Diffusion and propagation in triangular Lorentz lattice gas cellular automata

The diffusion process of point particles moving on regular triangular and random lattices, randomly occupied with stationary scatterers (a Lorentz lattice gas cellular automaton), is studied, for strictly deterministic scattering rules, as a function of the concentration of the scatterers. In addition to the normal and various kinds of retarded diffusion found before on the regular square lattice, straight-line propagation through the scatterers is observed.     

修正积分水平集方法的随机实现算法

本文提出了一个从随机到确定性的变测度算法，通过对不同的箱子采用不同的测度，将Monte-Carlo随机投点与确定性数论方法相结合的策略，使水平值充分地下降．最后，给出了实现算法收敛性并通过数值实验验证了其有效性．     

基于最小自由度优先原则的任意多边形模块布局算法

给出了直角多边形模块自由度的定义和公式,扩展了最小自由度优先原则,使算法能够处理任意直角多边形模块以及有相对约束的模块.实验结果说明该方法在布局效果和效率上都有良好的表现     

Stochastic control for a class of random evolution models

We construct the explicit connection existing between a solvable model of the discrete velocities non-linear Boltzmann equation and the Hamilton-Bellman-Jacobi equation associated with a simple optimal control of a piecewise deterministic process. This study extends the known relation that exists between the Burgers equation and a simple controlled diffusion problem. In both cases the resulting partial differential equations can be linearized via a logarithmic transformation and hence offer the possibility to solve physically relevant non-linear field models in full generality.     

Neighborhood Portfolio Approach for Local Search Applied to Timetabling Problems

A recent trend in local search concerns the exploitation of several different neighborhoods so as to increase the ability of the algorithm to navigate the search space. In this work we investigate a hybridization technique, that we call Neighborhood Portfolio Approach, that consists in the interleave of local search techniques based on various combinations of neighborhoods. In particular, we are able to select the most effective search technique through a systematic analysis of all meaningful combinations built upon a set of basic neighborhoods. The proposed approach is applied to two practical problems belonging to the timetabling family, and systematically tested and compared on real-world instances. The experimental analysis shows that our approach leads to automatic design of new algorithms that provide better results than basic local search techniques.     

Very High-Speed True Random Noise Generator

In this work an original CMOS implementation of a discrete-time deterministic-chaos algorithm for random bit generation is presented. The proposed circuit topology prevents the degradation of the generated-sequence statistical properties that can be caused by several factors, including the parameter spreading of the technological processes. Experimental results show that, with a final rate of 3 Mbit/s, the circuit is compliant with the most recent security requirements for cryptographic modules issued by the American National Institute of Standards and Technologies.     

状态不可观测的信息物理融合系统运行时验证

确保信息物理融合系统（Cyber-Physical System,CPS）运行时行为正确性是至关重要的,尤其在航空航天、汽车、核电和医疗等安全攸关领域.本文针对具有随机行为且状态不可观测的CPS,提出一种基于隐马尔科夫模型的运行时安全性验证方法.首先构造状态不可观测的CPS运行时安全性验证框架,该框架通过隐马尔科夫模型表示系统,使用确定性有限自动机规约系统安全属性的否定,两者的乘积自动机作为运行时监控器,从而将CPS运行时安全性验证问题约简到监控器上的概率推断问题.然后,提出一种增量迭代安全性验证算法以及反例生成算法.实验结果表明本文算法和粒子滤波算法相比预测错误率下降了近20%,并且当系统违背安全属性时,本文的方法能给出反例.     

Prediction of Oligopeptide Conformations via Deterministic Global Optimization

A deterministic global optimization method is described for identifying the global minimum potential energy conformation of oligopeptides. The ECEPP/3 detailed potential energy model is utilized for describing the energetics of the atomic interactions posed in the space of the peptide dihedral angles. Based on previous work on the microcluster and molecular structure determination [21, 22, 23, 24], a procedure for deriving convex lower bounding functions for the total potential energy function is developed. A procedure that allows the exclusion of domains of the (ø, ) space based on the analysis of experimentally determined native protein structures is presented. The reduced disjoint sub-domains are appropriately combined thus defining the starting regions for the search. The proposed approach provides valuable information on (i) the global minimum potential energy conformation, (ii) upper and lower bounds of the global minimum energy structure and (iii) low energy conformers close to the global minimum one. The proposed approach is illustrated with Ac-Ala4-Pro-NHMe, Met-enkephalin, Leu-enkephalin, and Decaglycine.     

Determining Aliasing Probabilities in BIST by Counting Strings

The aliasing probability (AP) of a Built-In Self-Test (BIST)architecture is the probability that an error response gets classified as agood response. A general technique to determine the AP for many common andalternative BIST response analysis (RA) architectures is presented here.This technique models the RA circuit as a Deterministic Finite Automaton(DFA), and determines the AP by counting the ratio of strings accepted bythe DFA to the total number of possible error strings. The strings acceptedby a DFA can be calculated by counting the paths in the DFAs statetransition graph (STG). Moreover, if the STG is complete, then theAP(k) = ((1/N)N^k-1)/(N^k-1), where k is the testlength and N is the number of states and input symbols. Thistechnique is demonstrated by determining the APs for the following RAarchitectures: Multiple-Input Shift Registers (MISRs), Cellular Automata(CA), Linear Feedback Shift Registers (LFSRs), accumulators, and a set ofalternative architectures directly based on DFAs. This paper also shows howthe adjacency matrix of the STG can be used to directly determine the AP ofany RA architecture modeled as a DFA. Finally, the eigenvalues andeigenvectors of the DFAs STG adjacency matrix are used to derive generalexpressions for the DFAs AP.