Special Issue: Information and Communication Technology

Luc De Raedt, Yves Deville, Marc Bui, Dieu-Linh Truong, Editor Emeritus, Anton Železnikar, Drago Torkar, Jožef Stefan, Maria Ganzha, Wiesław Pawłowski, Aleksander Denisiuk, Editorial Board (+26 others)
2017 unpublished
Person tracking in camera network is still an open subject nowadays. The main challenge for this problem is how to link exactly individual trajectories when people move in a camera FOV (Field of View) or switch to other ones. This refers to solve the problem of person re-identification (Re-ID) in tracking process. A popular method for this is assigning the current position with the previous one based on the minimum distance between them. This is called as person identification by tracking. In
more » ... is work, we approach tracking by identification, which means the trajectory assignment is done by the person identity (ID) determined at each video frame. In order to improve the accuracy of vision-based person tracking, we focus on accuracy enhancement for person identification by adding ID of the WiFi-enabled device held by each person. A fusion scheme of WiFi and visual signals is proposed in this work for person tracking. An optimal assignment and Kalman filter are used in this combination to assign the position observations and predicted states from camera and WiFi systems. The correction step of Kalman filter is then applied for each tracker to give out state estimations of locations. The fusion method allows tracking by identification in non-overlapping cameras, with clear identity information taken from WiFi adapter. The evaluation on a multi-model dataset show outperforming tracking results of the proposed fusion method in comparison with vision-based only method. Povzetek: Opisana je metoda sledenja osebam preko kamer s pomočjo zlivanja podatkov. Video retrieval is a challenging task in computer vision, especially with complex queries. In this paper, we consider a new type of complex query which simultaneously covers person and location information. The aim to search a specific person in a specific location. Bag-Of-Visual-Words (BOW) is widely known as an effective model for presenting rich-textured objects and scenes of places. Meanwhile, deep features are powerful for faces. Based on such state-of-the-art approaches, we introduce a framework to leverage BOW model and deep features for person-place video retrieval. First, we propose to use a linear kernel classifier instead of using L 2 distance to estimate the similarity of faces, given faces are represented by deep features. Second, scene tracking is employed to deal with the cases face of the query person is not detected. Third, we evaluate several strategies for fusing individual person search and location search results. Experiments were conducted on standard benchmark dataset (TRECVID Instance Search 2016) with more than 300 GB in storage and 464 hours in duration. Povzetek: V prispevku je opisana metoda povpraševanja po osebi in lokaciji iz video vsebin. Informatica 41 (2017) 149-158 V.-T. Nguyen et al. This paper proposes a new data model, named Key-Value-Links (KVL), to help in-memory store utilizes RDMA efficiently. The KVL data model is essentially a key-value model with several extensions. This model organizes data as a network of items in which items are connected to each other through links. Each link is a pointer to the address of linked item and is embedded into the item establishing this link. Organizing datasets using the KVL model enables applications making use RDMA-Reads to directly fetch items at the server at very high speed. Since link chasing bypasses the CPU at the server side, this operation allows the client to read items at extremely low latency and reduces much workload at data nodes. Furthermore, our model well fits many real-life applications ranging from graph exploration and map matching to dynamic web page creation. We also developed an in-memory store utilizing the KVL model named KELI. The results of experiments on real-life workload indicate that KELI, without being applied much optimization, easily outperform Memcached, a popular in-memory key-value store, in many cases. Povzetek: Predlagan je nov podatkovni model, imenovan Key-Value-Links (povezave ključnih vrednosti). The purpose of a Network Intrusion Detection System (NIDS) is to monitor network traffic such to detect malicious usages of network facilities. NIDSs can also be part of the affected network facilities and be the subject of attacks aiming at degrading their detection capabilities. The present paper investigates such vulnerabilities in a recent consensus-based NIDS proposal [1]. This system uses an average consensus algorithm to share information among the NIDS modules and to develop coordinated responses to network intrusions. It is known however that consensus algorithms are not resilient to compromised nodes sharing falsified information, i.e. they can be the target of Byzantine attacks. Our work proposes two different strategies aiming at identifying compromised NIDS modules sharing falsified information. Also, a simple approach is proposed to isolate compromised modules, returning the NIDS into a non-compromised state. Validations of the defense strategies are provided through several simulations of Distributed Denial of Service attacks using the NSL-KDD data set. The efficiency of the proposed methods at identifying compromised NIDS nodes and maintaining the accuracy of the NIDS is compared. The computational cost for protecting the consensus-based NIDS against Byzantine attacks is evaluated. Finally we analyze the behavior of the consensus-based NIDS once a compromised module has been isolated. Povzetek: Sistemi za odkrivanje napadov v omrežjih temeljijo na pojavih nenavadnega prometa, vendar so občutljivi na napade. Prispevek opisuje obrambo pred bizantinskimi napadi. Recently, serval reasoners for very expressive fuzzy Description Logics have been implemented. However, in some cases, applications do not require all the reasoner services and would benefit from the efficiency of just certain reasoning tasks. To this scope, we are interested in the individual fuzzy classification issue. In fact, decision-making applications for real world domain is often based on classifying new situations into fuzzy categories. Therefore, we propose Fuzzy Realizer to offer an effective classification even with imprecise/vague or incomplete knowledge so that appropriate decision can be made. Fuzzy Realizer is a Java prototype implementation for realizing fuzzy ontologies. It supports the well-known fuzzy description logic Z SHOIN (D). It allows (i) fuzzy concrete domains, (ii) modified and (iii) weighted concepts. It is able to (i) classify new individuals, even with incomplete descriptions, (ii) provide a more human-oriented classification by hiding the crisp boundaries between different fuzzy categories and (iii) to populate fuzzy ontologies which address an aspect of fuzzy ontologies evolution, a topic which is rarely discussed. Povzetek: Razvit je postopek za individualno klasifikacijo s pomočjo mehke logike. The first starting point of this paper is the broadly accepted idea of employing, as a promising methodology, an artificial semantic language-intermediary for the realization of automatic cross-lingual intelligent information access to natural language (NL) texts on the Web. The second one is the emergence in computational semantics during 2013-2016 of great interest in the semantic formalism (more exactly, notation) called Abstract Meaning Representation (AMR). This formalism was introduced in 2013 in an ACL publication by a group consisting of ten researchers from UK and USA. This paper shows that much broader prospects for creating semantic languages-intermediaries in comparison with AMR are opened by the theory of K-representations (TKR), developed by V. A. Fomichov. The basic mathematical model of TKR describes the regularities of NL structured meanings. The mathematical essence is that this model introduces a system consisting of ten partial operations on conceptual structures. Initial version of this model was published in 1996 in Informatica (Slovenia). The second version of the model (stated in a monograph released by Springer in 2010) defines a class of formal languages called SK-languages (standard knowledge languages ). It is demonstrated that SK-languages allow us to simulate all expressive mechanisms of AMR. The advantages in comparison with AMR are, in particular, the possibilities to construct semantic representations of compound infinitive constructions (expressing goals, commitments, etc), of compound descriptions of notions and sets, and of complex discourses and knowledge pieces. Povzetek: Opisani so SK-jeziki za fleksibilno med-jezikovno dostopanje. Agent technology has proved its ability and efficiency in modelling complex distributed applications. During the last two decades, several MAS development methodologies have been proposed like, for instance, Gaia, Tropos and PASSI. Although these methodologies have made significant contributions to meet several challenges in the MAS development field, most of them do not use formal techniques. Formal methods, as it is well known, play a significant role in developing more reliable and robust MAS. This paper presents the Formal-PASSI methodology. Formal-PASSI is an extension of the well-known PASSI methodology. The extension consists mainly of the integration of a new formal model to the design process. The new model is based on the Maude language and its extension Maude-Strategy. It aims at offering a formal description of the MAS under development by a Model-to-Text transformation. The generated formal description is then used to validate some PASSI behavioural diagrams and check properties of both single & multi-agent abstraction levels before passing to the code model. The integration of formal methods into PASSI design process seems a good way to ensure the development of high quality agentbased applications. The proposed approach is supported by a tool (F-PTK) that we have developed and illustrated throughout the ATM case study. Povzetek: V članku je predstavljena formalna PASSI MAS metodologija, tj. multi-agentna metodologija. We present a web application to detect risks related to sexually transmitted infections (STIs). The application works as a questionnaire about sexual behaviour and risk factors for STIs and, based on the answers, calculates the risk of being infected. The application also works as an informational tool with educating about STIs and prevention. It uses a combination of approaches from computer science and psychology to deliver a usable, clean interface with which the user feels safe. Povzetek: Predstavljen je študentski projekt za detekcijo spolno prenosljivih bolezni, dosegljiv na aspo.mf.uni-lj.si.
fatcat:cifuetllzbcw5fqsrodjg7uuwy