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Paper is non-uniform; thus, it is difficult to ascertain whether the slight differences in near-infrared absorption spectra are caused by the difference in paper type or the paper’s non-uniformity. We used near-infrared hyperspectral imaging to measure the spectra of many different points quickly for eight different paper samples. Next, we analysed the data using machine learning and constructed a model to ascertain whether the differences in the spectra are due to the difference in paper type or the paper’s non-uniformity. Even papers with very similar spectral shapes were distinguished with high accuracy with this method. As the number of spectra used to construct the classification model increased, the accuracy of the classification model increased. With 6840 spectra per sample, the accuracy exceeded 85%, and with 68,400 spectra per sample, the accuracy for identification was 87.8%.

This study investigated the effects of bending curvature of simulated e-paper displays (−10 cm, plane and 10 cm) and ambient illuminance (50, 500, 6000 and 12,000 lx) on the visual performance of young and elderly users for simulated electronic-paper displays. In total, 24 people comprising 12 young and 12 elderly users participated in this study. Young users demonstrated significantly enhanced visual performance using the simulated electrophoretic ink (E ink) e-paper display with ambient illuminance set at 50 and 500 lx; however, participants did not demonstrate significantly different visual performance using the 2 simulated e-paper displays with ambient illuminance set at 6000 and 12,000 lx. The bending curvature did not exhibit significant effects on the visual performance of young participants under various ambient illuminances. The elderly participants exhibited significantly enhanced visual performance using the simulated E ink e-paper display only when ambient illuminance was set at 50 lx; however, participants did not exhibit significantly different visual performance using the two simulated e-paper displays with ambient illuminance set at other levels. Elderly users exhibited significantly enhanced visual performance when the bending curvature was set at 10 cm, with ambient illuminance set at 50 lx. Elderly users also demonstrated significantly enhanced visual performance under bending curvature settings of 10 cm and plane, with ambient illuminance set at 500 lx. However, the bending curvature of the simulated e-paper did not exhibit significant effects on the visual performance of elderly participants under ambient illuminance settings of 6000 and 12,000 lx.

Multi-sensor object detection and tracking on a highway scene with radar measurements is presented. The estimation algorithm is the random finite set based Bernoulli filter, working in the Bayesian framework. The recursion for calculating the Bayes estimation is implemented as a particle filter. A method is presented for calculating the likelihoods, suitable for particle filtering performed with moving sensors, assuming additive Gaussian measurement noise. In our approach, for calculating the posterior estimate of the object state, the measurement likelihoods are computed in the state space, instead of the measurement space, by mapping each measurement to the global coordinate system. The map consists of a nonlinear and an affine part. While the affine transformation trivially preserves the Gaussian nature, the nonlinear is well-proven to be approximated as affine too. This approach allows the particles to be drawn directly from the state space, hence the evaluation of the measurement model is not needed, which saves computational power.

Effects of character size under ambient illuminances and light sources on legibility of electronic paper displays (electrophoretic display and cholesteric liquid crystal display) were studied and compared with paper. Sixty subjects participated in a letter-search task in the experiment. The results showed that search speed depends on the illuminance but not light source. Search speed increased as the illuminance increase from 300, 700 to 1500 lx. Search speed also increased with the increase of character size, from character height of 1.4 mm (9.6 min visual angle), 2.2 mm (15.1 min visual angle) to 3.3 mm (22.7 min visual angle), and the increase leveled off at 4.3 mm (29.6 min visual angle). The effect of character size on accuracy was also significant. Accuracy increased with the increase of character size. However, the effect of illuminance and light source on accuracy was not statistically significant. Based on the results of this study, it seems that E-paper displays may need greater illumination (700 lx or higher), greater character size (3.3 mm or 22 min of visual angle).

This second part (out of three) of a series of position papers on triangular norms (for Part I see Triangular norms. Position paper I: basic analytical and algebraic properties, Fuzzy Sets and Systems, in press) deals with general construction methods based on additive and multiplicative generators, and on ordinal sums. Also included are some constructions leading to non-continuous t-norms, and a presentation of some distinguished families of t-norms.

In this position paper, we shall undertake a critical scrutiny of the decision analysis (DA) paradigm on the basis of experience we gained from working on the bullwhip effect. We had some success with sorting out the complexities of the bullwhip by using fuzzy numbers in the bullwhip models, and we found out that this points the way to a more viable approach to sort out complex decision problems. As a positive criticism of the DA paradigm we have collected the insights we have gained in an agenda for soft decision analysis (SDA), which we hasten to add is not complete but--hopefully--an opening for focused research and continuing development.

We present the basic analytical and algebraic properties of triangular norms. We discuss continuity as well as the important classes of Archimedean, strict and nilpotent t-norms. Triangular conorms and De Morgan triples are also mentioned. Finally, a brief historical survey on triangular norms is given.

In this paper we introduce a notion of a t-filter on residuated lattices which is a generalization of several special types of filters. We provide some basic properties of t-filters and show how particular results about special types of filters (e.g. Extension property, Triple of equivalent characteristics, and Quotient characteristics) are uniformly covered by this simple general framework.

In the present work, the analytical potential of laser induced breakdown spectroscopy (LIBS) for the discrimination of paper types and prints made by digital printers on these papers was assessed. Six different paper types (including standard office papers, color paper and non-bleached paper), and eight printers (including laser and inkjet, as well as color and black printers) were included in the study. Only one or two laser shots were delivered to each sample in order to cause minimal sample destruction and provide maximum spatial resolution. The statistical evaluation of LIBS spectra was performed by multiple methods including three comparative functions (linear correlation, sum of squared deviations and overlapping integral) as well as two advanced statistical methods (multivariate curve resolution alternating least squares (MCR-ALS) combined with classification tree and discriminant analysis (DA)). The best classification results were obtained with the newly introduced MCR-ALS/DA approach, which proved to be 96.3% accurate in the identification of the paper type and 83.3% accurate in the identification of the printer type, based on the LIBS spectrum collected from just a single laser shot to the sample. It was found that the UV part of the LIBS spectrum can be used most efficiently for the discrimination.

We illustrate the Efficient Forward Filtering Backward Smoothing (EFFBS) algorithm proposed by Khreich et al. (2010) for estimation of hidden Markov models. The algorithm is aimed at reducing the amount of memory required by the Baum-Welch recursions, while having the same complexity in terms of number of operations. In implementing the EFFBS algorithm we found a numerical problem that limits its applicability. We discuss this problem in detail, providing some possible explanations of the causes of the error, together with two illustrative examples.

In this paper, we describe the development of a system for evaluating an specific quality characteristic of recycled paper sheets using techniques of image analysis and pattern recognition. We call Bumpiness the phenomenon of interest, which is new in the literature on paper quality. This phenomenon is characterized by the appearance of macroscopic undulations on the paper sheet surface that may emerge shortly or some time after its production. We explore the detection and measurement of this defect by means of computer vision and statistical pattern recognition techniques that may allow early detection at the production site. Our goal is to give an scalar continuous measure of Bumpiness. We propose features computed from Gabor filter banks (GFB) and discrete wavelet transforms (DWT) for the characterization of paper sheet surface Bumpiness in recycled paper images. The starting point is to state the problem as a classification of the paper sheet images into two classes: low and high Bumpiness. In this setting we obtain, with both proposed texture modelling approaches (GFB and DWT), classification accuracies comparable to the agreement between human observers. The best performance is obtained using DWT features. Finally, we propose as the scalar index of Bumpines the fisher discriminant analysis (FDA) function defined on the space of the best features for the classification task. We perform an innovative validation process of this Bumpiness index, based on the ordering of random pairs of images, obtaining a very high agreement with the human observers.

The study used the simulated e-paper to investigate how the bending radius of curvature (−10 cm, plane, and 10 cm) and 12 text/background color-combinations of e-paper affect subjects’ visual performance and subjective preference under various ambient illuminance conditions (200 and 500 lx). Analysis results indicated that the bending curvature and ambient illuminance did not significantly affect subjects’ visual performance. However, subjects visual performance differed significantly for different text/background color combinations of the simulated e-paper. When the background color of the simulated e-paper was set to yellow-like condition and the luminance of the text was low (2.2 and 4.6 cd/m 2 ), subjects’ visual performance was best. Regarding the subjective preferences of subjects, the results of this research also demonstrated that the bending curvature, text/background color combinations and ambient illuminance all significantly affected the subjective preferences of subjects. Subjects exhibited the best preference under the following settings: bending curvature of the simulated e-paper set to plane; background color of the simulated e-paper set to yellow-like condition and low text luminance (2.2 or 4.6 cd/m 2 ); high ambient illuminance (500 lx).

Two players of Rock-Paper-Scissors are modeled as adaptive agents which use a reinforcement learning algorithm and exhibit chaotic behavior in terms of trajectories of probability in mixed strategies space. This paper demonstrates that an external super-agent can exploit the behavior of the other players to predict favorable moments to play against one of the other players the symbol suggested by a sub-optimal strategy. This third agent does not affect the learning process of the other two players, whose only goal is to beat each other. The choice of the best moment to play is based on a threshold associated with the Local Lyapunov Exponent or the Entropy, each computed by using the time series of symbols played by one of the other players. A method for automatically adapting such a threshold is presented and evaluated. The results show that these techniques can be used effectively by a super-agent in a game involving adaptive agents that exhibit collective chaotic behavior.

This third and last part of a series of position papers on triangular norms (for Parts I and II see (E.P. Klement, R. Mesiar, E. Pap, Triangular norms, Position paper I: basic analytical and algebraic properties, Fuzzy Sets and Systems, in press; E.P. Klement, R. Mesiar, E. Pap, Triangular norms. Position paper II: general constructions and parameterized families, submitted for publication) presents the representation of continuous Archimedean t-norms by means of additive generators, and the representation of continuous t-norms by means of ordinal sums with Archimedean summands, both with full proofs. Finally some consequences of these representation theorems in the context of comparison and convergence of continuous t-norms, and of the determination of continuous t-norms by their diagonal sections are mentioned.

Given a propositional theory T and a proposition q , a sufficient condition of q is one that will make q true under T , and a necessary condition of q is one that has to be true for q to be true under T . In this paper, we propose a notion of strongest necessary and weakest sufficient conditions. Intuitively, the strongest necessary condition of a proposition is the most general consequence that we can deduce from the proposition under the given theory, and the weakest sufficient condition is the most general abduction that we can make from the proposition under the given theory. We show that these two conditions are dual ones, and can be naturally extended to arbitrary formulas. We investigate some computational properties of these two conditions and discuss some of their potential applications.

In this paper we present a new semantics, called Local Models Semantics, and use it to provide a foundation to reasoning with contexts. This semantics captures and makes precise the two main intuitions underlying contextual reasoning: (i) reasoning is mainly local and uses only part of what is potentially available (e.g., what is known, the available inference procedures), this part is what we call context (of reasoning); however (ii) there is compatibility among the reasoning performed in different contexts. We validate our semantics by formalizing two important forms of contextual reasoning: reasoning with viewpoints and reasoning about belief.

In this communication, we will point out an interesting correspondence between a recent paper “On the properties of equidifferent OWA operator” [International Journal of Approximate Reasoning, in press, doi:10.1016/j.ijar.2005.11.003 ] by Liu, and an earlier result “On obtaining minimal variability OWA operator weights” [Fuzzy Sets and Systems 136 (2003) 203–215] by Fuller and Majlender.

This brief paper addresses problems that were raised in the paper (Fuzzy Sets and Systems, this issue) in connection with modelling fuzzy equality and similarity. In addition to specific comments to the cited paper, we also point out the more fundamental questions underlying this discussion.

The purpose of this note is to correct two convergence theorems for the generalized fuzzy integrals given in Fang [On the convergence theorems of generalized fuzzy integral sequence, Fuzzy Sets and Systems 124 (2001) 117-123].

In reply to Dubois and colleagues, here it is discussed the relationship between the notion of intuitionistic fuzzy set as proposed by the author in 1983 and the notion proposed in 1984 by Takeuti and Titani under the same name. It is demonstrated also the main direction of research, which does not (and in some cases, cannot) have analogues in fuzzy sets theory.

The problem of ‘structure from motion’ concerns the reconstruction of the three-dimensional structure of a scene from its projection onto a moving two-dimensional surface. Such a problem is solved effectively by the human visual system, judging from the ease with which we perform delicate control tasks involving vision as a sensor such as reaching for objects in the environment or driving a car. In this paper we study ‘structure from motion’ from the point of view of dynamical systems: we first formalize the problem of 3-D structure and motion reconstruction as the estimation of the state of certain nonlinear dynamical models. Then we study the feasibility of ‘structure from motion’ by analyzing the observability of such models. The models that define the visual motion estimation problem for feature points in the Euclidean 3-D space are not locally observable; however, the non-observable manifold can be easily isolated by imposing metric constraints on the state space. One of the peculiarities of vision as a sensor is its richness , which can be a disadvantage when we are interested only in few of the unknown parameters. For instance, if we want to control the direction of heading of our car by measuring brightness values on our retina, we have to overcome the effects that the shape of the environment, its reflectance properties, illumination and other quantities have on our measurements. Invariance to undesired parameters can be achieved by appropriate modeling or by choice of representation of the parameter space. We propose and analyze models for 3-D structure that are independent of 3-D motion and vice versa. Estimating unknown parameters from such models amounts to the identification of nonlinear and implicit systems with parameters on differentiable manifolds, such as a sphere or the so-called essential manifold . © 1997 Elsevier Science Ltd.

In this paper we will show that certain networks called ‘ inhibition nets ’ may be regarded as cognitive agents drawing nonmonotonic inferences. It will be proven that the system CL (introduced by KLM in [Artificial Intelligence 44 (1990) 186–189]) of nonmonotonic logic is both sound and complete with respect to the inferences drawn by finite hierarchical inhibition nets. The latter class of inhibition nets is shown to correspond to the class of finite, normal, hierarchical logic programs concerning dynamics, and also to the class of binary, layered, input-driven artificial neural networks.

The nearest neighbor problem is that of preprocessing a set P of n data points in Rd so that, given any query point q, the closest point in P to q can be determined efficiently. In the chromatic nearest neighbor problem, each point of P is assigned a color, and the problem is to determine the color of the nearest point to the query point. More generally, given k⩾1, the problem is to determine the color occurring most frequently among the k nearest neighbors. The chromatic version of the nearest neighbor problem is used in many applications in pattern recognition and learning. In this paper we present a simple algorithm for solving the chromatic k nearest neighbor problem. We provide a query sensitive analysis, which shows that if the color classes form spatially well separated clusters (as often happens in practice), then queries can be answered quite efficiently. We also allow the user to specify an error bound ε⩾0, and consider the same problem in the context of approximate nearest neighbor searching. We present empirical evidence that for well clustered data sets, this approach leads to significant improvements in efficiency.

There are two well known transformations from non-binary constraints to binary constraints applicable to constraint satisfaction problems (CSPs) with finite domains: the dual transformation and the hidden (variable) transformation. We perform a detailed formal comparison of these two transformations. Our comparison focuses on two backtracking algorithms that maintain a local consistency property at each node in their search tree: the forward checking and maintaining arc consistency algorithms. We first compare local consistency techniques such as arc consistency in terms of their inferential power when they are applied to the original (non-binary) formulation and to each of its binary transformations. For example, we prove that enforcing arc consistency on the original formulation is equivalent to enforcing it on the hidden transformation. We then extend these results to the two backtracking algorithms. We are able to give either a theoretical bound on how much one formulation is better than another, or examples that show such a bound does not exist. For example, we prove that the performance of the forward checking algorithm applied to the hidden transformation of a problem is within a polynomial bound of the performance of the same algorithm applied to the dual transformation of the problem. Our results can be used to help decide if applying one of these transformations to all (or part) of a constraint satisfaction model would be beneficial.

Symmetry often appears in real-world constraint satisfaction problems, but strategies for exploiting it are only beginning to be developed. Here, a framework for exploiting symmetry within depth-first search is proposed, leading to two heuristics for variable selection and a domain pruning procedure. These strategies are then applied to two highly symmetric combinatorial problems, namely the Ramsey problem and the generation of balanced incomplete block designs. Experimental results show that these general-purpose strategies can compete with, and in some cases outperform, previous more ad hoc procedures.

Some Virtues of possibilistic previsions introduced by Gert de Cooman in the paper A behavioural model for vague probability assesments are pointed out from the application point of view. A member of questions concerning extensions of the possibilistic previsions are posed.

We discuss various epistemological, foundational and practical aspects concerning the treatment of uncertainty, expressing the opinion that the approach followed in de Cooman's paper is neither useful nor convincing.

Monotonic logic requires reexamination of the entirety of a logic string when there is a contradiction. Nonmonotonic logic allows the user to withdraw conclusions in the face of contradiction without harm to the logic string. This attribute has considerable application to the field of information searching. Artificial intelligence models and neural networks based on nonmonotonic logic have the potential for more robust findings than the use of monotonic logic alone. This paper demonstrates the power of nonmonotonic logic but does not implement the logic.

We discuss two papers [Spong, M. W. (1989) Syst. Control. Lett. , 13 , 15–21; Chang, Y.-Z. and R. W. Daniel (1992) Automatica , 28 , 969–974] on the adaptive control of flexible joint robot manipulators. Our goal is to clarify the contributions of the two papers by correcting some technical errors and to provide some additional insight into the application of singular perturbation methods for the control of flexible joint robots.

Sandewall (1986) presents a theory of multiple inheritance with exceptions (also called non- monotonic inheritance) based on a set of nonmonotonic inference rules, taking advantage at the same time of theories based on nonmonotonic logic as proposed by Etherington and Reiter and of path-based theories as proposed by Touretzky, Horty and Thomason. Flaws in Sandewall's set of rules are shown and a revised set of rules is proposed. This revised set is shown to provide the same conclusion sets on a hierarchy as path-based theories for three classical variants of preclusion. Moreover, although most approaches to inheritance leave it in the metalanguage, it is shown that putting preclusion in the object language provides extensions with desirable general properties which are not always true in the restricted language of conclusion sets.

We correct a fundamental formula from paper ''A Robust Real-Time Ellipse Detector'' by Zhang and Liu published in journal ''Pattern Recognition'' in 2005.

The parameters of the models described by Rumelhart and Greeno in this journal (1971) are constrained in certain ways. Neglect of this fact in their paper leads them to an inadmissible set of parameter values, and an invalid argument and statement concerning the equivalence of two models. However, their conclusion that the Restle model fits their data better than the Luce model remains unchanged.

We show that slight technical changes in the definition transform the probability of fuzzy events introduced by R. R. Yager [16] into a new concept of such probabilities having nice properties, both from an intuitive and from a mathematical point of view: monotonicity, additivity, and continuity.

On each trial Ss viewed one of the patterns of six connected squares that result when the faces of a cube are unfolded onto a flat surface. The Ss tried, as rapidly as possible, to decide whether two arrows, each marked on an edge of a (different) square, would or would not meet if the squares were folded back up into the cube. The time required to make such decisions increased linearly (from 2 to about 15 sec) with the sum of the number of squares that would be involved in each fold, if those folds were actually performed physically.

For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms; (ii) to establish well-formalized models for elements combining randomness and fuzziness; (iii) to develop uni- and multivariate statistical methodologies to handle fuzzy-valued data; and (iv) to incorporate fuzzy sets to help in solving traditional statistical problems with non-fuzzy data. In spite of a growing literature concerning the development and application of fuzzy techniques in statistical analysis, the need is felt for a more systematic insight into the potentialities of cross fertilization between Statistics and Fuzzy Logic. In line with the synergistic spirit of Soft Computing, some instances of the existing research activities on the topic are recalled. Particular attention is paid to summarize the papers gathered in this Special Issue, ranging from the position paper on the theoretical management of uncertainty by the "father" of Fuzzy Logic to a wide diversity of topics concerning foundational/methodological/applied aspects of the integration of Fuzzy Sets and Statistics. (C) 2006 Elsevier B.V. All rights reserved.

Maximally stable component detection is a very popular method for feature analysis in images, mainly due to its low computation cost and high repeatability. With the recent advance of feature-based methods in geometric shape analysis, there is significant interest in finding analogous approaches in the 3D world. In this paper, we formulate a diffusion-geometric framework for stable component detection in non-rigid 3D shapes, which can be used for geometric feature detection and description. A quantitative evaluation of our method on the SHREC'10 feature detection benchmark shows its potential as a source of high-quality features.

In this position paper, we argue that when we are looking for the best fuzzy logic, we should specify in what sense the best, and that we get different fuzzy logics as ''the best'' depending on what optimality criterion we use.

The systems and concepts described in this paper document the evolution of the geometric invariance approach to object recognition over the last five years. Invariance overcomes one of the fundamental difficulties in recognising objects from images: that the appearance of an object depends on viewpoint. This problem is entirely avoided if the geometric description is unaffected by the imaging transformation. Such invariant descriptions can be measured from images without any prior knowledge of the position, orientation and calibration of the camera. These invariant measurements can be used to index a library of object models for recognition and provide a principled basis for the other stages of the recognition process such as feature grouping and hypothesis verification. Object models can be acquired directly from images, allowing efficient construction of model libraries without manual intervention. A significant part of the paper is a summary of recent results on the construction of invariants for 3D objects from a single perspective view. A proposed recognition architecture is described which enables the integration of multiple general object classes and provides a means for enforcing global scene consistency. Various criticisms of the invariant approach are articulated and addressed.