As mobile robots are increasingly introduced into our daily lives, it grows ever more imperative that these robots navigate with and among people in a safe and socially acceptable manner, particularly in shared spaces. While research on enabling socially-aware robot navigation has expanded over the years, there are no agreed-upon evaluation protocols or benchmarks to allow for the systematic development and evaluation of socially-aware navigation. As an effort to aid more productive development and progress comparisons, in this paper we review the evaluation methods, scenarios, datasets, and metrics commonly used in previous socially-aware navigation research, discuss the limitations of existing evaluation protocols, and highlight research opportunities for advancing socially-aware robot navigation.
Through eigenanalysis of communication matrices, we develop a new objective function formulation for mapping tasks to parallel computers with cellular networks. This new formulation significantly speeds up the solution process through consideration of the symmetries in the supply matrix of a network and a transformation of the demand matrix of any application. The extent of the speedup is not easily obtainable through analytical means for most production networks. However, numerical experiments of mapping wave equations on 2D mesh onto 3D torus networks by simulated annealing demonstrate a far superior convergence rate and quicker escape from local minima with our new formulation than with the standard graph theory-based one.
Comparing traditional malicious attack, embedding malicious codes into documents is becoming a more efficient and hidden way. The attackers embed the malicious codes into a document based on the document storage format so that they activate secretively when the document is opened by third-party software. With a simple action of double click the document, it could bring a nightmare to the user.Through researching and analyzing the structure of compound file, we mainly focus on the Word documents, and try to find out a method to detect them. We have used the bloom filter as well as the entropy rate of Markov chain and reached a high accuracy.Detect embedded malicious codes by analyzing the embedded codes themselves, because they are machine instructions which must can execute by CPU. A basic assumption is that the machine instructions in the document are different from the normal text, pictures, tables, etc. The basic direction of detection is to find the different areas in the document. Thus, we use the entropy rate as a measure to quantify this distinction.
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