This paper investigates the dissociation between conscious and unconscious knowledge in an implicit learning paradigm. Two experiments employing the artificial grammar learning task explored the acquisition of unconscious and conscious knowledge of structure (structural knowledge). Structural knowledge was contrasted to knowledge of whether an item has that structure (judgment knowledge). For b...

task assignment problem (tap) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints. tap is a combinatorial optimization problem and np-complete. this paper proposes a hybrid meta-heuristic algorithm for solving tap in a h...

response surface methodology is a common tool in optimizing processes. it mainly concerns situations when there is only one response of interest. however, many designed experiments often involve simultaneous optimization of several quality characteristics. this is called a multiresponse surface optimization problem. a common approach in dealing with these problems is to apply desirability funct...

economic dispatch with valve point effect and prohibited operating zones (pozs) is a non-convex and discontinuous optimization problem. harmony search (hs) is one of the recently presented meta-heuristic algorithms for solving optimization problems, which has different variants. the performances of these variants are severely affected by selection of different parameters of the algorithm. intel...

Most researchers leverage bottom-up suppression to unlock the underlying mechanisms of unconscious processing. However, a top-down approach - for example via hypnotic suggestion - paves the road to experimental innovation and complementary data that afford new scientific insights concerning attention and the unconscious. Drawing from a reliable taxonomy that differentiates subliminal and precon...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...

The process-dissociation procedure was used to investigate conscious and unconscious influences of memory for object location. In two experiments, subjects worked with drawings of household objects and rooms of a house depicted on a computer monitor to simulate placing objects in various locations. Memory for object locations was tested by having subjects search for those objects. A double diss...