Przemyslaw Walkowiak

Reflective Relational Learning for Ontology Alignment

We propose an application of a statistical relational learning method as a means for automatic detection of semantic correspondences between concepts of OWL ontologies. The presented method is based on an algebraic data representation which, in contrast to well-known graphical models, imposes no arbitrary assumption with regard to the data model structure. We use a probabilistic relevance model as the basis for the estimation of the most plausible matches.We experimentally evaluate the proposed method employing datasets developed for the Ontology Alignment Evaluation Initiative (OAEI) Anatomy track, for the task of identifying matches between concepts of AdultMouse Anatomy ontology and NCI Thesaurus ontology on the basis of expert matches partially provided to the system.

IMS-based performance analysis of a MANET controlled by the Delay-Aware NUM system

This paper presents the results of the performance evaluation concerning 3G/3GPP IP Multimedia Subsystem (IMS) applications deployed in a wireless multi-hop network controlled by the Delay-Aware Network Utility Maximization System (DANUMS). The main purpose of the DANUM system is simultaneous service of files and multimedia streams, i.e., types of traffic of different delay requirements. DANUMS combines a queue-level-based approximation of Max Weight Scheduling with a multi-path backpressure-oriented extension of the Optimized Link State Routing (OLSR) protocol. In order to evaluate DANUMS in a 3G videoconferencing scenario, we have integrated an Open IMS Core wired network installation with a wireless DANUMS testbed (playing the role of an IMS access network). The results of experiments presented in the paper show that by applying the DANUMS virtual queuing system, we can achieve a utility-aware coexistence of IMS audiovisual streams and non-IMS flows of different delay requirements.

Integration of DANUM-Based Carrier-Grade Mesh Networks and IMS Infrastructure

We propose a system, referred to as the CARMNET system, that combines the utility-aware flow control and resource allocation for wireless networks with the IMS architecture in order to optimize the Internet access for mobile users. The system utilizes the (DANUMS), which is an application of the NUM framework for wireless mesh networks. The proposed integration of DANUMS with telecom operator infrastructure enables a centralized management of user profiles and requirements across many wireless mesh networks. The utility functions predefined for each type of traffic allow DANUMS to manage the network resources in accordance to the user-perceived utility. The solution is based on the (IMS) architecture and the application of the SIP protocol, which are widely used by telecom operators. As a result of compliance with widely used protocols, the solution can be easily deployed in existing infrastructures.

SIP-based AAA in delay-aware num-oriented wireless mesh networks

Abstract A growing number of mobile nodes that require Internet access is observed. These nodes may be organized in a wireless mesh network in which some of the nodes may serve the access to the Internet and relay other users’ traffic. Such a vision, however, causes the need for carrier-grade reliable Internet sharing solution. This paper presents a CARMNET-XML protocol, which enables to provide Authentication, Authorisation and Accounting AAA functionalities in wireless mesh networks managed by the Delay-Aware Network Utility Maximization System (DANUMS). The presented solution is a part of a CARMNET system, which integrates the utility-oriented resource allocation provided by DANUMS with the IMS architecture. The system allows users to access Internet with a given quality without the need of extending the operator’s infrastructure. Moreover, we define the scenario of the system application involving the use of the proposed protocol that has been experimentally evaluated in a wireless testbed environment

Application of the projective geometry in the density mapping based on CCTV monitoring

In this paper we address a problem of automatic generation of the so-called density maps (heat maps) using video recordings acquired from surveillance CCTV systems in urban areas (CCTV - closed circuit television). Our software for density map estimation increments the accumulation table only in case of detecting a new moving object, resulting in a count of moving objects density map. We also applied an algorithm for projective transformation of image to achieve better accuracy of the moving object density maps. We analyzed the proposed solution for different angles of camera positions. Next the results were compared with the density maps calculated from the top view camera position.

Holistic Entropy Reduction for Collaborative Filtering

Abstract We propose a collaborative filtering (CF) method that uses behavioral data provided as propositions having the RDF-compliant form of (user X, likes, item Y ) triples. The method involves the application of a novel self-configuration technique for the generation of vector-space representations optimized from the information-theoretic perspective. The method, referred to as Holistic Probabilistic Modus Ponendo Ponens (HPMPP), enables reasoning about the likelihood of unknown facts. The proposed vector-space graph representation model is based on the probabilistic apparatus of quantum Information Retrieval and on the compatibility of all operators representing subjects, predicates, objects and facts. The dual graph-vector representation of the available propositional data enables the entropy-reducing transformation and supports the compositionality of mutually compatible representations. As shown in the experiments presented in the paper, the compositionality of the vector-space representations allows an HPMPP-based recommendation system to identify which of the unknown facts having the triple form (user X, likes, item Y ) are the most likely to be true in a way that is both effective and, in contrast to methods proposed so far, fully automatic.