Abstract: This paper presents one approach to solve server selection problem during search in distributed library systems. Information retrieval systems are aimed at providing infrastructure and means of finding specific documents in a collection, such that they satisfy specific information need. Distributed information retrieval systems aims at providing the same capabilities, but in an environment of distributed and heterogeneous document repositories. In such an information retrieval system, an important step is server selection i.e. selection of servers that will be included in a search operation, and to whom the query will be sent. Other problems that are specific to distributed information retrieval systems are query formatting for different servers, and results merging and ranking. These are special class of problems, and are not the subject of this paper. One of the first institutions to massively adopt information retrieval systems were libraries. Currently, almost every library has an online search capability. Using these search capabilities, a client application can perform search across a network of library servers. This paper is focused on a method for server selection in such search scenario.

Abstract: Since the late 1990s, with the raising of eGovernment concepts and the increase use of ICT by public administration entities, the need for collaboration among these organizations is a reality with which systems, managers and other stakeholders must deal. In order to increase performance, to supply the online services, and the search for cost reductions the governments paradigms focus, now more than ever, on how to better manage information. As the need of these ‘inter operations’ is real, interoperability is a key factor for organizations facing with collaborative-cooperative environments. The modern architecture of information systems (ISs) is based on distributed networks with a grand challenge of representing and sharing knowledge managed by ISs and consequently, to remove semantics interoperability barriers. This paper presents a literature review and a research method that defines the mechanisms for the creation of guidelines, attributes and an assessment methodology in public administration domain. The presented research strategy identifies the basic phases and activities, purposing a structure of how to collect and compose the guidelines, and how to define an assessment method through the help of semantic technologies.

Abstract: Social networks' users usually post status updates of their opinions on and reactions to events almost instantly. Because of this, pre-announced events, especially ones that divide the public, lead to generation of a large quantity of status updates in the days just before and after the event. Status updates published before the event usually contain speculations about what will happen, and those published after represent the reaction to what actually happened. In this paper we analyze the change of sentiment in tweets collected in following few days after a specific preannounced event. We also discuss can this analysis be used for prediction, as an indicator of to which extent will this event fulfill its designated long term goal.

Abstract: With the emergence of Linked Data, DBpedia has steadily grown to become one of the largest and most important structured knowledge sources we know of today. Adopting Wikipedia’s practice of entrusting the community with most of the work, the DBpedia internationalization committee has made a major step towards the move from unstructured to structured knowledge on the Web. Still, with new languages come new challenges. In this paper, we inspect some common obstacles that need to be tackled in order to add one more language to this popular data hub, but also some that haven’t been encountered before in this domain. More specifically, we explore the digraphic nature of the Serbian language, analyze the state of the DBpedia Extraction Framework with respect to its support for languages that use multiple scripts, and propose solutions towards overcoming this problem. Finally, we deploy the first digraphic DBpedia edition, taking the leading position amongst all DBpedia versions in the percentage of all covered Wikipedia templates, and all template occurrences in Wikipedia that are mapped, while adding a valuable new chapter to the DBpedia project and enriching the Linked Open Data Cloud even further.

Abstract: The development of information and communication technologies and the rapid development of the IT sector have greatly contributed to the development of society in general. In recent years, the techniques for measuring the development of information and communication technologies have begun to rise. Subject of this study is to measure the development of the countries’ ICT infrastructure, using statistical composite index. In order to measure the development, we will use composite IDI index, with special emphasis on the improvement of the index. In addition to the existing IDI method of ranking, we will use the I-distance. A comparative analysis of the created and the existing indexes shall be given.

Abstract: The paper presents an example of a system for storing information about rulebooks which are used for evaluation of scientific-research results of researchers. System is based on the CERIF data model and it was implemented as extension of the current CRIS system of the University of Novi Sad (CRIS UNS), where it is actively used by research community. Case study for modelling rulebook which was issued by the Ministry of Education and Science of the Republic of Serbia was presented in this paper.

Abstract: This paper describes an independent, modular software component that enables search and retrieval of scientific research data from CRIS system in accordance to SRU/W standard. The component is implemented as an extension of existing CRIS UNS system of University of Novi Sad.

Abstract: Grants (non-repayable funds) are disbursed by provincial bodies in Autonomous Province Vojvodina to diverse recipients: local governments, vulnerable social groups, national communities, religious communities, nonprofit entities, educational institutions, churches, small and medium-sized businesses, or to individual citizens. Provincial administrative authorities grant funds for specific purposes by publishing calls for proposals. The purpose of this paper was to present results achieved and experiences gained in development and implementation of an electronic service facilitating non-repayable funds management process in a way to provide for horizontal integration of fund allocations in different sectors. Therefore, the paper presents the context of the development, the main functional and non-functional features, and deployment of the government grants management electronic service serving both the applicants and the provincial government institutions.

Abstract: Lab practicing as a common form of experiential learning is important in engineering education. With the increase of number of students, it becomes a challenge to achieve an efficient organization of lab practicing activities. To address observed drawbacks of standard approaches, in this paper, a pipelined scheduling of timeslots is described and applied in multi-teacher classroom. Innovations in lab practicing policy require new software tools that support new policies and make them possible and effective. Supporting tool for collaborative lab practicing management was implemented on Android tablets and Google Drive Spreadsheet cloud platform. The tool was designed with principles of dashboard interfaces design to be efficient for use in a dynamic lab environment. Effective design solutions within limitations of spreadsheet platform were presented. The tool is used and monitored for two semesters. Errors detection and correction, as the main potential risk, were analyzed and it is shown that users successfully solved with tablet interface all but one type of error, which was corrected from web interface. Main findings confirmed that beside a number of potential risks and sources of errors, it is possible to build a dependent application on spreadsheet platform for use in complex environment of collaborative lab practicing management.

Abstract: The paper deals with IEEE 1484.12.1 – 2002 Standard for Learning Object Metadata (LOM) and IMS Learner Information Package (LIP) specification. The main goal is to develop Web-based Learning System which is characterized with high level of adaptability. The LOM is used for the description of learning objects, making possible the creation of well-structured descriptions of learning resources, while LIP describes learner’s profile. Conformity criteria for best matching learning object and learner’s profile are investigated. Previously introduced solutions are based on If-Then rules with low level of adaptability. The original contribution of this work is the adoption of similarity relation and more general logical operations in order to achieve greater adaptability. It is shown how the similarity relation, as well as general logical operations, could be incorporated in Web-based Learning System.

Abstract: Like with Wireless Sensor Networks (WSN) there are two main goals of Sensor Web: the optimal deployment of sensor nodes, and the maximization of sensor network lifetime. They are particularly important considering critical event applications, like residential fire detection, because of the fact that the topology of sensor nodes and the network lifetime have a dramatic impact on the overall network effectiveness and the efficiency of its operation. One of the possible solutions may be the development of an appropriate algorithm for minimizing the expected energy consumption as a function of specific sensor nodes topology. In this paper we have analyzed a hexagonal sensor deployment scheme and proposed specific algorithm for energy saving by scheduling specific active-passive pattern of sensor nodes.

Abstract: The deployment of increasing number of real-time services over communication networks raises essential issues for assurance of the quality of services, which requires a clear picture of the network performance. The availability of accurate statistics helps to estimate the traffic flows, to find service degradation due to congestion, as well as to optimize routing. Presently, for network measurement and monitoring are applied various methods which require separate infrastructure, and thus, higher expenses. Most methods are not capable to meet all monitoring requirements, some are not accurate or granular enough, others are adding network load or lack scalability. The paper provides a concept for using Software Defined Networking as a unified monitoring solution, by suggesting how to measure link utilization, packet loss and delay. Initially, some monitoring methods are presented, and the opportunity of using OpenFlow enabled topology in Software Defined Networking for monitoring. The paper proposes a monitoring concept for measuring link usage, packet loss and delay.

Abstract: Vehicle detection and classification is a very actual problem, because vehicle count and classification data are important inputs for traffic operation, pavement design, transportation planning and other applications. Magnetic detector based sensors provide many advantages compared to other technologies. In this work a new vehicle detection and classification method is presented using a single magnetic detector based system. Due to the relatively big number of false detections caused by vehicles with high metallic content passing in the neighboring lane, a technique for false detection filtering is also presented. Vehicle classes are determined using a feedforward neural network which is implemented in the microcontroller of the detector, together with the detection algorithm and the algorithm used for determining the neural network inputs. The gathering of training samples and testing of the trained neural network have been done in real environment. For the training of the neural network the back-propagation algorithm has been used with different training parameters.

Abstract: Wearable motion sensors provide data that directly reflect the motion of individual body parts and that can enable the development of advanced tracking and analysis procedures. Today widely available light and small size sensors make a wide range of practical measurements feasible. As these sensors are somewhat inaccurate, they are primarily suitable for monitoring motion dynamics. A number of studies conducted so far show that these sensors can be efficiently used for motion pattern identification and classification enabling general motion analysis and evaluation. To make full advantage of the feasibility and widespread use of these sensors, it is necessary to provide for, in terms of lifetime and computational complexity, efficient calibration and data analysis procedures.

Abstract: In this paper, we describe a web-based tool for the visualization and analysis of real-time output data of a professional optical tracking system – Qualisys. Optical tracking systems are used for capturing the positions and movements of various objects in space with the aid of several high-speed cameras and reflective markers. The positions of individual markers are represented as time-dependent 3D spatial points. Tracking software running on a single dedicated computer enables the visualization of data as an interactive 3D scene. The main goal of our work is to enable a real-time visualization of this 3D scene on multiple computers simultaneously with the aid of modern web technologies and tools. The framework is based on an interactive Node.js web server, which streams data from the Qualisys tracking software, reformats it and sends it to a web browser through a fast WebSocket protocol. The web browser enables the visualization of the 3D scene based on WebGL technology. The tool described in this paper enables a synchronized visualization of the tracking data on multiple computers simultaneously and thus represents an excellent teaching and presentation tool of optical motion capture techniques.

Abstract: Modern smart phone devices are equipped with several space positioning sensors. Most of them are inaccurate low-cost silicon devices, not designed for motion tracking. The paper presents the results of several constraint motion tracking experiments using iPhone 4 sensors. The experiments confirm that the best choice for motion tracking is sensor fusion - a simultaneous usage of accelerometer and gyroscope data. While accelerometer data are less accurate than gyroscope data, they are still good enough for a number of various motion-connected applications.

Abstract: Eigenvalues Driven Gaussian Selection (EDGS) is used in this paper in order to reduce the computational complexity of an acoustic processing module of a medium vocabulary continuous speech recognition system for the Serbian language, based on Hidden Markov Models (HMMs) with the diagonal covariance matrices. The optimal values of five different parameters are discussed: overlap threshold and overlap percentage used for clustering, pruning threshold and pruning percentage used for decoding, as well as newly introduced discard threshold. Significant reduction of computational complexity is obtained, without noticeable degradation in error rate.

Abstract: Knowledge management (KM) can support small and medium enterprises and individual professionals to access information and knowledge on recent developments and innovations in their field, and to share the best practices available. It is particularly important for the healthcare professional field where a lot of changes appear and professionals need to be aware of them in order to better help people. This paper presents a concept and a prototype of a web-based KM platform in support of the Bulgarian community of professionals in the field of Optometry and Eye Optics.

Abstract: In this paper, influence diagram with fuzzy probability values, as a graphical tool for the diagnostic reasoning in power system has been proposed. Instead of Bayesian networks that are using conditional probability tables, often difficult or impossible to obtain, a verbal expression of probabilistic uncertainty, represented by fuzzy sets is used in this paper. The proposed methodology enables both type of inference support: bottom-up and topdown inference, including decision nodes in the analysis. This inference engine is illustrated on the case of the detection of the cause of excessive tripping of transformer breaker in the substation.

Abstract: In this paper we propose a method for scoliosis screening based on mathematical model of linear fuzzy space and image processing using self-organizing maps. Taking into account that the number of school age children with some sort of a spine deformity in Serbia exceeds 27%, this paper’s research came out of a need to develop and implement some novel, effective and primarily economical methods for automated diagnostics of some spine disorders. The ultimate goal however is to produce a suite of mobile applications capable of automated diagnostic of some spine disorders, which could be used by non-medically educated school personal for the purpose of early diagnosis i.e. screening for those spine disorders within adolescents (when the early physical therapy and scoliotic bracing proves to be most effective, and thus least monetary demanding compared to some other invasive means of clinical therapy).