introduction: the present post-eventual research study was conducted with the purpose of comparing the memory performance between two distinct groups of 50 healthy children and 50 attention deficit hyperactivity disorder (adhd) children (25 girls and 25 boys) in tehran with an age range of 10-12. methods: the whole students were selected through simple random sampling method and were assessed i...

New non-volatile memory devices can overcome DRAM’s high energy consumption, volatility, and the density scaling limit. By using these advantages, next generation nonvolatile memory devices can be a promising candidate replacing conventional memory devices such as DRAM. In this paper, we propose a pattern adaptive buffering management method for the superblock-based M-D (memory-disk) adapter th...

This paper proposes an adaptive rendering technique for ray-bundle tracing. Ray-bundle tracing can be done by per-pixel linked-list construction on a GPU rasterization pipeline. This rasterization based approach offers significant benefits for the efficient generation of light maps (e.g., hardware acceleration, tessellation, and recycling of shaders used in real-time graphics). However, it is i...

Many of the problems considered in optimization and learning assume that solutions exist in a dynamic. Hence, algorithms are required that dynamically adapt with the problem’s conditions and search new conditions. Mostly, utilization of information from the past allows to quickly adapting changes after. This is the idea underlining the use of memory in this field, what involves key design issue...

This paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (MIMO) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. The agents may have different dynamics and communicate together under a directed graph. A distributed adaptive method is designed for both cases. The structures of the contro...

The aim of this contribution is to provide an adaptive estimation of the long-memory parameter in the classical semi-parametric framework for Gaussian stationary processes using a wavelet method. In particular, the choice of a data-driven optimal band of scales is introduced and developed. Moreover, a central limit theorem for the estimator of the long-memory parameter reaching the minimax rate...