Compact Reconfigurable Binary-Decision-Diagram Logic Circuit on a GaAs Nanowire Network

We describe a reconfigurable binary-decision-diagram logic circuit based on Shannon's expansion of Boolean logic function and its graphical representation on a semiconductor nanowire network. The circuit is reconfigured by using programmable switches that electrically connect and disconnect a small number of branches. This circuit has a compact structure with a small number of devices compared with the conventional look-up table architecture. A variable Boolean logic circuit was fabricated on an etched GaAs nanowire network having hexagonal topology with Schottky wrap gates and SiN-based programmable switches, and its correct logic operation together with dynamic reconfiguration was demonstrated.

基于BDD的增量启发式搜索

增量搜索是一种利用先前的搜索信息提高本次搜索效率的方法,通常可以用来解决动态环境下的重规划问题.在人工智能领域,一些实时系统常常需要根据外界环境的变化不断修正自身,这样就会产生一系列变化较小的相似问题,此时应用增量搜索将会非常有效.另外,基于BDD(binary decision diagram)的启发式搜索,结合了基于BDD的搜索和启发式搜索这两种方法的优点.它既用BDD这一紧凑的数据结构来表示系统的状态空间,又通过使用启发信息来进一步压缩搜索树的大小.在介绍基于BDD的启发式搜索和增量搜索之后,结合这两种方法给出了基于BDD的增量启发式搜索算法——BDDRPA*.大量的实验结果表明,BDDRPA*算法是非常有效的,它可以被广泛地应用到智能规划、移动机器人问题等领域中.

Applications on fault tree analysis in railway power supply systems

Fault tree analysis (FTA) is presented to model the reliability of a railway traction power system in this paper. First, the construction of fault tree is introduced to integrate components in traction power systems into a fault tree; then the binary decision diagram (BDD) method is used to evaluate fault trees qualitatively and quantitatively. The components contributing to the reliability of overall system are identified with their relative importance through sensitivity analysis. Finally, an AC traction power system is evaluated by the proposed methods.

A novel Information sharing model using binary decision diagrams for redundancy, shadowing, generalisation and correlation.

This paper outlines a novel information sharing method using Binary Decision Diagrams (BBDs). It is inspired by the work of Al-Shaer and Hamed, who applied BDDs into the modelling of network firewalls. This is applied into an information sharing policy system which optimizes the search of redundancy, shadowing, generalisation and correlation within information sharing rules.

Evaluation of binary decision diagrams for redundancy, shadowing, generalisation and correlation in an Information sharing model.

This paper defines a structured methodology which is based on the foundational work of Al-Shaer et al. in [1] and that of Hamed and Al-Shaer in [2]. It defines a methodology for the declaration of policy field elements, through to the syntax, ontology and functional verification stages. In their works of [1] and [2] the authors concentrated on developing formal definitions of possible anomalies between rules in a network firewall rule set. Their work is considered as the foundation for further works on anomaly detection, including those of Fitzgerald et al. [3], Chen et al. [4], Hu et al. [5], among others. This paper extends this work by applying the methods to information sharing policies, and outlines the evaluation related to these.

Using Sensitivity as a Method for Ranking the Test Cases Classified by Binary Decision Trees

Usually, data mining projects that are based on decision trees for classifying test cases will use the probabilities provided by these decision trees for ranking classified test cases. We have a need for a better method for ranking test cases that have already been classified by a binary decision tree because these probabilities are not always accurate and reliable enough. A reason for this is that the probability estimates computed by existing decision tree algorithms are always the same for all the different cases in a particular leaf of the decision tree. This is only one reason why the probability estimates given by decision tree algorithms can not be used as an accurate means of deciding if a test case has been correctly classified. Isabelle Alvarez has proposed a new method that could be used to rank the test cases that were classified by a binary decision tree [Alvarez, 2004]. In this paper we will give the results of a comparison of different ranking methods that are based on the probability estimate, the sensitivity of a particular case or both.

On some Properties of Boolean Functions and Their Binary Decision Diagrams

Иво Й. Дамянов - Манипулирането на булеви функции е основнo за теоретичната информатика, в това число логическата оптимизация, валидирането и синтеза на схеми. В тази статия се разглеждат някои първоначални резултати относно връзката между граф-базираното представяне на булевите функции и свойствата на техните променливи.

Bayesian and Decision Tree Approaches for Pattern Recognition Including Feature Measurement Costs

The minimum cost classifier when general cost functionsare associated with the tasks of feature measurement and classification is formulated as a decision graph which does not reject class labels at intermediate stages. Noting its complexities, a heuristic procedure to simplify this scheme to a binary decision tree is presented. The optimizationof the binary tree in this context is carried out using ynamicprogramming. This technique is applied to the voiced-unvoiced-silence classification in speech processing.

Delayed-decision making in noisy bistable switches

Bistable switches are frequently encountered in biological systems. Typically, a bistable switch models a binary decision where each decision corresponds to one of the two stable equilibria. Recently, we showed that the global decision-making process in bistable switches strongly depends on a particular equilibrium point of these systems, their saddle point. In particular, we showed that a saddle point with a time-scale separation between its attractive and repulsive directions can delay the decision-making process. In this paper, we study the effects of white Gaussian noise on this mechanism of delayed decision-making induced by the saddle point. Results show that the mean decision-time strongly depends on the balance between the initial distance to the separatrix and the noise strength. © IFAC.

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.

Multiclass Adaboost Based on an Ensemble of Binary Adaboosts

This paper presents a multi-class AdaBoost based on incorporating an ensemble of binary AdaBoosts which is organized as Binary Decision Tree (BDT). It is proved that binary AdaBoost is extremely successful in producing accurate classification but it does not perform very well for multi-class problems. To avoid this performance degradation, the multi-class problem is divided into a number of binary problems and binary AdaBoost classifiers are invoked to solve these classification problems. This approach is tested with a dataset consisting of 6500 binary images of traffic signs. Haar-like features of these images are computed and the multi-class AdaBoost classifier is invoked to classify them. A classification rate of 96.7% and 95.7% is achieved for the traffic sign boarders and pictograms, respectively. The proposed approach is also evaluated using a number of standard datasets such as Iris, Wine, Yeast, etc. The performance of the proposed BDT classifier is quite high as compared with the state of the art and it converges very fast to a solution which indicates it as a reliable classifier.

Phase relations in the system Ta-Rh-O and thermodynamic properties of TaRhO4

Phase relations in the system Ta-Rh-O were determined by analysis of quenched samples corresponding to thirteen compositions inside the ternary triangle after equilibration at 1273 K. All the Ta-Rh alloys were found to be in equilibrium with Ta2O5. Only one ternary oxide TaRhO4 was detected. Based on phase relations in the ternary system, a solid-state electrochemical cell, incorporating calcia-stabilized zirconia as the electrolyte, was designed to measure the standard Gibbs energy of formation (Delta G degrees, J mol(-1)) of TaRhO4 in the temperature range from 900 to 1300 K. For the reaction, 1/2 beta-Ta2O5 + 1/2 Rh2O3(ortho) -> TaRhO4 Delta G degrees = -42993 + 5.676T (+/- 85) The calculated decomposition temperatures of TaRhO4 are 1644 +/- 5K in pure O-2 and 1543 +/- 5K in air at a total pressure p(o) = 0.1 MPa. Thermodynamic properties of TaRhO4 at 298.15K have been evaluated from the results. The limited experimental thermodynamic data for Rh-rich alloys available in the literature are in fair accord with Miedema's model. The Gibbs energies of formation of the different phases in the binary system Ta-Rh were estimated based on these inputs, consistent with the binary phase diagram. Based on the thermodynamic information on the stability of various phases, an oxygen potential diagram for the system Ta-Rh-O at 1273K was constructed. Also presented are temperature-composition diagrams for the ternary system at constant oxygen partial pressures (po(2)/p(o) = 0.212 and 10(-6)) calculated form the basic data.

Size dependent microstructure for Ag-Ni nanoparticles

The Ag-Ni system is characterized by large differences in atomic sizes (14%) and a positive heat of mixing (+23 kJ mol(-1)). The binary equilibrium diagram for this system therefore exhibits a large miscibility gap in both solid and liquid state. This paper explores the size-dependent changes in microstructure and the suppression of the miscibility gap which occurs when free alloy particles of nanometer size are synthesized by co-reduction of Ag and Ni metal precursors. The paper reports that complete mixing between Ag and Ni atoms could be achieved for smaller nanoparticles (<7 nm). These particles exhibit a single-phase solid solution with face-centered cubic (fcc) structure. With increase in size, the nanoparticles revealed two distinct regions. One of the regions is composed of pure Ag. This region partially surrounds a region of fcc solid solution at an early stage of decomposition. Experimental observations were compared with the results obtained from the thermodynamic calculations, which compared the free energies corresponding to a physical mixture of pure Ag and Ni phases and a fcc Ag-Ni solid solution for different particle sizes. Results from the theoretical calculations revealed that, for the Ag-Ni system, solid solution was energetically preferred over the physical mixture configuration for particle sizes of 7 nm and below. The experimentally observed two-phase microstructure for larger particles was thus primarily due to the growth of Ag-rich regions epitaxially on initially formed small fcc Ag-Ni nanoparticles. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

System Gd-Rh-O: Thermodynamics and phase relations

Thermodynamic properties of GdRhO3 are investigated in the temperature range from 900 to 1300 K by employing a solid-state electrochemical cell, incorporating calcia-stabilized zirconia as the electrolyte. The standard Gibbs free energy of formation of GdRhO3 from component binary oxide Gd2O3 with C-rare earth structure and Rh2O3 with orthorhombic structure can be expressed as; Delta G(f(ox))(o)(+/- 60)/J mol(-1) = -56603 + 3.78(T/K) Based on the thermodynamic information on GdRhO3 from experiment and auxiliary data for binary oxides from the literature and estimated properties of Gd-Rh alloys, phase relations are computed for the system Gd-Rh-O at 1273 K. Gibbs free energies for intermetallic phases in the binary Gd-Rh are evaluated using calorimetric data available in the literature for two compositions and Miedema's model, consistent with the binary phase diagram. Isothermal section of the ternary phase diagram, oxygen potential-composition diagram and a 3-D chemical potential diagram for the system Gd-Rh-O at 1273 K are developed. Phase relations in the ternary Gd-Rh-O are also computed as a function of temperature at constant oxygen partial pressures. The ternary oxide, GdRhO3 decomposes to Gd2O3 with B-rare earth structure, metallic Rh and O-2 at 1759(+/- 2) K in pure O-2 and 1649(+/- 2) K in air at a total pressure P-0 -0.1 MPa. (c) 2012 Elsevier B.V. All rights reserved.

Chess endgame news

News that Bourzutschky confirms there is no sub-7-man pawnless zugzwang, and that Bourzutschky and Konoval are generating DTC EGTs with a new program. News also of Kristensen's work on EGTs using OBDDs, Ordered Binary Decision Diagrams.