of scale deposits control, thereby maintaining the economic viability of the operations.
Using SVM with the Raw kernel amounts to solving the following quadratic program: Maximize J over α i : subject to.
The dual version of the above problem corresponds to finding a solution to the following quadratic program: Maximize J over α i : subject to, where α i is a real number.
Given a n-dimensional input vector, x i=(x 1,x 2,…,x n) with class labels, y i ∈ {+1,–1}, (i=1,2,..., N), the hyperplane decision function of binary SVM with kernel method is written as: and the following quadratic program: maximize subject to a i ≥ 0, and where is the number of training patters; a i are the parameters of the SVM; is a suitable kernel function, and b is the bias term.
The centroid vector of each voronoi region which can be expressed as: The new local SVM's approximation can be written as: and the following quadratic program: maximize subject to a i ≥ 0, and SVM is considered as a purely non-parametric model, whereas SV-HMM is considered as semi-parametric model as it adopts the method of grouping the associated input vectors in each class i.
