Special Issue dedicated to the 70th Birthday of Professor Imre J. Rudas (Part II)
Abstract: Automation of industrial and consumer products has reached the level on which systems provide for the capability to supervise decisions on physical actions and execution of these actions. Development of these industrial products proceed during their full lifecycle requiring lifecycle integration of innovation, manufacturing, and application as well as utilization the recently emerged methodology of continuous engineering. Engineering in the above level of industrial technology requires contextually integrated model system which serves all research, development, production, and operational activities during the integrated life cycle of product. Smart product requires smart model system which has the capability to recognize situation and apply it at decision on values of relevant product object parameters in virtual to control physical operation of product. This paper introduces recent contributions in modeling for smart engineering. It starts with a novel general model of integrated smart engineering system. Considering this model, smart engineering specific upgrade of formerly published concept of virtual engineering space (VES) is introduced. VES upgrade concentrates on research as key issue in giving smart characteristics for contexts in VES model system. Following this, contextual driving of object parameters is outlined for integrated smart engineering system. The remaining part of paper introduces concept and plan of virtual research laboratory (VRL) in close connection with modeling for integrated smart engineering system. Plans are outlined for next future implementation of the VRL concept and methodology at the Doctoral School of Applied Informatics and Applied Mathematics, Óbuda University. The laboratory system consists of research eligible configuration of the 3DEXPERIENCE engineering modeling platform. It is accessed in the professional cloud of Dassault Systémes.
Keywords: system level model of engineering structure; virtual engineering space (VES); contextual driving structure in engineering model; virtual research laboratory (VRL)
Abstract: Modeling the effect of therapeutic drugs on tumor dynamics is a fundamental step that leads to the optimization of cancer therapy using mathematical tools. We discuss three tumor dynamics models starting from a minimalist model describing the effect of bevacizumab based on experiments where the measurements can be defined with one parameter exponential curves, and finally discussing a more complex model that describes the effect of pegylated liposomal doxorubicin (PLD) based on measurements with richer dynamics. The differential equations are created with the analogy of formal reaction kinetics, enabling universal interpretation of the modeled phenomena. Parametric identification is carried out based on measurements to prove the efficacy of the models. The results of the parametric identification show that the discussed models can sufficiently describe the experimental results. The between-subject variability of the model parameters is given which highlights the parameters that may change the most in a virtual patient set.
Keywords: antiangiogenic therapy; chemotherapy; pegylated liposomal doxorubicin; stochastic approximation expectation maximization
Abstract: The person localization by ultra-wideband (UWB) sensors is a challenging field attracting researchers worldwide. Whereas the issue of the person localization in 2-dimensional space (2D) has been discussed in many articles, only a few papers have been devoted to the people localization in 3-dimensional space (3D). Combining two 3D localization methods a new approach to the person localization in 3D can be obtained to fill this gap. The new 3D localization method introduced in this paper is referred to as the Taylor series based localization method (TSM). This method combines the 3D-2D method of object localization in 3D with the conventional method of Taylor series. The performance properties of the introduced TSM will be illustrated via the experimental scenario intent on the through-the-wall localization of a moving person by a multistatic UWB radar system.
Keywords: 3D localization; signal processing; target tracking; Taylor series based localization method; UWB radar
Abstract: In the digital age, being able to determine the relationships between attributes in datasets is advantageous for many fields of information technology, such as data mining, machine learning, etc. There are inherent rules, functional dependencies that are derived from the nature of the data, of which many are not trivially obvious to the human data manager. This paper presents a new method to extract such relationships. It uses Sequential Indexing Table structures that can implicitly indicate if the values of an attribute are determined by the combination of the values of the attributes preceding it in the layered architecture, i.e. is functionally dependent on those attributes. A new algorithm is given to use this feature to extract functional dependencies, and the performance is analyzed using real-life datasets.
Keywords: functional dependency extraction; data processing; functional dependencies; data mining; sequential indexing tables
Abstract: The goal of this paper is to examine the friction behaviour in a one-degree mechanical system designed for precise tracking. Friction as one of the main disturbances present in this system strongly influences its performance, which is most visible during the velocity reversals. Identification and compensation of the friction are crucial to achieve high tracking accuracy at very low velocities. In this paper the procedure for identification of static and dynamic frictional parameters of LuGre is presented. The experimental results show characteristic behaviours of friction present both in sliding and in presliding regime. Furthermore, it is experimentally proven in several control scenarios that dynamic friction model compensation causes significant decrease of trajectory tracking error.
Keywords: friction dynamic models; friction identification; precise tracking; the active disturbance rejection paradigm; control of astronomic mounts
Abstract: Advanced control in the area of turbojet engines defines many different applied complex control strategies. Highly theoretical approaches and designs are often presented in this area. The article is aimed at practical aspects of adaptive controller design for a class of small turbojet engines in triple loop control architecture. The article presents a non-linear dynamic model of a small turbojet engine taking in account the environmental conditions, which it operates in. The designed triple loop control architecture shows increased precision of control keeping acceleration schedule of the simulated engine and is not susceptible to outer disturbances. The article shows pilot dynamic simulation tests, showing feasibility of the taken approach. It can also be used for other classes of turbojet engines as well other similar technical systems.
Keywords: turbojet engines; adaptive control; non-linear system; dynamic modelling
Abstract: The past 3 decades are characterized by the introduction of digital tools in the manufacturing sector, and by the advent of mechatronics being used for repetitive and fast material handling within logistics. Retrospectively this time is referred as the 3rd Industrial Revolution. Presently, the cyber-physical systems and cyber-physical production systems are being referenced as substituents of the 4th Industrial Revolution. The Authors have selected some outstanding episodes within this transition time to highlight the Hungarian successful achievements developed and implemented by talented researchers and innovative ideas by far-looking professors. The article also offers elements of visions for technology development, focusing on the new results of robotics and on biotransformation in manufacturing.
Keywords: Technology Platforms; Strategic Research Agenda; Robotics
Abstract: In the constantly growing and widening field of forensic science, crime maps are used in versatile ways. The representation of the data and analysis could offer some steps toward crime prevention and helps understand patterns, in terms of a timely distribution of crime types. Clustering is able to help identify criminal hot-spots and additional analysis may determine which areas require intervention. The aim of this study is to present an analysis of criminal information related to Hungary, in annual and monthly breakdown.
Keywords: clustering; Fuzzy C-Means; crime hot-spots; forensic science; crime prevention
Abstract: This paper presents the design of a reduced complexity state convergence controller, termed as composite state convergence controller, for a single degree-of- freedom nonlinear telerobotic system. First, nonlinear master and slave models are feedback-linearized and composite states are formed by combining their respective position and velocity signals. These composite master and slave states along with the operator’s force are then transmitted across the communication channel instead of full states. In this way, the complexity of communication structure is reduced. An augmented system composed of composite master and slave states is finally constructed and method of state convergence is applied to compute the control gains of the proposed scheme. It is shown that position and velocity states of the master and slave systems still converge in the absence and presence of time delays, even though the design is based on the reduced order composite system. The validity of the proposed scheme is confirmed through MATLAB simulations as well as semi-real time experiments.
Keywords: state convergence; nonlinear telerobotic system; feedback linearization; composite states
Abstract: Nowadays, when computers and computer systems are almost omnipresent and are part of most households and most people have access to them, they are more vulnerable than ever. Today, protection and security of computer networks and systems using passive protection does not suffice anymore. One has to anticipate attacks and be a step ahead of the attackers. To achieve this type of security, one has to employ active protection techniques, such as digital baits – honeypots. The primary goal of using honeypots is to divert the interest of potential attackers from other really important targets within a particular computer network. The secondary goal is to acquire information about the attackers' activities and methods. Subsequently, these data are thoroughly analysed. By analysing the attacks, security improvement measures aimed at the particular network and/or computer system may be proposed in order to prevent threats. The goal of this paper is to contribute to computer security by proposing a clustered, high-interaction-honeypot-based security system.
Keywords: security; honeypot; intrusion detection system; malware; clustered honeypot
Abstract. Correlation coefficients (association measures) were introduced more than one hundred years ago as measures of relationship between variables that usually belong to one of the following basic types: continuous, ordinal, or categorical. Nowadays, it appears the growing demand for the development of new correlation coefficients for measuring associations between variables or objects with more sophisticated structures. The paper presents a non-statistical, functional approach to the study of correlation coefficients. It discusses the methods of construction of correlation coefficients using similarity and dissimilarity measures. Generally, all these measures are considered as functions defined on the underlying (universal) domain and satisfying some sets of properties. The methods of construction of correlation functions on the universal domain can be easily applied for constructing correlation coefficients for specific types of data. The paper introduces a new class of correlation functions, satisfying a weaker set of properties than the previously considered correlation functions (association measures) defined on a set with involution (negation) operation called here strong correlation functions. The methods of constructing both types of correlation functions are discussed. The one-to-one correspondence between the strong correlation functions and the bipolar similarity and dissimilarity functions is established. The theoretical results illustrated by examples of construction of classical Pearson’s product-moment correlation coefficient, Spearman’s and Kendall’s rank correlation coefficients, etc. from similarity and dissimilarity functions.
Keywords: similarity; dissimilarity; correlation; association; Spearman’s and Kendall’s rank correlations; Pearson’s correlation; cosine similarity, and cosine correlation
Abstract: In this paper a coarse-grain model is presented that describes the major features of cell growth and cell cycle in Saccharomyces cerevisiae. Central for the construction of the growth and cell cycle model has been the large amount of scientific papers covering the description of cellular growth in steady-state and perturbed growth conditions, describing ribosome and protein contents, and the description of cell cycle progression as percentage of budded cells (cells that have entered S-phase). The coarse model is composed by i) a growth module, i.e. a set of ODEs representing the dynamics of synthesis/degradation of ribosomes and proteins, and ii) a cell cycle module, i.e. a set of three consecutive timers (T1, T2 and TB) that temporally accounts for the yeast cell cycle, underlying the length of the G1 phase (timer T1 plus T2) and of the budded phase (timer TB) entailing S, G2 and M phases. The growth module acts as a master, setting the length of the first of the three sequential timers. Main results coming from the mathematical analysis involve the qualitative behavior of the system, constraining ribosome synthesis and growth to the set of model parameters. Further results involve the generalization of a known constraint that involves the lengths of the cycles of parent and daughter cells, and accounts for the genealogical age heterogeneity, typical of budding yeast Saccharomyces cerevisiae.
Keywords: Linear ODE models, Systems Biology