Jaroslav Pokorny

Physiologic and Morphologic Characteristics of Granule Cell Circuitry in Human Epileptic Hippocampus

Summary: Morphological and electrophysiological techiques were used to examine granule cells and their mossy fiber axons in nine surgically resected hippocampal specimens from temporal lobe epilepsy (TLE) patients. Timm histochemistry showed mossy fiber sprouting into the inner molecular layer (IML) of the dentate in a subset of tissue samples. In slices from five tissue samples, stimulus‐induced bursting activity could be induced with a low concentration (2.5 μM) of bicuculline; bursts were sensitive to the N‐methyl‐d‐aspartate (NMDA) blocker, APV. There was a general correlation between such sprouting and experimentally induced yperexcit ability. Fourteen granule cells from five tissue samples were intracellularly stained [with lucifer yellow (LY) or neurobiotin]. Axons from a subset of these neurons showed axon collaterals reaching into the IML, but this axon projection pattern for single cells was not directly correlated with degree of mossy fiber sprouting shown grossly by Timm staining. Electron microscopic examination of intracellularly stained elements showed mossy fiber axon terminals making asymmetric synaptic contacts (including autapses on the granule cell dendrite) with dendritic shafts and spines in both apical and basal domains. These data are consistent with the hypothesis that mossy fiber sprouting provides a structural basis for recurrent excitation of granule cells, but does not provide direct support of the hypothesis that mossy fiber sprouting causes hyperexcitability. The data suggest that granule cell bursting activity is at least in part a function of compromised synaptic inhibition, since levels of γ‐aminobutyric acid (GABA) blockade that are generally subthreshold for burst induction were epileptogenic in some tissue samples from human epileptic hippocampus.

NoSQL databases: a step to database scalability in web environment

The paper is focused on so called NoSQL databases. In context of cloud computing, architectures and basic features of these databases are studied, particularly their horizontal scalability and concurrency model, that is mostly weaker than ACID transactions in relational SQL-like database systems. Some characteristics like a data model and querying capabilities are discussed in more detail. The paper also contains an overview of some representatives of NoSQL databases.

Web searching and information retrieval

The first Web information services were based on traditional information retrieval (IR) algorithms and techniques. However, IR algorithms were developed for smaller and more coherent collections than the Web is. Thus Web searching requires new techniques - exploiting linkage among Web pages or extensions of the old ones, for example. This article offers an overview of todays search engine architectures and techniques in the context of IR. The authors introduce three such architectures and describe their basic components. Then they discuss the most important feature of each Web search process: page importance and its use in retrieval. Some issues and challenges in Web search engines are also summarized as well as considerations on the future of Web searching in terms of the so-called semantic Web.

Modelling stars using XML

We suppose collections of XML data described by Document Type Definitions (DTDs). This data has been generated by applications and plays a role of OLTP database(s). A star schema, a well-known technique used in data warehousing, can be applied. Then dimension information is supposed to be contained in XML data. We will use the notions of subDTD and view, and formulate referential integrity constraints in XML environment. We use simple pattern matching capabilities of current XML query languages for XML view specification and tree embedding algorithms for these purposes. A dimension hierarchy is defined as a set of logically connected collections of XML data. Facts may be also conceived as elements of an XML document. Due to the structural complexity of XML data the approach requires subtler formal model than it is done with conventional dimension and fact tables described by classical star schemes. In consequence, our approach captures more from heterogeneity of source databases than it is done in classical relational approaches to data warehousing.

A system recommending top-k objects for multiple users preferences

We discuss models of user preferences in Web environment. We construct a model for user preference querying over a number of data sources and ordering of answers by a combination of particular attribute rankings. We generalize Fagins algorithm in two directions - we develop some new heuristics for top-k search in the model without random access and propose a method of ordering lists of objects by user fuzzy function. To enable different user preferences our system does not require objects to be sorted -instead we use a B+-tree on each of the attribute domains. This leads to a more realistic model of Web services. We implement our methods and heuristics for search of top-k answers into Tokaf middleware framework prototype. We describe experiments with Tokaf and compare different performance measures with some other methods.

XML in the World of (Object-)Relational Database Systems

XML is universally recognized as the standard for interchange and deviceindependent representation of information. On the other hand, XML is recently understood as a new approach to data modelling 3 A well-formed XML document or a set of documents is an XML database and the associated DTD or schema specified in the language XML Schema is its database schema. Implementation of a system enabling us to store and query XML documents efficiently is developed today in different ways. We do not discuss here native storage solution, i.e. a DBMS dedicated to manage XML data collections. A more practical possible solution can be found in storing XML data in (object-)relational DBMS. Moreover, this approach enables to provide XML with missing database mechanisms (e.g. indexes, transactions, multi-user access, etc.). Currently there is a relatively large number of works devoted to storing XML data, including the special architectures like PDOM, CMS, XML Servers, XML Query Engines, etc. We refer reader to Bourret for their comprehensive overview. Our contribution is a summarization of recent XML storage techniques based on today’s (object-)relational database technologies, their comparing and evaluation. We also present own algorithm for mapping XML Schema structures to object-relational (OR) schema. A more comprehensive discussion can be found in Mlynkova and Pokorny. For transferring the data between XML documents and (O)R structures so-called mapping methods are of a great importance. A basic classification of existing mapping methods includes the following three classes:

A mediation layer for heterogeneous XML schemas

This paper introduces an approach to minimize the total designer effort for building XML data integration systems. Since fully automatic schema mapping generation is infeasible, in our view such an approach can be used as a semi‐automatic tool for XML schemas mediation. A method is proposed to query XML documents through a mediation layer. Such a layer is introduced to describe the mappings between global XML schema and local heterogeneous XML schemas. It produces a uniform interface over the local XML data sources, and provides the required functionality to query these sources in a uniform way. It involves two important units: the XML Metadata Document (XMD) and the Query Translator. The XMD is an XML document containing metadata, in which the mappings between global and local schemas are defined. The XML Query Translator which is an integral part of the system is introduced to translate a global user query into local queries by using the mappings that are defined in the XMD.

Integrating user and group preferences for top-k search from distributed web resources

We discuss models of user and group preferences in social networks and the Semantic web. We construct a model for user and group preference querying over RDF data as well as for ordering of answers by aggregation of particular attribute ranking. We have implemented our methods and heuristics into the Tokaf middleware framework prototype. We describe also experiments with Tokaf.In this paper we investigate the problem of automatically identifying the genre of TV programmes. The approach here proposed is based on two foundations: Gaussian mixture models (GMMs) and artificial neural networks (ANNs). Firstly, we use Gaussian mixtures to model the probability distributions of low-level audiovisual features. Secondly, we use the parameters of each mixture model as new feature vectors. Finally, we train a multilayer perceptron (MLP), using GMM parameters as input data, to identify seven television programme genres. We evaluated the effectiveness of the proposed approach testing our system on a large set of data, summing up to more than 100 hours of broadcasted programmes.

Efficient Processing of Narrow Range Queries in Multi-dimensional Data Structures

Multi-dimensional data structures are applied in many real index applications, i.e. data mining, indexing multimedia data, indexing of text documents and so on. Many index structures and algorithms have been proposed. There are two major approaches to multi-dimensional indexing: data structures to indexing metric and vector spaces. R-trees, R*-trees and (B)UB-trees are representatives of the vector data structures. These data structures provide efficient processing of many types of queries, i.e. point queries, range queries and so on. As far as the vector data structures are concerned, the range query retrieves all points in defined hyper box in an n-dimensional space. The narrow range query is an important type of the range query. Its processing is inefficient in vector data structures. Moreover, the efficiency decreases as the dimension of the indexed space increases. We depict an application of the signature for more efficient processing of narrow range queries. The approach puts the signature into the multi-dimensional data structures like R-tree or UB-tree but original functionalities are preserved, i.e. the range query algorithm for general range query. The novel data structure is called the signature data structure, e.g., signature R-tree or signature UB-tree

Designing semantic web services using conceptual model

There are emerging technologies such as SAWSDL or WSMO that extend the current Web Services technologies to so called Semantic Web Services by combining the structural and semantic descriptions of Web services. In this paper, we identify problems that can arise when using these technologies for the design and management of Semantic Web Services and we show that using a conceptual model instead of these technologies can help to solve these problems. We also show how to automatically derive the description of Semantic Web Services represented with existing technologies, concretely with SAWSDL, from the conceptual level because this representation brings other advantages.