Literatura académica sobre el tema "Description logics with spatial operators"

AbstractA crucial component of a medical concept representation system is the classifier. It requires features that are not sufficiently supported by current logic based formalisms like description logics and conceptual graphs. Those features are, for instance, the representation of partitive and spatial relations and their impact on sUbsumption. This paper introduces graph oriented classification operators for a concept representation language with normal forms. Emphasis is on the separation of generic and partitive relations and on the mutual interdependence of sUbsumption and part-whole. For that purpose operators are given for formal subsumption, formal part-whole, subsumptive part-whole and part-sensitive subsumption. These operators are based on the formal structure of concept descriptions and on explicitly introduced generic and partitive relationships between their constituents.

Abstract Tone mapping is extensively researched to address the issue of displaying high dynamic range (DR) scenes on low DR displays. Even though several tone-mapping operators (TMOs) exist, not all are designed for hard real time. The operator has to be capable of scaling up the spatial resolution without compromising the frame rate. The implementation of a TMO should also be simple enough to embed in low-cost platforms for imaging systems. A computationally efficient, and well accepted, class of TMOs are global ones based on histograms. This work presents a method to implement TMOs that use histograms. This method is suitable for low-cost field-programmable gate arrays (FPGAs), using simple components such as adders, multipliers, and random access memories, and is particularly suited for a nonlinear CMOS image sensor (CIS) operating continuously in hard real time. The authors develop a fixed-point design, validated in bit-true fashion using Xilinx and Altera tools, from a background algorithm implemented using Matlab. Our generic design uses pipelined circuits and operates with low latency. The use of a hardware description language to model our circuits guarantees portability and modularity. Moreover, the complete TMO is generated from design parameters and a design template. The architecture is robust and scales well from kilopixel to megapixel formats. The circuits achieve 30 frames per second, at high definition resolutions, while occupying only a small fraction of the available logic elements in a low-cost FPGA device.

This paper presents an approach to ontology construction pursued through the induction of concept descriptions expressed in Description Logics. The author surveys the theoretical foundations of the standard representations for formal ontologies in the Semantic Web. After stating the learning problem in this peculiar context, a FOIL-like algorithm is presented that can be applied to learn DL concept descriptions. The algorithm performs a search through a space of candidate concept definitions by means of refinement operators. This process is guided by heuristics that are based on the available examples. The author discusses related theoretical aspects of learning with the inherent incompleteness underlying the semantics of this representation. The experimental evaluation of the system DL-Foil, which implements the learning algorithm, was carried out in two series of sessions on real ontologies from standard repositories for different domains expressed in diverse description logics.

Description Logics (DLs) provide a clear and broadly accepted paradigm for modeling and reasoning about terminological knowledge. However, it has been often noted, that although DLs are well-suited for representing a single, global viewpoint on an application domain, they offer no formal grounding for dealing with knowledge pertaining to multiple heterogeneous viewpoints — a scenario ever more often approached in practical applications, e.g. concerned with reasoning over distributed knowledge sources on the Semantic Web. In this paper, we study a natural extension of DLs, in the style of two-dimensional modal logics, which supports declarative modeling of viewpoints as contexts, in the sense of McCarthy, and their semantic interoperability. The formalism is based on two-dimensional semantics, where one dimension represents a usual object domain and the other a (possibly infinite) domain of viewpoints, addressed by additional modal operators and a metalanguage, on the syntactic level. We systematically introduce a number of expressive fragments of the proposed logic, study their computational complexity and connections to related formalisms.

This paper proposes an operational approach to (1) formalize, in Description Logics (DL), the topological relations between simple regions and (2) automatically check whether a set of relations is consistent. The solution allows for the use of traditional DL reasoners (Pellet, Fact++, etc.) to check the consistency of relations and detect the sources of error. The solution does not require any specific extension of the DL or reasoner. The authors demonstrate how to apply this approach with Protégé and Fact++. Different spatial relations in agricultural and environmental applications are also provided to illustrate the possible uses of our method.

Revising knowledge bases (KBs) in description logics (DLs) in a syntax-independent manner is an important, nontrivial problem for the ontology management and DL communities. Several attempts have been made to adapt classical model-based belief revision and update techniques to DLs, but they are restricted in several ways. In particular, they do not provide operators or algorithms for general DL KB revision. The key difficulty is that, unlike propositional logic, a DL KB may have infinitely many models with complex (and possibly infinite) structures, making it difficult to define and compute revisions in terms of models. In this paper, we study general KBs in a specific DL in the DL-Lite family. We introduce the concept of features for such KBs, develop an alternative semantic characterization of KBs using features (instead of models), define two specific revision operators for KBs, and present the first algorithm for computing best approximations for syntax-independent revisions of KBs.

Sequential reactive systems are computer programs or hardware devices which process the flows of input data or control signals and output the streams of instructions or responses. When designing such systems one needs formal specification languages capable of expressing the relationships between the input and output flows. Previously, we introduced a family of such specification languages based on temporal logics $LTL$, $CTL$ and $CTL^*$ combined with regular languages. A characteristic feature of these new extensions of conventional temporal logics is that temporal operators and basic predicates are parameterized by regular languages. In our early papers, we estimated the expressive power of the new temporal logic $Reg$-$LTL$ and introduced a model checking algorithm for $Reg$-$LTL$, $Reg$-$CTL$, and $Reg$-$CTL^*$. The main issue which still remains unclear is the complexity of decision problems for these logics. In the paper, we give a complete solution to satisfiability checking and model checking problems for $Reg$-$LTL$ and prove that both problems are Pspace-complete. The computational hardness of the problems under consideration is easily proved by reducing to them the intersection emptyness problem for the families of regular languages. The main result of the paper is an algorithm for reducing the satisfiability of checking $Reg$-$LTL$ formulas to the emptiness problem for Buchi automata of relatively small size and a description of a technique that allows one to check the emptiness of the obtained automata within space polynomial of the size of input formulas.

In automotive manufacturing, quality inspection of spot welding demands excessive manual operations. Operators refer to a printed drawing of the testing body, with the inspection points marked on this drawing. Operators have to locate the matching spot on the drawing and the body manually to perform the inspection. Further more, different subsets of spots are inspected on different car bodies with a pre-determined sequence. This paper describes a system that projects visual data onto arbitrary surfaces for providing just-in-time information to a user in-situ within a physical work-cell. This system aims to reduce the inefficiencies and potential mistakes in manual inspection process. This paper discusses how spatial augmented reality and head-mount displays may be combined to display global information visible by all operators as well as personalized information to individuals. Further investigations on applying spatial augmented reality for spot welding inspections are explored, including four types of digital information projected onto the surfaces of car body parts under structured work environments: 1) Location of spot welds; 2) Inspection methods; 3) Operation Description Sheet (ODS) information; 4) Visualization of weld locating methods. Three visualization methods are used to attract operators' attention to locate the position of spot welds efficiently. This paper also proposes a method to project augmentations on objects moving along an assembly line. The proposed system allows operators becoming more effective and efficient in performing proper inspections, by providing them the required information at the required time without the need to refer to paper-based manuals or computer terminals.

Le Logiche Descrittive sono una famiglia di formalismi molto espressivi per la rappresentazione della conoscenza. Questi formalismi sono stati investigati a fondo dalla comunità scientifica, ma, nonostante questo grosso interesse, sono state definite poche Description Logics con operatori spaziali e tutte centrate sul Region Connection Calculus. Nella mia tesi considero tutti i più importanti formalismi di Qualitative Spatial Reasoning per mereologie, mereo-topologie e informazioni sulla direzione e studio alcune tecniche generali di ibridazione. Nella tesi presento un’introduzione ai principali formalismi di Qualitative Spatial Reasoning e le principali famiglie di Description Logics. Nel mio lavoro, introduco anche le tecniche di ibridazione per estendere le Description Logics al ragionamento su conoscenza spaziale e presento il potere espressivo dei linguaggi ibridi ottenuti. Vengono presentati infine un risultato generale di para-decidibilità per logiche descrittive estese da composition-based role axioms e l’analisi del tradeoff tra espressività e proprietà computazionali delle logiche descrittive spaziali.
Description Logics are a family of expressive Knowledge-Representation formalisms that have been deeply investigated. Nevertheless the few examples of DLs with spatial operators in the current literature are defined to include only the spatial reasoning capabilities corresponding to the Region Connection Calculus. In my thesis I consider all the most important Qualitative Spatial Reasoning formalisms for mereological, mereo-topological and directional information and investigate some general hybridization techniques. I will present a short overview of the main formalisms of Qualitative Spatial Reasoning and the principal families of DLs. I introduce the hybridization techniques to extend DLs to QSR and present the expressiveness of the resulting hybrid languages. I also present a general paradecidability result for undecidable languages equipped with composition-based role axioms and the tradeoff analysis of expressiveness and computational properties for the spatial DLs.

With the advent of the Semantic Web and Semantic Technologies, ontologies have become one of the most prominent paradigms for knowledge representation and reasoning. The popular ontology language OWL, based on description logics, became a W3C recommendation in 2004 and a standard for modelling ontologies on the Web. In the meantime, many studies and applications using OWL have been reported in research and industrial environments, many of which go beyond Internet usage and employ the power of ontological modelling in other fields such as biology, medicine, software engineering, knowledge management, and cognitive systems. However, recent progress in the field faces a lack of well-structured ontologies with large amounts of instance data due to the fact that engineering such ontologies requires a considerable investment of resources. Nowadays, knowledge bases often provide large volumes of data without sophisticated schemata. Hence, methods for automated schema acquisition and maintenance are sought. Schema acquisition is closely related to solving typical classification problems in machine learning, e.g. the detection of chemical compounds causing cancer. In this work, we investigate both, the underlying machine learning techniques and their application to knowledge acquisition in the Semantic Web. In order to leverage machine-learning approaches for solving these tasks, it is required to develop methods and tools for learning concepts in description logics or, equivalently, class expressions in OWL. In this thesis, it is shown that methods from Inductive Logic Programming (ILP) are applicable to learning in description logic knowledge bases. The results provide foundations for the semi-automatic creation and maintenance of OWL ontologies, in particular in cases when extensional information (i.e. facts, instance data) is abundantly available, while corresponding intensional information (schema) is missing or not expressive enough to allow powerful reasoning over the ontology in a useful way. Such situations often occur when extracting knowledge from different sources, e.g. databases, or in collaborative knowledge engineering scenarios, e.g. using semantic wikis. It can be argued that being able to learn OWL class expressions is a step towards enriching OWL knowledge bases in order to enable powerful reasoning, consistency checking, and improved querying possibilities. In particular, plugins for OWL ontology editors based on learning methods are developed and evaluated in this work. The developed algorithms are not restricted to ontology engineering and can handle other learning problems. Indeed, they lend themselves to generic use in machine learning in the same way as ILP systems do. The main difference, however, is the employed knowledge representation paradigm: ILP traditionally uses logic programs for knowledge representation, whereas this work rests on description logics and OWL. This difference is crucial when considering Semantic Web applications as target use cases, as such applications hinge centrally on the chosen knowledge representation format for knowledge interchange and integration. The work in this thesis can be understood as a broadening of the scope of research and applications of ILP methods. This goal is particularly important since the number of OWL-based systems is already increasing rapidly and can be expected to grow further in the future. The thesis starts by establishing the necessary theoretical basis and continues with the specification of algorithms. It also contains their evaluation and, finally, presents a number of application scenarios. The research contributions of this work are threefold: The first contribution is a complete analysis of desirable properties of refinement operators in description logics. Refinement operators are used to traverse the target search space and are, therefore, a crucial element in many learning algorithms. Their properties (completeness, weak completeness, properness, redundancy, infinity, minimality) indicate whether a refinement operator is suitable for being employed in a learning algorithm. The key research question is which of those properties can be combined. It is shown that there is no ideal, i.e. complete, proper, and finite, refinement operator for expressive description logics, which indicates that learning in description logics is a challenging machine learning task. A number of other new results for different property combinations are also proven. The need for these investigations has already been expressed in several articles prior to this PhD work. The theoretical limitations, which were shown as a result of these investigations, provide clear criteria for the design of refinement operators. In the analysis, as few assumptions as possible were made regarding the used description language. The second contribution is the development of two refinement operators. The first operator supports a wide range of concept constructors and it is shown that it is complete and can be extended to a proper operator. It is the most expressive operator designed for a description language so far. The second operator uses the light-weight language EL and is weakly complete, proper, and finite. It is straightforward to extend it to an ideal operator, if required. It is the first published ideal refinement operator in description logics. While the two operators differ a lot in their technical details, they both use background knowledge efficiently. The third contribution is the actual learning algorithms using the introduced operators. New redundancy elimination and infinity-handling techniques are introduced in these algorithms. According to the evaluation, the algorithms produce very readable solutions, while their accuracy is competitive with the state-of-the-art in machine learning. Several optimisations for achieving scalability of the introduced algorithms are described, including a knowledge base fragment selection approach, a dedicated reasoning procedure, and a stochastic coverage computation approach. The research contributions are evaluated on benchmark problems and in use cases. Standard statistical measurements such as cross validation and significance tests show that the approaches are very competitive. Furthermore, the ontology engineering case study provides evidence that the described algorithms can solve the target problems in practice. A major outcome of the doctoral work is the DL-Learner framework. It provides the source code for all algorithms and examples as open-source and has been incorporated in other projects.

The paper considers the standard concept description language ALC augmented with various kinds of modal operators which can be applied to concepts and axioms. The main aim is to develop methods of proving decidability of the satisfiability problem for this language and apply them to description logics with most important temporal and epistemic operators, thereby obtaining satisfiability checking algorithms for these logics. We deal with the possible world semantics under the constant domain assumption and show that the expanding and varying domain assumptions are reducible to it. Models with both finite and arbitrary constant domains are investigated. We begin by considering description logics with only one modal operator and then prove a general transfer theorem which makes it possible to lift the obtained results to many systems of polymodal description logic.

This paper presents an approach to ontology construction pursued through the induction of concept descriptions expressed in Description Logics. The author surveys the theoretical foundations of the standard representations for formal ontologies in the Semantic Web. After stating the learning problem in this peculiar context, a FOIL-like algorithm is presented that can be applied to learn DL concept descriptions. The algorithm performs a search through a space of candidate concept definitions by means of refinement operators. This process is guided by heuristics that are based on the available examples. The author discusses related theoretical aspects of learning with the inherent incompleteness underlying the semantics of this representation. The experimental evaluation of the system DL-Foil, which implements the learning algorithm, was carried out in two series of sessions on real ontologies from standard repositories for different domains expressed in diverse description logics.

This chapter lays the conceptual groundwork that is necessary by way of prelude to the technical work that is to be undertaken in Chapter 22, where logically precise axioms are framed governing the orderings of points on directed lines. Here it is explained how reference (and commitment) to reals arises from the re-carving of contents of statements of dimensional measurement in terms of a unit, and a notion of congruence (or equality-of- magnitude). Thus one speaks of a dimension D (e.g., length; duration), unit-of-D (e.g., meter; second), D* (e.g., long), #D (e.g., the length of; the duration of), and ≅D (e.g., exactly as long as; equal in duration to). There follows a survey of the different locutions we employ that appear to embed reference to reals, and a tabulation of the systematic similarities across various measurable dimensions (such as length, time, weight, etc.). The outcome of this study of systematic variations in expression of some same state of affairs (i.e., the outcome of measurement) is the formulation of Schema R for the reals. It is compared and contrasted with Schema N for the naturals and with Schema Q for the rationals. Schema R turns out to admit of proof (more precisely: proofs of all its instances) courtesy of introduction and elimination rules involving canonical statements of measurement and identity statements involving the real-number abstraction operator #D on one side, and a de-dimensionalized numerical term on the other side. The crux of this treatment by appeal to one’s geometric intuition of the continuity of a (directed) line will be its painstaking description of how, in principle, to determine the aforementioned de-dimensionalized numerical representation. The considered choice here will be a (potentially infinite) bicimal expansion. The constructive character of such an expansion turns on the determinacy of the trichotomy of ordering of points on a directed line. The chapter argues, as Russell did, for the primacy of spatial measurement (that is, lengths of line segments). Measurement of lengths serves as the paradigm case of measurement in any dimension, for reasons that are expounded upon.

This chapter proposes a multi-agent based framework that allows multiple data sources and models to be semantically integrated for spatial modeling in business processing. The authros introduce a multiagent system (OSIRIS – Ontology-based Spatial Information and Resource Integration Services) to semantically interoperate complex spatial services and integrate them in a meaningful composition. The advantage of using multi-agent collaboration in OSIRIS is that it obviates the need for end-user analysts to be able to decompose a problem domain to subproblems or to map different models according to what they actually mean. The authors also illustrate a multi-agent interaction scenario for collaborative modeling of spatial applications using the proposed custom feature of OSIRIS using Description Logics. The system illustrates an application of domain ontology of urban environmental hydrology and evaluation of decision maker’s consequences of land use changes. In e-government context, the proposed OSIRIS framework works as semantic layer for one stop geospatial portal.

Intuitive means of human-machine interaction are needed in order to facilitate seamless human-robot cooperation. Knowledge about human posture, whereabouts, and performed actions allows interpretation of the situation. Thus, expectations towards system behavior can be inferred. This work demonstrates a system in an industrial setting that combines all this information in order to achieve situation awareness. The continuous human action recognition is based on hierarchical Hidden Markov Models. For identifying and predicting human location, an approach based on potential functions is presented. The recognition results and spatial information are used in combination with a Description Logics-based reasoning system for modeling semantic interrelations, dependencies, and situations.

We present a method based on clustering techniques to detect possible/probable novel concepts or concept drift in a Description Logics knowledge base. The method exploits a semi-distance measure defined for individuals, that is based on a finite number of dimensions corresponding to a committee of discriminating features (concept descriptions). A maximally discriminating group of features is obtained with a randomized optimization method. In the algorithm, the possible clusterings are represented as medoids (w.r.t. the given metric) of variable length. The number of clusters is not required as a parameter, the method is able to find an optimal choice by means of evolutionary operators and a proper fitness function. An experimentation proves the feasibility of our method and its effectiveness in terms of clustering validity indices. With a supervised learning phase, each cluster can be assigned with a refined or newly constructed intensional definition expressed in the adopted language.

During the last decades, the interest displayed in neurocognitive and brain science research is relatively high. In this chapter, the cognitive neuroscience field approach focuses in the aspect of the way that cognitive functions are produced by neural circuits in the brain. Within this frame, the effects of impairment to the brain and subsequent changes in the thought processes due to changes in neural circuitry resulting from the ensued damage are analyzed and evaluated. All cognitive functions result from the integration of many simple processing mechanisms, distributed throughout the brain. Brain cortex structures, linked with cognitive disorders, are located in several parts like the frontal, the parietal, the temporal, the occipital lobe and more are analyzed and specified. A critical topic of this chapter in the evaluation of brain operations is mapping regions that control cognitive and mathematical concepts functions. Dyscalculia, in this chapter, is described as a specific disorder of managing and conceiving mathematical concepts. Dyscalculia could be identified by difficulties in visual perception, in spatial number organization, in basic mathematical operations and in mathematical induction logic. Moreover, people who deal with dyscalculia present problems, in Euclidean and Non-Euclidean Geometry concepts perception, in Calculus aspects as well as in solving algorithmic problems where the design, the description and the application of algorithmic steps are required. In order to enhance cognitive brain functions perception, the use of EEG brain imaging is proposed measuring cerebral activity and event-related potentials. The procedure described in this chapter is about the comparison and contrasts EEG brain imaging patterns of healthy volunteers to EEG samples taken of adults considered being at risk of mathematics learning disabilities such as Dyscalculia and algorithmic thinking difficulties. EEG interpretation analysis is to follow where the deviation of a normal and an abnormal range of wave's frequency are defined. Several visualized EEG patterns in relevance with specific abnormalities are presented while several neurocognitive generated disorders could be identified with the use of EEG Brain-imaging technique. The electroencephalogram EEG brain imaging procedure, in order to evaluate problems associated with brain function, is to be further analyzed in this chapter as well. The EEG is the depiction of the electrical activity occurring at the surface of the brain. The recorded waveforms reflect the cortical electrical activity and they are generally classified according to their frequency (Delta, Theta, Beta, Alpha, Beta, and Gamma) amplitude, and shape. EEG Implementation with the use of 10/20 system of the standardized position of scalp electrodes placement for a classical EEG recording is described as well. The EEG implementation objective is to identify, classify and evaluate those frequencies and regions in the brain that best characterize brain activity associated with mathematical learning disabilities. Mapping the brain with non-invasive techniques based on trigger and sensing/evaluation experimental multimedia methods similar to those used in computer games and applications are expected to provide relevant results in order to enhance and confirm theoretical cognitive aspects. At that point, a cognitive and mathematical perception evaluation is to follow and specifically the assessment of the relation of difficulties in mathematics with particular parts of the human brain. EEG wave data visualization is contacted with the use of Acknowledge an interactive, intuitive program which provides data analysis instantly. At the end of this chapter EEG computational evaluation with the use of pattern recognition methods as well as the intuition of author's future work in relevance with the use of experimental multimedia technologies to enhance the dynamic recognition and evaluation of user cognitive responses during EEG implementation are noted.

We study combinations of the description logic DL-Lite_{bool}^N with the branching temporal logics CTL* and CTL. We analyse two types of combinations, both with rigid roles: (i) temporal operators are applied to concepts and to ABox assertions, and (ii) temporal operators are applied to concepts and Boolean combinations of concept inclusions and ABox assertions. For the resulting logics, we present algorithms for the satisfiability problem and (mostly tight) complexity bounds ranging from ExpTime to 3ExpTime.

We aim to determine which temporal instance queries can be uniquely characterised by a (polynomial-size) set of positive and negative temporal data examples. We start by considering queries formulated in fragments of propositional linear temporal logic LTL that correspond to conjunctive queries (CQs) or extensions thereof induced by the until operator. Not all of these queries admit polynomial characterisations, but by imposing a further restriction to path-shaped queries we identify natural classes that do. We then investigate how far the obtained characterisations can be lifted to temporal knowledge graphs queried by 2D languages combining LTL with concepts in description logics EL or ELI (i.e., tree-shaped CQs). While temporal operators in the scope of description logic constructors can destroy polynomial characterisability, we obtain general transfer results for the case when description logic constructors are within the scope of temporal operators. Finally, we apply our characterisations to establish (polynomial) learnability of temporal instance queries using membership queries in the active learning framework.

The described design methodology combines parametric design, data analysis, algorithmic design and semiotics theory to systematically analyze urban reality. The analysis leads to a creation of a nebula of data which corresponds to the place of interest. The nebula of data consists of networks of semiotics spatially defined. Through the proposed methodology, semiotics are used to enhance the perception that we have for a place and create a strategy for its' branding. Space is not approached as an empty container but as a complex system that consists of material and immaterial elements. The characteristics of these elements are quantified by their context and the logics of description to which they correspond. Logics of description are constantly changing following the multiplicity and the expansion of concepts. Therefore, space is constantly redefined following the transformation of the corresponding virtual data. Considering that each framework draws up an ideology following the change of context and the logics of description, a tool (machine) for analyzing written speech is developed, combining data visualization techniques, linguistics and design methodologies to configure logics of description. Written speech is transformed into a series of networks, visualizing their ontological relationships and disregarding the factor of time. A nebula of data corresponding to the mental reality of space is formed. Following a methodological procedure, the nebula of space is transformed to a nebula of place. The nebula of place contains its' key characteristics parametrized. A selection of these characteristics is combined to create the brand of the place concerning its' context and logics of description. The before mentioned methodological tool connects people, spaces, and machines enabling the connection of spatial data to create the impression (brand) of a place.

Optical symbolic processing applications in pattern recognition rather than logic operations [1,2] are considered in this paper. The database we employ is summarized in Section 2. Optical correlators represent one of the most powerful functions possible and preferable for realization on optical systems. We thus retain this architecture as the fundamental level-one symbolic processor to be used [2,3]. We utilize the attractive aspects of distortion-invariant iconic optical matched spatial filter (MSF) filters [4] in this work. We increase the flexibility, capacity and performance of such filters by using segments of the input object as separate filters (Section 3). The correlation outputs for these object sections represent the symbolic description of the input to be processed. A hierarchical set of rules for symbolic output processing and substitution is then employed (Section 4). The symbolic substitution used, the interactive expert system nature of the rule design, and the confidence of each rule are then detailed (Section 4). Tests of the system are then presented (Section 5).

Research on the visual computation has received a great deal of attention The demands on human-based cognitive computing are very high. for example, the implementation of autonomous driving functions depends on the effective cooperation of three components: perception, decision making and execution. The perception layer identifies people, objects, and signs on the road by simulating the human eye through multi-dimensional sensors; the decision layer evaluates and makes decisions through pre-processing such as algorithm fusion and feature extraction; the data is fused and output to each control unit in the execution layer; and finally, the hardware mechanism in the execution layer makes feedback actions to realize the full set of autonomous driving operations. In this work, we try to show that this kind of symbolism framework will encounter the so-called “the framing problem” as earlier attempts to formalize the changes of knowledge in event flows. The framing problem is the problem of finding a sufficient set of axioms for a feasible description for environments of the robot or automatic driving. Even the visual-spatial hybrid computation with additional default inference has shown its potentiality in the automation, there still be the frame problem. This means that the symbolic methodology has its own logical flaw.

Recent advances in the use of fast Fourier transform (FFT) techniques for the solution of the explicitly time-dependent nonrelativistic Schrodinger equation have made calculations of electron motion in a strong (nonperturbative) laser field possible. Evaluation of the spatial differential operators is provided on a grid by a Fourier transform and synthesis. These techniques are physically and numerically attractive because of the natural description of periodic wavepacket phenomena and the intrinsic computational efficiency arising from the use of the FFT algorithm. Explicitly time-dependent treatments have the advantage of treating the continuum directly; a corresponding disadvantage arises in the difficulty of asymptotic analysis of the evolved wavefunction, for example, in the simulation of a photoelectron spectrum. Several different time propagation schemes can be used with the FFT spatial evaluations; results for some of these schemes are presented for model 1-D potentials.

Introducción: La consolidación del desarrollo urbano es asociada a la movilidad, en mayor medida si se trata de AUTOPISTAS. Involucrando lógicas propias y autónomas, resultan funcionales exclusivamente a sus fines: contener y conducir de modo eficiente el flujo vehicular, partiendo de imponer sus también propios condicionamientos espaciales -estructuras de soporte, intercambiadores, organizadores bajo, sobre y a nivel, puentes, túneles, pantallas visuales, entre otros-. Queda afectado entonces el sector del territorio sobre el que descienden, por una secuencia dominantemente lineal de distintas categorías de impactos, vinculados además al nivel de consolidación urbana. Como producto de la interacción entre Fijos y Flujos -TERRITORIO/ AUTOPISTAS-, es que surgen las Situaciones Intersticiales urbanas, encaradas aquí desde un origen investigativo en donde el Intersticio fue entendido como diferencia entre entidades territoriales anteriores y nuevas superpuestas, redundante en hibridación material o funcional de respectivas condiciones originales, y abordado como producto de acciones y relaciones sociales, temporales y espaciales. Este espacio intersticial, fue considerado entonces información ineludible al abordar operaciones sobre áreas urbanas en correlato con flujos de movilidad autopistas. Objetivos: Se pretende generar un corpus de inferencias conducente a la elaboración de futuros diagnósticos, pautas y estrategias, a fin de “mitigar” los impactos afectantes e irresueltos que producen la sumatoria de situaciones intersticiales y remanentes espaciales, para ser eficientemente incorporados como variables a tomar en cuenta en los estudios del territorio en tanto urbano. Metodología: Los datos emergen de la aplicación de un instrumento de lectura e interpretación sistémica que atiende a la complejidad del tejido urbano y la superposición de estratos físicos y fenomenológicos: Herramienta Intersticio, en situaciones intersticiales “bajo autopista” en un recorte de Región Metropolitana de Buenos Aires/ RMBA – Argentina. Conclusiones: Conclusiones genéricas producto del análisis, evidencian que el Flujo Autopista-AU corta/secciona a la CIUDAD, aceptado como hecho consumado su implantación y descenso en aras de la conectividad del territorio. Los DETERMINANTES ESPACIALES (modulación, soporte, senda-techo entre otros) condicionan las apropiaciones de manera tal que sea cual fuere el carácter del ámbito de inserción, contexto y autopista establecen un vínculo que–rozando en algunos casos la indiferencia-, no incita a contexto y autopista establecen un vínculo que–rozando en algunos casos la indiferencia-, no incita a “pleitos” urbanos verificables… Una adecuación (voluntaria?) que no evita que programa y usos predominantes, incidan desde este status quo en la dinámica del sitio… Aunque en muchos casos no difieran de los propios del sector de pertenencia, domina el conflicto en el escenario y su función de uso, situación que no ocurre cuando el mismo uso tiene una pertenencia al tejido urbano de la ciudad: es que la Autopista deja en su abajo, una suerte de confusión entre lo público y lo privado, que sumada a la incidencia de estructura de soporte y plano superior límite, hacen que se produzcan siempre indefiniciones y/o conflictos -problemas propios de las infraestructuras en el territorio cuando no poseen diagnósticos desde la gestión de pertenencia-. Afrontar específicamente la evaluación de las condiciones de habitabilidad de las situaciones intersticiales estudiadas y/o la determinación de casos pasibles de una optimización -reconfiguración de la situación presente-, conducen a reconocer la necesidad de una proyección del “sobre” y “bajo” autopista de manera conjunta. Sumado a lo anterior, se confirma como necesaria la planificación previa de los intersticios “bajo autopista”, apoyada en el estudio realizado en esta investigación, desde una potencialidad espacial latente y mal aprovechada, así como desde la anarquía evidente que los distintos usos-programas encontrados en esos espacios de muestra, en general con calidad urbana degradada. El ineludible vínculo entre el desarrollo urbano y la movilidad, deberá contar con instrumentos propios que contemplen estos espacios, no como remanente de una intervención, sino de manera sostenible, compatible con la preservación y mejora del medioambiente natural y urbano, contribuyendo por las actividades que induce, directa e indirectamente en la formación de capital social. Introduction: Urban consolidation development is associated to motility, in great part if is referred to HIGHWAYS. Involving own and autonomy logics, they results functionality exclusively to its purpose: to content and conduce in an efficient way vehicular fluxes, starting from impose its own spatial conditions - support structures, organizing under and upper level of bridges panels, tunnels, visuals screens, and so on-. The territorial sector where it happens this descending is affected because of a domineerig lineal sequence of different categories of impacts entailed besides to urban consolidation level. As a product of interaction between Fix and Fluxes -TERRITORY/ HIHGWAYS-, is that appears urban Interstitials Situations, faced here from an investigative origin where Interstice was understood as the difference between previous territorial entities and new ones superposed, redounding in material or functional hybridization of respective original conditions, and boarded as a product of social, and spatial actions and relations. So, this interstitial space, was considered unavoidable information when boarding operations over urban areas in relation with motility fluxes highways. Objectives: The research, presently in development pretends to fix regulations and strategies appointing to a systematically formulation of typological patterns taking in account interstitially space, unavoidable information to face actions over urban areas in relation with motility high-way fluxes and appropriation in the under high-way. Methodologies: Is based in data emerging from the application of a reading and systemic interpretation instrument appointing to the complexity of urban tissue and the superposition of physics and phenomenological layers, -Interstitial Tool-, in interstitials situations “under highway” in a fragment of the Buenos Aires Metropolitan Region / RMBA – Argentina. By other way, digital descriptions are used as the best choice for representing all this process –still unfinished-, by the application of digital methods to board the understanding of the mentioned urban problematic. Conclusions: Generic conclusions as result of the analysis, put in evidence that the motility high-way fluxes cuts/sections the CITY, accepted its implantation and descent as a consummated fact in account of territorial connectivity. SPATIAL DETERMINING (modulation, support, way-cover between others), conditions appropriations in that way, that it doesn’t matter character of the insertion contour; context and highway establishes a nexus; an urban adequation (voluntary or involuntary) that cannot avoid that programs and uses doesn’t fall into a sort of accepted status quo, even if in much cases have no difference from proper uses of the insertion area; conflict takes possession of the scene and its uses, all that because the highway leaves in its “under” a sort of confusion between public and privat activities, adding to this, the incidence of the supporting structure and upper plane that conduces always to not resulted conditions and/or conflicts proper from this kind of infrastructures over territories when there isn’t governmental diagnostics and actions-. The evaluation of specific conditions of habitability of the interstitial situations mentioned, must be boarded to be changed, as well as those cases apt to be optimized, producing a reconfiguration of present situation. There is a responsibility about a simultaneous design of the upper and under highways. The unavoidable bond between urban development and motility must depend on, own instruments that overview those spaces , not as remnants of another intervention but in a sustainability way, compatible with preservation and an natural and urban ambient improvement, contributing to all that makes direct or indirectly to construct the social capital of urban areas.

Description logics are knowledge representation and reasoning formalisms which represent conceptual knowledge on an abstract logical level. Concrete domains are a theoretically well-founded approach to the integration of description logic reasoning with reasoning about concrete objects such as numbers, time intervals or spatial regions. In this paper, the complexity of combined reasoning with description logcis and on concrete domains is investigated. We extend ALC(D), which is the basic description logic for reasoning with concrete domains, by the operators 'feature agreement' and 'feature disagreement'. For the extended logic,called ALCF(D), an algorithm for deciding the ABox consistency problem is devised. The strategy employed by this algorithm is vital for the efficient implementation of reasoners for description logics incorporating concrete domains. Based on the algorithm, it is proved that the standard reasoning problems for both logics ALC(D) and ALCF(D) are PSpace-complete - provided that the satisfiability test of the concrete domain used is in PSpace.

The eight topological RCC8(or Egenhofer-Franzosa)- relations between spatial regions play a fundamental role in spatial reasoning, spatial and constraint databases, and geographical information systems. In analogy with Halpern and Shoham’s modal logic of time intervals based on the Allen relations, we introduce a family of modal logics equipped with eight modal operators that are interpreted by the RCC8-relations. The semantics is based on region spaces induced by standard topological spaces, in particular the real plane. We investigate the expressive power and computational complexity of the logics obtained in this way. It turns our that, similar to Halpern and Shoham’s logic, the expressive power is rather natural, but the computational behavior is problematic: topological modal logics are usually undecidable and often not even recursively enumerable. This even holds if we restrict ourselves to classes of finite region spaces or to substructures of region spaces induced by topological spaces. We also analyze modal logics based on the set of RCC5relations, with similar results.

Most of the research on temporalized Description Logics (DLs) has concentrated on the case where temporal operators can occur within DL concept descriptions. In this setting, reasoning usually becomes quite hard if rigid roles, i.e., roles whose interpretation does not change over time, are available. In this paper, we consider the case where temporal operators are allowed to occur only in front of DL axioms (i.e., ABox assertions and general concept inclusion axioms), but not inside of concepts descriptions. As the temporal component, we use linear temporal logic (LTL) and in the DL component we consider the basic DL ALC. We show that reasoning in the presence of rigid roles becomes considerably simpler in this setting.

Recently, a lot of research has combined description logics (DLs) of the DL-Lite family with temporal formalisms. Such logics are proposed to be used for situation recognition and temporalized ontology-based data access. In this report, we consider DL-Lite-LTL, in which axioms formulated in a member of the DL-Lite family are combined using the operators of propositional linear-time temporal logic (LTL). We consider the satisfiability problem of this logic in the presence of so-called rigid symbols whose interpretation does not change over time. In contrast to more expressive temporalized DLs, the computational complexity of this problem is the same as for LTL, even w.r.t. rigid symbols.

Ontology-based query answering augments classical query answering in databases by adopting the open-world assumption and by including domain knowledge provided by an ontology. We investigate temporal query answering w.r.t. ontologies formulated in DL-Lite, a family of description logics that captures the conceptual features of relational databases and was tailored for efficient query answering. We consider a recently proposed temporal query language that combines conjunctive queries with the operators of propositional linear temporal logic (LTL). In particular, we consider negation in the ontology and query language, and study both data and combined complexity of query entailment.

We consider ontology-based query answering in a setting where some of the data are numerical and of a probabilistic nature, such as data obtained from uncertain sensor readings. The uncertainty for such numerical values can be more precisely represented by continuous probability distributions than by discrete probabilities for numerical facts concerning exact values. For this reason, we extend existing approaches using discrete probability distributions over facts by continuous probability distributions over numerical values. We determine the exact (data and combined) complexity of query answering in extensions of the well-known description logics EL and ALC with numerical comparison operators in this probabilistic setting.

As widely argued [HG97; Sat96], transitive roles play an important role in the adequate representation of aggregated objects: they allow these objects to be described by referring to their parts without specifying a level of decomposition. In [HG97], the Description Logic (DL) ALCHR+ is presented, which extends ALC with transitive roles and a role hierarchy. It is argued in [Sat98] that ALCHR+ is well-suited to the representation of aggregated objects in applications that require various part-whole relations to be distinguished, some of which are transitive. However, ALCHR+ allows neither the description of parts by means of the whole to which they belong, or vice versa. To overcome this limitation, we present the DL SHI which allows the use of, for example, has part as well as is part of. To achieve this, ALCHR+ was extended with inverse roles. It could be argued that, instead of defining yet another DL, one could make use of the results presented in [DL96] and use ALC extended with role expressions which include transitive closure and inverse operators. The reason for not proceeding like this is the fact that transitive roles can be implemented more efficiently than the transitive closure of roles (see [HG97]), although they lead to the same complexity class (ExpTime-hard) when added, together with role hierarchies, to ALC. Furthermore, it is still an open question whether the transitive closure of roles together with inverse roles necessitates the use of the cut rule [DM98], and this rule leads to an algorithm with very bad behaviour. We will present an algorithm for SHI without such a rule. Furthermore, we enrich the language with functional restrictions and, finally, with qualifying number restrictions. We give sound and complete decision proceduresfor the resulting logics that are derived from the initial algorithm for SHI. The structure of this report is as follows: In Section 2, we introduce the DL SI and present a tableaux algorithm for satisfiability (and subsumption) of SI-concepts—in another report [HST98] we prove that this algorithm can be refined to run in polynomial space. In Section 3 we add role hierarchies to SI and show how the algorithm can be modified to handle this extension appropriately. Please note that this logic, namely SHI, allows for the internalisation of general concept inclusion axioms, one of the most general form of terminological axioms. In Section 4 we augment SHI with functional restrictions and, using the so-called pairwise-blocking technique, the algorithm can be adapted to this extension as well. Finally, in Section 5, we show that standard techniques for handling qualifying number restrictions [HB91;BBH96] together with the techniques described in previous sections can be used to decide satisfiability and subsumption for SHIQ, namely ALC extended with transitive and inverse roles, role hierarchies, and qualifying number restrictions. Although Section 5 heavily depends on the previous sections, we have made it self-contained, i.e. it contains all necessary definitions and proofs from scratch, for a better readability. Building on the previous sections, Section 6 presents an algorithm that decides the satisfiability of SHIQ-ABoxes.