DESIGNING DISTRIBUTED CONTROLLING TESTBED SYSTEM FOR SUPPLY CHAIN AND LOGISTICS IN AUTOMOTIVE INDUSTRY

The arrival of the era of autonomous robots is indisputable. In this paper, innovations in the distributed control systems realized by autonomous guided vehicles in the automotive industry are provided as proof of concept. The main goal of the considered distributed control system design is to bring all-in-one dependent and independent VDA 5050 compliant robots that are easily configurable and manageable with the web-based high-quality user interface responsive business-critical application. Special attention is paid to applying a platform to manage all autonomous IoT based robots in one seamless system. In addition, a "single point of truth" as one of the main issues of modern distributed controlled systems has been considered.

TOOL FOR INTERACTIVE VISUAL ANALYSIS OF LARGE HIERARCHICAL DATA STRUCTURES

In the Big Data era data visualization and exploration systems, as means for data perception and manipulation are facing major challenges. One of the challenges for modern visualization systems is to ensure adequate visual presentation and interaction.  Therefore, within this paper, we present a tool for interactive visualization of data with a hierarchical structure. It is a general-purpose tool that uses a graph-based approach. However, its main focus is on the visual analysis of concept lattices generated as the output of the Formal Concept Analysis algorithm. As the data grow, concept lattice can become complex and hard for visualization and analysis. In order to address this issue, functionalities important for the exploration of the large concept lattices are applied within this tool. The usage of the tool is presented in the example of visualization of concept lattices generated based on the available data on the Canadas open data portal and can be used for exploring the usage of tags within datasets

GENERATING KNOWLEDGE STRUCTURES FROM OPEN DATASETS' TAGS - AN APPROACH BASED ON FORMAL CONCEPT ANALYSIS

Under influence of data transparency initiatives, a variety of institutions have published a significant number of datasets. In most cases, data publishers take advantage of open data portals (ODPs) for making their datasets publicly available. To improve the datasets' discoverability, open data portals (ODPs) group open datasets into categories using various criteria like publishers, institutions, formats, and descriptions. For these purposes, portals take advantage of metadata accompanying datasets. However, a part of metadata may be missing, or may be incomplete or redundant. Each of these situations makes it difficult for users to find appropriate datasets and obtain the desired information. As the number of available datasets grows, this problem becomes easy to notice. This paper is focused on the first step towards decreasing this problem by implementing knowledge structures to be used in situations where a part of datasets' metadata is missing. In particular, we focus on developing knowledge structures capable of suggesting the best match for the category where an uncategorized dataset should belong to. Our approach relies on dataset descriptions provided by users within dataset tags. We take advantage of a formal concept analysis to reveal the shared conceptualization originating from the tags' usage by developing a concept lattice per each category of open datasets. Since tags represent free text metadata entered by users, in this paper we will present a method of optimizing their usage through means of semantic similarity measures based on natural language processing mechanisms. Finally, we will demonstrate the advantage of our proposal by comparing concept lattices generated using formal the concept analysis before and after the optimization process. The main experimental research results will show that our approach is capable of reducing the number of nodes within a lattice more than 40%

SCIENTIFIC REFERENCES IMPORT FROM UNSTRUCTURED DATA

Along teaching scientific research is second most important task for every university and faculty member. Research results are commonly published as journal papers, book chapters or as conference proceedings with the purpose to communicate the findings in academic circles, serve as promotion, or be used for tenure or reapplication. Maintaining the list of scientific references, can be a time consuming and tedious activity. To help along the process we have created a Web application named References that makes the process of editing and formatting the references partially automated and less time consuming. In this paper we present the architecture of the application, its functionalities and newly added feature that enables importing references both from structured and unstructured data

A SOFTWARE SOLUTION FOR THE DEVELOPMENT OF REUSABLE LEARNING CONTENT

The purpose of this paper is to present an approach for creating reusable learning content. Our approach is based on the usage of a software solution we have developed in order to enable creation of reusable and portable learning content. This Windows desktop solution, named ScormCreator, provides users with ability to create learning content according to SCORM reference model because of its ability to provide the transfer of learning content from one system to another, storing, sharing and reuse of the learning content

A NEURAL NETWORK APPROACH FOR THE ANALYSIS OF LIMIT BEARING CAPACITY OF CONTINUOUS BEAMS DEPENDING ON THE CHARACTER OF THE LOAD

Being a part of civil engineering, limit state analysis represents a structural analysis with a goal of developing efficient methods to directly estimate collapse load for a particular structural model. As a theoretical foundation, limit state analysis uses a set of bound (limit) theorems. Limit theorems are based on the law of conservation of energy and are used for a direct definition of the limit state function for failure by plastic collapse or by inadaptation. This study proposes an artificial neural network (ANN) model in order to approximate the residual bending moment, limit and the incremental failure force of continuous beams. The neural network structure applied here is a radial-Gaussian network architecture (RGIN) and complementary training procedure. This structure is intended to be used for civil engineering purposes and it is demonstrated on the example of the two-span continuous beam loaded in the middle of the span that the limit and the incremental failure force can be obtained using neural network approach with sufficient precision and is especially suitable in analysis when some of the model parameters are variable

AN APPROACH FOR COMMUNICATION RELAIBILITY USING SELF-ADAPTIVE AUTONOMIC COMPUTING TECHNIQUES

Interdependency of electric power grids and information and communication technology is a rapidly growing topic. With the introduction of Smart Grid, handling dynamic load tracking, dynamic tariffs, clients that can consume but also produce electricity that can be delivered to the grid has become a part of everyday operational cycles within power supply companies. Hence, electricity distribution and power supply companies are in need for introduction of efficient mechanisms for the optimal tracking and use of available electric energy. In this paper, we describe the low voltage (LV) distribution network monitoring system developed for the Electric Power Industry of Serbia (EPS) electricity distribution company. The system we present is implemented in a way so that it provides abilities to measures, communicates and stores real-time data, translating it into actionable information needed by EPS to meet the described challenges regarding LV distribution networks. The implemented system is using self-adaptive autonomic computing techniques to provide a reliable data transfer from measurement devices deployed in different parts of the LV distribution network

Model application for rapid detection of the exact location when calling an ambulance using OGC Open GeoSMS Standards

The web has penetrated just about every sphere of human interest and using information from the web has become ubiquitous among different categories of users. Medicine has long being using the benefits of modern technologies and without them it cannot function. This paper offers a proposal of use and mutual collaboration of several modern technologies within facilitating the location and communication between persons in need of emergency medical assistance and the emergency head offices, i.e., the ambulance. The main advantage of the proposed model is the technical possibility of implementation and use of these technologies in developing countries and low implementation cost