Much research work has recently focused on the problem of representing historical information in XML. This report describes a number of temporal XML data models and provides their comparison according to the following properties: time dimension (valid time, transaction time), support of temporal elements and attributes, querying possibilities, association to XML Schema/DTD, and influence on XML syntax.

Integration has been an acknowledged data processing problem for a long time. However, there is no universal tool for general data integration. Because various data descriptions, data heterogeneity, and machine unreadability, it is not easy way. Improvement in this situation could bring the Semantic Web. Its idea is based on machine understandable web data, which bring us an opportunity of better automated processing. The SemanticWeb is still a future vision, but there are already some features we can use. The paper describes how is integration solved in mediation integration system VirGIS and discusses use of nowadays Semantic Web features to improve it. According to the proposed changes, a new ontology that covers data used in VirGIS is presented.

Abstract Logic is the foundational discipline of many sciences. Part mathematics, part philosophy and part computing science, logic remains a core intellectual study and is increasingly relevant to practical concerns. It spreads into planning, into program synthesis, into circuit design and into discourse analysis. It underpins the entire science of artiŻcial intelligence. In order to increase knowledge from the field of logic, I participated in the Logic Summer School. This report covers some information.

Knowledge representation in geographic information systems (GIS) and associated data processing presents many challenges for researchers. To use ontologies as knowledge representation belongs to the most topical problems to solve. This involves ontology development as well as ontology re-usage. The goal of the research described in this paper is to develop a specific ontology for a given GIS area.

Ontologies play an important role in knowledge representation. Among various fields, where ontologies can be useful, is the GIS data area. We consider data in a specific GIS domain and develop a new ontology. The result is described in this paper.

Information Retrieval (IR) as a process of searching relevant information is a significant discipline of a data processing field. European Summer School in Information Retrieval ESSIR provides students, academic and industrial researchers and developers a grounding in the core objects of IR (models, architectures, algorithms), as well as covering some current topics, e.g. information retrieval from the Web. We have participated its 5th year that was held at Dublin City University in Dublin, Ireland.

As XML has undoubtedly become a standard for data representation, it is inevitable to propose and implement techniques for efficient managing of XML data. A natural alternative is to exploit features and functions of (object-)relational database systems, i.e. to rely on their long theoretical and practical history. The main concern of such techniques is the choice of an appropriate XML-to-relational mapping strategy. In this paper we focus on enhancing of user-driven techniques which leave the mapping decisions in hands of users. We propose an algorithm which exploits the user-given annotations more deeply searching the user-specified "hints" in the rest of the schema and applies an adaptive method on the remaining schema fragments. We describe the proposed algorithm, the similarity measure designed for this purpose, sample implementation of key features of the proposal called UserMap, and results of experimental testing on real XML data.

Recently XML has achieved the leading role among languages for data representation and thus we can witness a massive boom of corresponding techniques for managing XML data. Most of the processing techniques however suffer from various bottlenecks worsening their time and/or space efficiency.We assume that the main reason is they consider XML collections too globally, involving all their possible features, although real data are often much simpler. Even though some techniques do restrict the input data, the restrictions are often unnatural. In this paper we analyze existing XML data, their structure and real complexity in particular.We have gathered more than 20GB of real XML collections and implemented a robust automatic analyzer. The analysis considers existing papers on similar topics, trying to confirm or confute their observations as well as to bring new findings. It focuses on frequent but often ignored XML items (such as mixed content or recursion) and relationship between schemes and their instances.

As the XML has become a standard for data representation, it is inevitable to propose and implement techniques for efficient managing of XML data. A natural alternative is to exploit features of (object-)relational database systems, i.e. to rely on their long theoretical and practical history. The main concern of such techniques is the choice of an appropriate XML-to-relational mapping strategy. In this paper we focus on enhancing of user-driven techniques which leave the mapping decisions in hands of users who specify their requirements using schema annotations.We describe our prototype implementation called UserMap which is able to exploit the annotations more deeply searching the user-specified “hints” in the rest of the schema and applies an adaptive method on the remaining schema fragments. Using a sample set of supported fixed mapping methods we discuss problems related to query evaluation for storage strategies generated by the system, in particular correction of the candidate set of annotations and related query translation. And finally, we describe the architecture of the whole system.

Recently XML is the standard format used for the exchange of data between information systems and is also frequently applied as a logical database model. If we use XML as a logical database model we need a conceptual model for the description of its semantics. However, XML as a logical database model has some special characteristics which makes existing conceptual models as E-R or UML unsuitable. In this paper, the current approaches to the conceptual modeling of XML data are described in an uniform style. A list of requirements for XML conceptual models is presented and described approaches are compared on the base of the requirements.

In this paper we present an architecture for decision making of software agents that allows the agent to behave autonomously. Our target area is computational agents — encapsulating various neural networks, genetic algorithms, and similar methods — that are expected to solve problems of different nature within an environment of a hybrid computational multi-agent system. The architecture is based on the vertically-layered and belief-desire-intention architectures. Several experiments with computational agents were conducted to demonstrate the benefits of the architecture.

We design a formal model of an amorphous computer suitable for theoretical investigation of its computational properties. The model consists of a finite set of nodes created by RAMs with restricted memory, which are dispersed uniformly in a given area. Within a limited radius the nodes can communicate with their neighbors via a single-channel radio. The assumptions on low-level communication abilities are among the weakest possible: the nodes work asynchronously, there is no broadcasting collision detection mechanism and no network addresses. For the underlying network we design a randomized communication protocol and analyze its efficiency. The subsequent experiments and combinatorial analysis of random networks show that the expectations under which our protocol was designed are met by the vast majority of the instances of our amorphous computer model.

Exploiting the concepts of social networking represents a novel approach to the approximate similarity query processing. We present an unstructured and dynamic P2P environment in which a metric social network is built. Social communities of peers giving similar results to specific queries are established and such ties are exploited for answering future queries. Based on the universal law of generalization, a new query forwarding algorithmis introduced and evaluated. The same principle is used to manage query histories of individual peers with the possibility to tune the tradeoff between the extent of the history and the level of the queryanswer approximation. All proposed algorithms are tested on real data and medium-sized P2P networks consisting of tens of computers.

The technical report presents a brief overview on web search engines with deeper insight into their linear algebra background. The linear algebra plays very important role in modern web search algorithms (e.g. Google). The report presents two algorithms, particularly HITS and PageRank. The algorithms are discussed on their convergence problems and also some improvements to their personalization abilities. The computation complexity is also mentioned and briefly sketched.

In MANETs and similar link-free networks of communicating objects there is no central authority for naming and connection management. Autoconfiguration of network nodes is therefore desirable and, building on approaches in IPv6, a number of ‘zero configuration’ networking protocols have been proposed for this case. Typically these protocols do not easily scale and have difficulty with network partitioning and merging. In this paper we propose a number of novel, decentralized techniques for name resolution in zero configuration protocols that are more flexible and yet lead to name extensions of smallest possible length, assuming that objects sufficiently mix within their ranges. Finally, the techniques are converted into a fully decentralized, scalable autoconfiguration protocol for use in ad hoc networks with directional antennas. The protocol is ‘lazy’ in the sense that name resolution is postponed until the moment that conflicts prevent the correct functioning of the communication structure.

We present a design of cognitive system architecture with an internal world model. The internal world model is realized with the help of artificial mirror neurons. We consider generalized artificial mirror neurons acting both as a mechanism for assembling and learning multimodal sensorimotor information and as associative memory for invoking multimodal information given only some of its components. We show that within an artificial cognitive system a network of generalized mirror neurons can simultaneously serve as an internal world model recognized by the agent and as that of the agent`s position within this world. We also specify a self-organizing control mechanism, which is based on the basic operations over concepts that were essentially identified by the British 18th century philosopher David Hume. This control mechanism makes use of the internal world model constructed in agent`s interaction with real world and straightforwardly supports imitation learning. Building heavily on the properties of the generalized mirror net and on automatic abstract concept creation, we offer an algorithmic explanation of computational language acquisition, thinking and consciousness in our model. Rather than describing an implementation of the respective mechanisms, the aim of the paper is to establish a proof of the principle of algorithmic nature of higher cognitive functions.

Moderní teorie kognitivních systémů pohlíží na tyto systémy jako na autonomní vtělené výpočetní systémy, které se situují v okolí prostřednictvím svých senzomotorických jednotek. Přesto zejména v kruzích počítačových teoretikù je opakovaně slyšet názory, že na kognici lze pořád možné pohlížet i "klasicky", jako na problém specifického zpracování dat a že tudíž vtělení není nezbytné pro zachycení podstaty kognice. Ukážeme, že takto zjednodušený pohled opomíjí podstatnou vlastnost kognitivních systémů - a sice jejich aktivní vliv na výběr či dokonce vznik vstupních dat. Bez této zpětné vazby si systém nemůže vytvořit svůj vnitřní model světa poznaný prostřednictvím svých akcí. Pro vysvětlení povahy zmíněného problému použijeme výpočetní model kognitivních systémů zavedený autorem v předchozích pracích. Tento model umožní na principielní úrovni přemýšlet o fungování algoritmických mechanizmů imitace, komunikace, vzniku řeči, myšlení a vědomí a tím přispět i k jejich pochopení v živých systémech.

Amorphous computing differs from the classical ideas about computations almost in every aspect. The architecture of amorphous computers is random, since they consist of a plethora of identical computational units spread randomly over a given area. Within a limited radius the units can communicate wirelessly with their neighbors via a single-channel radio. We consider a model whose assumptions on the underlying computing and communication abilities are among the weakest possible: all computational units are finite state probabilistic automata working asynchronously, there is no broadcasting collision detection mechanism and no network addresses. We show that under reasonable probabilistic assumptions such amorphous computing systems can possess universal computing power with a high probability. The underlying theory makes use of properties of random graphs and that of probabilistic analysis of algorithms. To the best of our knowledge this is the first result showing the universality of such computing systems.

A computational model of molecularly communicating mobile nanomachines is de¯ned. Nanomachines are modelled by timed probabilistic automata augmented by a severely restricted communication mechanism. We show that for molecular communication among such machines an asynchronous stochastic protocol originally designed for wireless communication in so-called amorphous computers with static computational units can also be used. We design an algorithm that using randomness and timing delays selects with a high probability a leader from among sets of anonymous candidates. This enables a simulation of counter automata proving that networks of mobile nanomachines possess universal computing power.