A model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets

In many application areas there is a need to represent human-like knowledge related to spatio-temporal relations among multiple moving objects. This type of knowledge is usually imprecise, vague and fuzzy, while the reasoning about spatio-temporal relations is intuitive. In this paper we present a model of fuzzy spatio-temporal knowledge representation and reasoning based on high-level Petri nets. The model should be suitable for the design of a knowledge base for real-time, multi-agent-based intelligent systems that include expert or user human-like knowledge. The central part of the model is the knowledge representation scheme called FuSpaT, which supports the representation and reasoning for domains that include imprecise and fuzzy spatial, temporal and spatio-temporal relationships. The scheme is based on the high-level Petri nets called Petri nets with fuzzy spatio-temporal tokens (PeNeFuST). The FuSpaT scheme integrates the theory of the PeNeFuST and 117 spatio-temporal relations.The reasoning in the proposed model is a spatio-temporal data-driven process based on the dynamical properties of the scheme, i.e., the execution of the Petri nets with fuzzy spatio-temporal tokens. An illustrative example of the spatio-temporal reasoning for two agents in a simplified robot-soccer scene is given.     

TeMAS–a multi-agent system for temporally rich domains

In this paper, we present the model and simulator of a multi-agent system (MAS) for temporally rich domains. The theoretical foundations of the model include a knowledge representation scheme based on an original modification of Petri nets, called Petri nets with time tokens (PNTTs), as well as temporal reasoning based on the extension of Allen's temporal logic. The proposed MAS, called TeMAS, has a hierarchical structure, consisting of different levels, where each level contains clusters of agents. A paradigm of hierarchically organized blackboards is used for the communication among agents, clusters, as well as levels. We describe an object-oriented implementation of a program simulator of TeMAS and give an example of the use of the simulator for interpretation of events in a dynamic scene. Slobodan Ribarić received the B.S. degree in electronics, the M.S. degree in automatics, and the Ph.D. degree in electrical engineering from the Faculty of Electrical Engineering, Ljubljana, Slovenia, in 1974, 1976, and 1982, respectively. He is currently a Full Professor at the Department of Electronics, Microelectronics, Computer and Intelligent Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia. His research interests include pattern recognition, artificial intelligence, biometrics, computer architecture and robot vision. He has published more than 150 papers on these topics and authored four books (Microprocessor Architecture, The Fifth Computer Generation Architecture, Advanced Microprocessor Architectures, CISC and RISC Computer Architecture) and co-authored one book (An Introduction to Pattern Recognition). Dr. Ribarić is a Member of the IEEE, ISAI and IAPR. Tomislav Hrkać received the B.S. degree in computer science from the Faculty of Electrical Engineering and Computing at the University of Zagreb, Croatia, in 1999. Since October 2000, he has been a Researcher with the Department of Electronics, Microelectronics, Computer and Intelligent Systems at the same faculty. He received the M.S. degree in 2004. As a co-author, he published several papers in international conference proceedings and a paper in a reviewed scientific journal. He is a Student Member of IEEE.     

Efficient multiple phase shift patterns for dense 3D acquisition in structured light scanning

Although phase shifts (PS) are frequently used to acquire colored surfaces of static objects, especially when acquisition time is not critical, the periodic nature of relative (wrapped) PS maps makes it necessary to deal with the issue of phase unwrapping. Consequently, multiple phase shifts (MPS) have been widely used as an alternative, but this usually involves a large number of different PS maps to unwrap an absolute (unique) phase. In this paper we propose a new MPS method to unwrap a phase and accurately perform the dense 3D acquisition of neutral and colored objects using only two PS maps. Accuracy is reported including a quantitative and qualitative evaluation of the results.     

TS-based sampled-data model predictive controller for continuous-time nonlinear systems

This paper proposes a new fuzzy model predictive control approach for continuous-time nonlinear systems in terms of linear matrix inequalities (LMIs). The proposed approach is based on the Takagi–Sugeno fuzzy modeling, a quadratic Lyapunov function, and a sampled-data parallel distributed compensation controller with constant sampling time. The goal is designing the sampled-data controller such that at each sampling time, the stability of the closed-loop system is guaranteed and an infinite horizon cost function is minimised. The main advantage of the proposed approach is to eliminate the approximations induced from discretizing the original system and cost function upper bound minimisation. Consequently, a lower bound of the cost function is obtained and the performance of the proposed model predictive controller is improved compared to the recently published papers in the same field of interest. In addition, the Euclidean norm constraint of the control input vector is derived in terms of LMIs. To illustrate the merits of the proposed approach, the proposed technique is applied to a continuous stirred tank reactor system.     

Assessment of MR imaging during one-lung flooding in a large animal model

Magnetic Resonance Materials in Physics, Biology and Medicine - Magnetic resonance imaging (MRI) of the lung remains challenging due to the low tissue density, susceptibility artefacts,...     

Systematic studies of structure and physiological activity of alapyridaine. A novel food-born taste enhancer

By application of taste dilution analysis (+)-(S)-1-(1-carboxyethyl)-5-hydroxy-2-(hydroxymethyl)-pyridinium inner salt was recently successfully identified as a multimodal taste enhancer in beef bouillon. While being taste-less on its own, this so-called alapyridaine was found to intensify the human perception of sweet, salty, and umami taste. To gain information on the molecular requirements of this novel class of taste enhancer, a range of structurally related pyridinium betaines were synthesized, purified, and their physiological activities sensorially evaluated. Removal or modification of the hydroxyl and the hydroxymethyl group, respectively, induced a loss in bioactivity, thus indicating the 2-(hydroxymethyl)-5-hydroxypyridinium moiety as an essential structural element for taste enhancement. Regarding the amino substituent, neither the prolongation or removal of the alkyl chain or the carboxy function in the 1-(1-carboxy-2-ethyl)-moiety, nor the incorporation of an additional carboxy function led to any active derivative, thus demonstrating that also the structure of the nitrogen substituent is rather conserved for taste enhancement. But substitution of the methyl group by a benzyl group yielded a compound showing similar taste enhancing activities as found for alapyridaine. Interestingly, additional insertion of glycine between the 1-(1-carboxy-2-phenylethyl)-moiety and the pyridinium ring resulted in a compound eliciting comparable taste enhancing effects as shown for the compound lacking the glycine spacer. In contrast to these multimodal taste enhancers, substitution of the alanine moiety in alapyridaine by an arginine moiety revealed an one-dimensional taste enhancer exclusively increasing the human sensitivity for salty taste.     

Theory and application of static field inhomogeneity effects in gradient-echo imaging

The influence of local static magnetic field inhomogeneities on gradient-echo imaging is discussed and the underlying theoretical aspects are reviewed. A high-resolution approach is suggested to suppress image distortion and restore signal loss due to spin dephasing. Acquisition of three-dimensional data sets not only overcomes part of the limitations associated with gradient echoes but also makes it possible to extract local information about the strength or direction of background gradients and relative susceptibility changes between different tissues. Applications of the suggested approach in the human brain for anatomical imaging as well as for extraction of physical and physiological parameters are presented and discussed.