Parameter identification and slip estimation of induction machine

This paper presents a newly developed algorithm for induction machine rotor speed estimation and parameter detection. The proposed algorithm is based on spectrum analysis of the stator current. The main idea is to find the best fit of motor parameters and rotor slip with the group of characteristic frequencies which are always present in the current spectrum. Rotor speed and parameters such as pole pairs or number of rotor slots are the results of the presented algorithm. Numerical calculations show that the method yields very accurate results and can be an important part of machine monitoring systems.     

Harnessing “Click”‐Type Chemistry for the Preparation of Novel Electronic Materials

Sequence‐independent or “click”‐type chemistry is applied for the preparation of novel π‐conjugated oligomers. A variety of bi‐functional monomers for Wittig–Horner olefination are developed and applied in a sequential protection–deprotection process for the preparation of structurally similar π‐conjugated oligomers. Selected oligomers are incorporated as the organic semiconductors in light‐emitting diodes and a field‐effect transistor, demonstrating the potential of the approach.     

Evolution of social learning when high expected payoffs are associated with high risk of failure

In an environment where the availability of resources sought by a forager varies greatly, individual foraging is likely to be associated with a high risk of failure. Foragers that learn where the best sources of food are located are likely to develop risk aversion, causing them to avoid the patches that are in fact the best; the result is sub-optimal behaviour. Yet, foragers living in a group may not only learn by themselves, but also by observing others. Using evolutionary agent-based computer simulations of a social foraging game, we show that in an environment where the most productive resources occur with the lowest probability, socially acquired information is strongly favoured over individual experience. While social learning is usually regarded as beneficial because it filters out maladaptive behaviours, the advantage of social learning in a risky environment stems from the fact that it allows risk aversion to be circumvented and the best food source to be revisited despite repeated failures. Our results demonstrate that the consequences of individual risk aversion may be better understood within a social context and suggest one possible explanation for the strong preference for social information over individual experience often observed in both humans and animals.     

On Stochastic Modeling of Interface Defects in Composite Materials

The article presents mathematical and computational research dealing with the problem of stochastic interface defects occurring in composite materials between their constituents. A mathematical model of the periodic composite with such defects is presented in detail, as well as probabilistic numerical methods enabling computational experiments which are shown in a further part of the text. The fiber-reinforced and laminated composite has been tested in numerical tests as well as the superconducting coil cable-four-component composite to verify how the structural defects considered, according to the model introduced, influence the static behavior of the composites analyzed. All the results obtained and discussed in the article are summarized in concluding remarks which show the directions of further model development, while numerous references enable the reader to study the problem further.     

Partition coefficients of environmentally important phenols in a supercritical carbon dioxide-water system from cocurrent extraction without analysis of the compressible phase

Partition coefficients of phenol, salicylic acid, and several environmentally important chloro- and nitrophenols in a supercritical CO2-water system were measured using direct cocurrent extraction of aqueous solutions of the individual solutes with CO2. Partitioning data on the nitrophenols and salicylic acid were obtained for the first time. To bypass the troublesome and error-prone analysis of the CO2-rich phase, the present method employed only the solute concentrations in the aqueous phase before and after extraction to determine the partition coefficient. Unlike most previous engineering studies of phenol partitioning in a CO2-water system, the concentrations of phenolic solutes approached infinite dilution in both phases. This makes the results relevant to analytical-scale SFE of environmental water samples with CO2. Because of effective infinite dilution of the solutes, the partition coefficients provide a direct measure of relative CO2-philicity/hydrophilicity of the individual phenols. Compared to the octanol-water partition coefficients of substituted phenols, the CO2-water partition coefficients are more sensitive to substitution in the position neighboring the hydroxyl group.     

ATR artificial brain project: 2004 progress report

This article presents the key assumptions and current status of the ATR Artificial Brain Project being undertaken to create Volitron, a device equipped with circuitry that enables the emergence of thought. Such thought would be recognized from Volitron's specific communication behaviors. The project consists of three complementary themes: psychodynamic architecture, brain-specific evolvable hardware, and the management of brain-building. The psychodynamic architecture is designed to develop automatically, driven by “pleasure” coming from discharges of tension gathered in special tension-accumulating devices. Tension-discharging patterns come first of all from the robot's interactions with its care giver/provider. For the dedicated hardware, we developed qcellular-automata (qCA), in which groups of uniform logic primitives (q-cells) serve as spike-train-processing units, as well as pulsed para-neural networks (PPNN) that can be evolved, using fuzzified signals and a genetic algorithm combined with hill climbing, and converted into qCA. The psychodynamic ideas were tested using three robots: Neko, equipped with a pleasure-driven associator, Miao, equipped with MemeStorms (a special working memory in which conflicting ideas fight for access to the long-term memory and actuators), and Miao+, whose brain is equipped with a growing neural network. This work was presented in part at the 9th International Symposium on Artificial Life and Robotics, Oita, Japan, January 28–30, 2004     

Characterization of Combinatorially Independent Permutation Separability Criteria

The so-called permutation separability criteria are simple operational conditions that are necessary for separability of mixed states of multipartite systems: (1) permute the indices of the density matrix and (2) check if the trace norm of at least one of the resulting operators is greater than one. If it is greater than one then the state is necessarily entangled. A shortcoming of the permutation separability criteria is that many permutations give rise to equivalent separability criteria. Therefore, we introduce a necessary condition for two permutations to yield independent criteria called combinatorial independence. This condition basically means that the map corresponding to one permutation cannot be obtained by concatenating the map corresponding to the second permutation with a norm-preserving map. We characterize completely combina-torially independent criteria, and determine simple permutations that represent all independent criteria. The representatives can be visualized by means of a simple graphical notation. They are composed of three basic operations: partial transpose, and two types of so-called reshufflings. In particular, for a four-partite system all criteria except one are composed of partial transpose and only one type of reshuffling; the exceptional one requires the second type of reshuffling. Furthermore, we show how to obtain efficiently a simple representative for every permutation. This method allows to check easily if two permutations are Combinatorially equivalent or not.     

Multi-Frame Correspondence Estimation Using Subspace Constraints

When a rigid scene is imaged by a moving camera, the set of all displacements of all points across multiple frames often resides in a low-dimensional linear subspace. Linear subspace constraints have been used successfully in the past for recovering 3D structure and 3D motion information from multiple frames (e.g., by using the factorization method of Tomasi and Kanade (1992, International Journal of Computer Vision, 9:137–154)). These methods assume that the 2D correspondences have been precomputed. However, correspondence estimation is a fundamental problem in motion analysis. In this paper we show how the multi-frame subspace constraints can be used for constraining the 2D correspondence estimation process itself.We show that the multi-frame subspace constraints are valid not only for affine cameras, but also for a variety of imaging models, scene models, and motion models. The multi-frame subspace constraints are first translated from constraints on correspondences to constraints directly on image measurements (e.g., image brightness quantities). These brightness-based subspace constraints are then used for estimating the correspondences, by requiring that all corresponding points across all video frames reside in the appropriate low-dimensional linear subspace.The multi-frame subspace constraints are geometrically meaningful, and are {not} violated at depth discontinuities, nor when the camera-motion changes abruptly. These constraints can therefore replace {heuristic} constraints commonly used in optical-flow estimation, such as spatial or temporal smoothness.