Graphical constraints: a graphical user interface for constraint problems

A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.

Developmental and physical-fitness associations with gross motor coordination problems in peruvian children

he aims of this cross-sectional study were to examine the developmental characteristics (biological maturation and body size) associated with gross motor coordination problems in 5193 Peruvian children (2787 girls) aged 6–14 years from different geographical locations, and to investigate how the probability that children suffer with gross motor coordination problems varies with physical fitness. Children with gross motor coordination problems were more likely to have lower flexibility and explosive strength levels, having adjusted for age, sex, maturation and study site. Older children were more likely to suffer from gross motor coordination problems, as were those with greater body mass index. However, more mature children were less likely to have gross motor coordination problems, although children who live at sea level or at high altitude were more likely to suffer from gross motor coordination problems than children living in the jungle. Our results provide evidence that children and adolescents with lower physical fitness are more likely to have gross motor coordination difficulties. The identification of youths with gross motor coordination problems and providing them with effective intervention programs is an important priority in order to overcome such developmental problems, and help to improve their general health status.