The Failure of the Strong Pumping Lemma for Multiple Context-Free Languages

Seki et al. (Theor. Comput. Sci. 88(2):191–229, 1991) showed that every m-multiple context-free language L is weakly 2m-iterative in the sense that either L is finite or L contains a subset of the form \(\{ u_{0} w_{1}^{i} u_{1} \cdots w_{2m}^{i} u_{2m} \mid i \in \mathbb {N}\}\) , where w ₁?w _2n ≠ε. Whether every m-multiple context-free language L is 2m-iterative, that is to say, whether all but finitely many elements z of L can be written as z=u ₀ w ₁ u ₁?w _2m u _2m with w ₁?w _2m ≠ε and \(\{ u_{0} w_{1}^{i} u_{1} \cdots w_{2m}^{i} u_{2m} \mid i \in \mathbb {N}\} \subseteq L\) , has been open. We show that there is a 3-multiple context-free language that is not k-iterative for any k.     

Multi-modal Information Integration for Interactive Multi-agent Systems

This paper proposes a multi-agent system that carries out cooperative work. To achieve this, we use Fuzzy Associative Memory Organizing Unit Systems (FAMOUS) and Conceptual Fuzzy Sets (CFS). By using these proposed methods, each agent robot can decide its own behaviour to suit the situation in its environment. We apply this system to an Intelligent Transportation System (ITS) and do simulations.     

Effect of surface modification on NO2 sensing properties of SnO2 varistor-type sensors

NO₂ sensing properties of SnO₂-based varistor-type sensors have been investigated in the temperature range of 400-650°C and in the NO₂ concentration range of 15–30 ppm. Pure SnO₂ exhibited a weak nonlinear I–V characteristic in air, but clear nonlinearity in NO₂ at 450°C. The breakdown voltage of SnO₂ shifted to a high electric field upon exposure to NO₂ and the magnitude of the shift was well correlated with NO₂ concentration. Thus, SnO₂ exhibited some sensitivity to NO₂ as a varistor-type sensor. When SnO₂ particles coated with a SiO₂ thin film were used as a raw material for fabricating a varistor, the breakdown voltage in air was approximately the double that of pure SnO₂ and the sensitivity to 15 ppm NO₂ was enhanced slightly. However, the sensitivity to 30 ppm NO₂ decreased. The Cr₂O₃-loading on SnO₂ also led to an increase in the breakdown voltage in air, but the Cr₂O₃ addition was not effective for promoting the NO₂ sensitivity under the present experimental conditions.     

Non-uniqueness and symmetry of optimal topology of a shell for minimum compliance

Uniqueness and symmetry of solution are investigated for topology optimization of a symmetric continuum structure subjected to symmetrically distributed loads. The structure is discretized into finite elements, and the compliance is minimized under constraint on the structural volume. The design variables are the densities of materials of elements, and intermediate densities are penalized to prevent convergence to a gray solution. A path of solution satisfying conditions for local optimality is traced using the continuation method with respect to the penalization parameter. It is shown that the rate form of the solution path can be formulated from the optimality conditions, and the uniqueness and bifurcation of the path are related to eigenvalues and eigenvectors of the Jacobian of the governing equations. This way, local uniqueness and symmetry breaking process of the solution are rigorously investigated through the bifurcation of a solution path.     

The Lambek calculus enriched with additional connectives

Some formal properties of enriched systems of Lambek calculus with analogues of conjunction and disjunction are investigated. In particular, it is proved that the class of languages recognizable by the Lambek calculus with added intersective conjunction properly includes the class of finite intersections of context-free languages.I would like to thank Professor Johan van Benthem for much encouragement and a number of helpful suggestions. Thanks are also due to Dirk Roorda, who commented on an earlier draft of the paper, and to my advisor Professor Stanley Peters.     

Conservative reliability index for epistemic uncertainty in reliability-based design optimization

In this paper, a simple but efficient concept of epistemic reliability index (ERI) is introduced for sampling uncertainty in input random variables under conditions where the input variables are independent Gaussian, and samples are unbiased. The increased uncertainty due to the added epistemic uncertainty requires a higher level of target reliability, which is called the conservative reliability index (CRI). In this paper, it is assumed that CRI can additively be decomposed into the aleatory part (the target reliability index) and the epistemic part (the ERI). It is shown theoretically and numerically that ERI remains same for different designs, which is critically important for computational efficiency in reliability-based design optimization. Novel features of the proposed ERI include: (a) it is unnecessary to have a double-loop uncertainty quantification for handling both aleatory and epistemic uncertainty; (b) the effect of two different sources of uncertainty can be separated so that designers can better understand the optimization outcome; and (c) the ERI needs to be calculated once and remains the same throughout the design process. The proposed method is demonstrated with two analytical and one numerical examples.     

Sensor Fusion System Using Recurrent Fuzzy Inference

In robotic and manufacturing systems, it is difficult to measure the state of systems accurately because of many uncertain factors and noise, and it is very important to estimate the state of systems. We must measure the phenomena of systems by multiple sensors and estimate the state of systems by acquiring information of sensors. However, we can not acquire all of sensor information synchronically, because each sensor has particular sensor information and measuring time. For estimating the state of systems by multiple sensors, a multi-sensor fusion system fusing various sensory information is needed. In this paper, we propose a Recurrent Fuzzy Inference (RFI) with recurrent inputs and apply it to a multi-sensor fusion system for estimating the state of systems. The membership functions of RFI are expressed by Radial Basis Function (RBF) with insensitive ranges. The shape of the membership functions can be adjusted by a learning algorithm. The learning algorithm is based on the steepest descent method and incremental learning which can add new fuzzy rules. The effectiveness of the multi-sensor fusion system using RFI will be shown through a numerical experiment of moving robot and estimation of surface roughness in grinding process.     

MISCELA: discovering simultaneous and time-delayed correlated attribute patterns

This article addresses a new pattern mining problem in time series sensor data, which we call correlated attribute pattern mining. The correlated attribute patterns (CAPs for short) are the sets of attributes (e.g., temperature and traffic volume) on sensors that are spatially close to each other and temporally correlated in their measurements. Although the CAPs are useful to accurately analyze and understand spatio-temporal correlation between attributes, the existing mining methods are inefficient to discover CAPs because they extract unnecessary patterns. Therefore, we propose a mining method Miscela to efficiently discover CAPs. Miscela can discover not only simultaneous correlated patterns but also time delayed correlated patterns. Furthermore, we extend Miscela to automatically search for correlated patterns with any time delays. Through our experiments using three real sensor datasets, we show that the response time of Miscela is up to 20.84 times faster compared with the state-of-the-art method. We show that Miscela discovers meaningful patterns for urban managements and environmental studies.