This compilation presents the main stages of the development process of the University of Óbuda over three centuries, from industrial education to higher education and finally, to the participants of the Conference. The first legal predecessor, the Secondary Industrial School (the Upper Industrial School located at the Vocational School), during the period of technics, led the way to the establishment of Donát Bánki and Kálmán Kandó, later to the Technical College of Light Industry, then to the establishment of an integrated Budapest Technical College, and onward to the successor, the University of Óbuda in the XXI. Century.
In practice, measurement results are sometimes described by an estimate, which is not the best one as defined in the GUM. Such alternative estimates arise when the result of a measurement is not corrected for all systematic effects. No recommendation exists in the GUM for associating an uncertainty with an uncorrected estimate.
A common choice in guidelines and in the literature is the uncertainty for an alternative estimate y′. It arises from the expected quadratic loss, on which, also in the GUM, the standard uncertainty u(y), and the best estimate y are based. However, such an uncertainty is not a standard uncertainty and we establish, it may not be used for uncertainty propagation.
One consequence is, for example, that pairs (y′, u(y′)) are not to be used in calibration certificates.
Nowadays, concerns related to mankind’s increasing and destructive impact on the environment have influenced and changed the paradigms of product development; this in turn has brought about the appearance of environmental considerations in the creation and design of new products. Numerous industrial sectors have changed their processes of product development and production to meet the ecological requirements. Issues such as the scarcity of natural resources, increasing consumption and increasing pollution also present a number of problems. This article presents a process of comparing new alternatives with a specific methodology of decision-making. It is primarily focused on the use of rare natural materials and resources that are extracted and processed.
Evan Krell, Alaa Sheta, Arun Prassanth Ramaswamy Balasubramanian and Scott A. King
The autonomous navigation of robots in unknown environments is a challenge since it needs the integration of a several subsystems to implement different functionality. It needs drawing a map of the environment, robot map localization, motion planning or path following, implementing the path in real-world, and many others; all have to be implemented simultaneously. Thus, the development of autonomous robot navigation (ARN) problem is essential for the growth of the robotics field of research. In this paper, we present a simulation of a swarm intelligence method is known as Particle Swarm Optimization (PSO) to develop an ARN system that can navigate in an unknown environment, reaching a pre-defined goal and become collision-free. The proposed system is built such that each subsystem manipulates a specific task which integrated to achieve the robot mission. PSO is used to optimize the robot path by providing several waypoints that minimize the robot traveling distance. The Gazebo simulator was used to test the response of the system under various envirvector representing a solution to the optimization problem.onmental conditions. The proposed ARN system maintained robust navigation and avoided the obstacles in different unknown environments. vector representing a solution to the optimization problem.
Oded Koren, Carina Antonia Hallin, Nir Perel and Dror Bendet
Big data research has become an important discipline in information systems research. However, the flood of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts. Thus, research indicates that there is an increasing need to develop more efficient algorithms for treating mixed data in big data for effective decision making. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm that handles the problem of mixed data. We then use big data platforms to implement the algorithm, demonstrating its functionalities by applying the algorithm in a detailed case study. This provides us with a solid basis for performing more targeted profiling for decision making and research using big data. Consequently, the decision makers will be able to treat mixed data, numerical and categorical data, to explain and predict phenomena in the big data ecosystem. Our research includes a detailed end-to-end case study that presents an implementation of the suggested procedure. This demonstrates its capabilities and the advantages that allow it to improve the decision-making process by targeting organizations’ business requirements to a specific cluster[s]/profiles[s] based on the enhancement outcomes.
Attila Zakariás, Tamás László, Csaba Krizbai, Tamás Szabó and Norbert Demeter
In the 21. century, the job of a horticulturist is made easier with the help of a thermogradient table, with which the developmental stage of plants in different temperature conditions can be observed, this way, a plant's optimal ambient temperature can be found. The price of a thermo-gradient table is very high, it can reach thousands of euros. This is the reason why we had the idea of making our own thermo-gradient table, which is much more competitive, and can ease our institution horticulturist’s work.
Thermal conduction is a heat transfer mechanism. It is present in our everyday lives. Studying thermal conductivity helps us better understand the phenomenon of heat conduction. The goal of this paper is to measure the thermal conductivity of various materials and compare results with the values provided by the manufacturers. To achieve this we assembled a measuring instrument and performed measurements on heat insulating materials.
Glue applying machines allow the application of glue to a surface during production. The purpose of this work is to solve certain problems with the development of a new machine. In this paper, measurements and tests made before designing the new machine will be presented. The parts of the machine that that have been designed will also be presented as well as a simulation by finite element method conducted for a part of the machine’s support frame that has a critically dangerous cross-section.
The aim of this paper is to present a granulate manufacturing machine that will be used for recycling plastics in a laboratory at the Sapientia University. In order to produce granulates of recycled plastics the plastic part has to be ground and then extruded. The extruded polymer filament then can be converted to granulates. We present the working principle, design steps, structure and 3D model of a small scale granulate producing machine with a cost-effective approach
This paper discusses the design steps, working principle and structure of a small-scale thermo-plastic extrusion machine that will be used in a laboratory at the Sapientia University. The aim of the laboratory is to present the polymer processing technologies by student-built machines and to stress the importance of plastic recycling. In order to recycle plastic parts a grinding process is necessary, followed by extrusion. During the process the machine melts the polymer and extrudes a filament that can be converted into granulates or used as it is. The structure of the extrusion machine is rather similar to that of a commercial one, however it focuses on presenting the manufacturing principles and cost effectiveness.