Special Issue dedicated to the 70th Birthday of Professor Imre J. Rudas (Part I)
Abstract: Conventional robust control design algorithms generate only one solution that fulfils the suboptimal H ∞ norm criterion and thus, leaves no room for further controller tuning. Often, the designed controller is not suitable, because it is either unstable or some structural properties needs to be also satisfied. Then, the designer has to modify the original control problem and to perform the entire synthesis again. This paper proposes a method for improving the H ∞ control synthesis, by introducing extra flexibility into the design process. Based on the formulation of all controllers belonging to a given performance level and Lyapunov function candidate, the paper reveals the group structure, corresponding to performance problem. Based on this group structure, efficient systematic algorithms can be developed for H ∞ controller tuning.
Keywords: performance blending; robust control; geometry
Abstract: Diabetic retinopathy (DR) has been the most frequently occurring complication in the patients suffering from a long-term diabetic condition, that ultimately leads to blindness. Early detection of the disease through biomarkers and effective treatment has been proposed to prevent/delay its occurrence. Several biomarkers have been explored, to help understand the incidence and progression of DR. These included the presence of microaneurysms, exudates, hemorrhages, etc. in the retina of the patients, which contributes to the disease. Investigation of the retinal images from time to time has been proposed as a strategy to prevent blindness. Evaluating the retinal images manually is time-consuming and demands great expertise in the diagnosis of DR. To circumvent such issues computer-aided diagnosis are very promising in the detection of DR. In the present study, we used a DR dataset and applied different classification algorithms in machine learning to predict the occurrence of the DR. The classifiers employed herein, included K-nearest neighbor, random forest classifier, support vector machine, regression tree classifier, logistic regression and the Naïve Bayes theorem. Our results showed that the random forest classification model provided the significant detail of attributes in terms of their importance in the diagnosis of the DR. More importantly, our supervised classification models provided the prediction accuracy of the disease and Naïve Bayes classifier demonstrated highest accuracy of 80.15% in the prediction of DR compared to the others. Additionally, receiver operating characteristics (ROC) analysis, with the classifiers and the area under curve (AUC) represented the fitting results of each classifier. The presented approach can prove to be a potential tool for the ophthalmologist in the early diagnosis tool for DR.
Keywords: diabetic retinopathy (DR); data mining; retinal images; microaneurysms; exudates; classification
Abstract: The behavior-based system (BBS) is a hierarchical structure built upon behavior components, behavior coordination and behavior fusion. The goal of this paper, is to recall the concept of the interpolative fuzzy behavior-based system and to introduce a declarative language especially designed for supporting its implementation and configuration into embedded applications. The suggested Fuzzy Behavior Description Language (FBDL) aids the definition of fuzzy rule-based systems and their connections to form behavior components and behavior coordination as fuzzy state-machines. The suggested language also assists the fuzzy rule definition with variable consequent, to help the creation of behavior fusion functions. For simplifying the definition of hierarchical rule-bases, the structure of rule-base dominancy is also introduced in the FBDL. According to the suggested embedded application concept, the FBDL code, as a parameter configuration, can directly "run" on a built in fuzzy state machine controller, called "FRI Behavior Engine". This case the behavior of the agent controlled by the FRI Behavior Engine, can be directly modified by changing the FBDL code, without reprogramming other parts of the agent controller software.
Keywords: Behavior Based Control; Fuzzy Rule Interpolation; Fuzzy State Machine; Declarative Language; FBDL: Fuzzy Behavior Description Language
Abstract: Nowadays, energy consumption and especially energy saving, are topics of great importance. Recent news regarding global warming has increased the need to save energy. In Finland, one of the major sources of energy consumption is housing. Furthermore, the heating of residential buildings accounts for up to 68% of housing energy consumption. Therefore, it is not surprising that apartment energy consumption and ways to save energy in housing are a popular research topic in Finland. In this paper, two different research areas are introduced: First, a literature survey is presented on the research subjects of energy saving in the area of real estate and housing. The goal is to gain overall knowledge of the current state of energy saving research. The overall conclusion is that knowledge of energy consumption improves efforts toward energy saving. Second, rapid prototyping with off-the-shelf devices and open source software are described. These devices are cheap to install, and a wide range of sensors are available. Consequently, it is important to deal with these topics together. The former studies provide knowledge about the usage of open hardware, open software, and open architectures with the development of prototype systems for gathering data. The literature survey gives us new information on the specialties of energy consumption measuring, offering a new area for modeling and developing prototype systems. These experiences will be taken forward and utilized in energy saving and environmentally sustainable solutions, such as Green Computing.
Keywords: IoT; Prototyping; Energy saving
Abstract: In this paper the TP-based model transformation method is used in order to obtain a Tensor Product-based model of magnetic levitation systems which approximates the behavior of the plant, but exhibiting a numerical approximation error. In order to test the derived TP model, the behavior of the TP model is compared to the laboratory equipment behavior taking into consideration five testing scenarios. Experimental results show that approximation errors are generally low, but depend on model parameters.
Keywords: LTI systems; qLPV models; Tensor Product; magnetic levitation systems; transformation spaces
Abstract: Depression widely affects global populations and is one of the leading causes of disability and suicide. Despite its prevalence, traditional diagnosis for depression is exceedingly associated with misidentification and over-estimation, due to its subjective nature. With advances in affective computing, computational approaches make it possible to discern depression through second party physiological indicators; people observing the behaviour of depressed individuals have measurable changes in their physiological signals. We explored Blood volume pulse (BVP), Galvanic Skin Response (GSR), Skin Temperature (ST) and Pupillary Dilation (PD) from observers as valid sources to indicate depression in others. The behaviour of individuals suffering from four levels of depression was shown in 16 videos to 12 experimental observers whose physiological signals were recorded. We found that depression provokes visceral physiological reactions in observers that we can measure, resulting in neural network classification of 94% accuracy. In contrast, we also found that depression does not provoke strong conscious recognition (‘verbal’) in observers, which is only slightly over a chance level, at 27%.
Keywords: depression detection; physiological signals; observers; galvanic skin response; skin temperature; blood volume pulse; pupillary dilation, affective computing
Abstract: Based on the observation that it is very difficult to combine the mathematical frame- works of the prevailing Lyapunov function-based adaptive controllers and the traditional, optimal control-based “Model Predictive Controllers (MPC)”, a novel adaptive solution was introduced to improve the operation of the “Receding Horizon Controllers (RHC)”. Because at the local optima the gradient of the auxiliary function is zero, Lagrange’s original “Re- duced Gradient Method (RGM)” was replaced by a “Fixed Point Iteration (FPI)”-based algorithm that directly drove this gradient toward zero. According to “Banach’s Fixed Point Theorem” the convergence of the method was guaranteed by a contractive function that gen- erated the iterative sequence. The greatest modeling burden in this approach was the need for the calculation of the Jacobian of the problem, i.e. the gradient of the gradient of the auxiliary function. In the first simulations only a single “Degree of Freedom (DoF)” 2nd order nonlinear system, a van der Pol oscillator was investigated. The attempts that were made to evade the calculation of the Jacobian were finished with the conclusion that at least a rough numerical approximation of this Jacobian generally must be utilized. Though the MPC approach allows the use a great variety of cost functions and dynamical models, math- ematically well established results are available only for quadratic cost functions and “Lin- ear Time-invariant (LTI)” models. For other cost functions and models careful numerical analysis is needed. In this paper the use of non-quadratic cost functions is numerically in- vestigated in the FPI-based adaptive RHC control of 2 DoF 2nd order nonlinear system that consists of two, nonlinearly coupled van der Pol oscillators, is considered. To guarantee lucid calculations simple functions are introduced that map the active parts of the horizon under consideration to the elements of the gradient of the auxiliary function that are calculated an- alytically. For the calculation of the Jacobian only a rough numerical estimation is applied. The simulation results reveal certain limitations of the suggested method.
Keywords: Optimal Control; Model Predictive Control; Receding Horizon Control; Adaptive Control; Fixed Point Iteration-based Adaptive Control; Banach Space; van der Pol Oscillator
Abstract: Complex digital systems usually demand some kind of a multiprocessing architecture. The requirements to be fulfilled (energy and communication efficiency, speed, pipelining, parallelism, the number of component processors, cost, etc.) and their definable priority order may cause conflicts. Therefore, the best choice of the component processors (beside general-purpose CPUs also DSPs, GPUs, FPGAs and other custom hardware) is very important. Such resulting architectures are called heterogeneous multiprocessing architectures (HMA). The system-level synthesis (SLS) methodology can be applied beneficially in designing the HMAs. In this way, the design procedure can get rid of the most intuitive trial and error steps including also the partly reusing of existing structures. Therefore, the SLS methods help to optimize HMAs by reducing the intuitive steps. A high degree of similarity can be observed between HMAs and modern distributed industrial process control systems (DCS). This paper illustrates the procedure of adapting and applying an SLS tool in redesigning of an existing DCS as a benchmark for analyzing, evaluating and comparing the results. Through this adaptation, all such SLS functions become executable on the traditional and standardized documentation form of a DCS.
Keywords: system-level synthesis; high-level synthesis; heterogeneous multiprocessing system; industrial process control
Abstract: Laparoscopic surgery has revolutionized medicine, yet it requires specific skills not traditionally taught to surgeons. Early in training, surgical trainees frequently use low-fidelity “box-trainers” to increase their skills. Evaluation of performance, however, is crude, frequently focusing on speed alone or subjective observations. There is a research collaboration between the Department of Electrical and Computer Engineering and the Department of Surgery, of the Homer Stryker M.D. Medical School, at WMU. The objective of this research is to develop an intelligent box-trainer system which incorporates sensory devices and high definition digital video cameras along with a fuzzy logic-based performance assessment system. Two of the key research problems of this work are the implementation of the tool tip tracking task and the associated performance assessment method. This system will more consistently evaluate trainees and their performance in real time without needing the presence of an independent observer. Using fuzzy logic to capture expert knowledge and fusing it with sensory data for performance assessment purposes is a new approach in the area of laparoscopic surgery training.
Keywords: Intelligent Laparoscopic Surgical Box-Trainer; Laparoscopic Surgical Tool Tip Tracking; Fuzzy Logic-Based Performance Assessment System
Abstract: In our increasingly connected and open World, randomness has become an endangered species. We may soon not have anything private, all out communication, interaction with others becomes publicly available. The only method to secure (temporarily) communication is mixing it with randomness – encoding it with random keys. But massive reuse of the same sources of randomness and rapid development of technology often reveals that used sources were not perfectly random. The Internet security is top-down, based on higher-level certificates, but we can never be quite certain with 'given from above' products in their quality – in order to beat each other producers are 'cutting corners' and even the high-level security certificates are available on Internet dark markets. This clearly shows in tremendous increase of all kind of security accidents, so there is an urgent need for new, independent sources of randomness. Mathematical treatment of randomness is based on infinite concepts, thus useless in practice with devices with finite memory (humans, computers, Internet Of Things). Here is introduced a definition for randomness based on devices with finite memory – k-randomness; it is shown, how this allows to create new randomness in computer games; numerous tests show, that this source is quite on par with established sources of randomness. Besides algorithmically-generated randomness is in computer games present also human-generated randomness - when competing players try to beat each other they invent new moves and tactics, i.e. introduce new randomness. This randomness appears in the sequence of players moves and when combined with the sequences of moves of other players can be used for generating secret keys for symmetric encryption in multi-player game communication system. The method does not use public-key step for creation of shared secret (the key), thus the encryption system does not need any upper-level security authorities.
Keywords: entropy; randomness; encryption; digital games; finite-state machines; human behavior; cyclic order; k-random sequences; player’s actions combination
Abstract: The learning habits among students in higher education, has radically changed in the last 20 years, partially due to the features of the information and digital society, wide scale broadband internet access, proliferation of smart devices and consequently, available online mobile applications. As a result, the use of eLearning systems, in higher education, is a must in the 21st Century. As hardware and software developments periodically foster each other’s progression, the technological developments, including more and more sophisticated eLearning platforms and available mobile applications, triggers a multiplicative, radical change in educational practices and methodologies. This paper presents an extended version of the Technology Acceptance Model (xTAM), applying Structural Equation Modeling (SEM) with the AMOS program. It focuses on the motivation and usage intention of eLearning systems, among early Z generation students, in higher education and highlights the digital learning aspects and smart tool usages in the Hungarian environment. The evaluation of the above external factors illustrates the behavior of students, when using eLearning systems.
Keywords: IT security awareness; xTAM; SEM; eLearning systems; digital learning; Z generation; smart tools
Abstract: Self-driving technologies introduced new challenges to the control engineering community. Autonomous vehicles with limited automation capabilities require constant human supervision, and human drivers have to be able to take back control at any time, which is called handover. This is a critical process in terms of safety, thus appropriate handover modeling is fundamental in design, simulation and education related to selfdriving cars. This article reviews the literature of handover processes, situation awareness and control-oriented human driver models. It unifies the psychological and physiological control theory models to create a parameterized engineering tool to quantify the handover processes.
Keywords: autonomous vehicle safety; situation awareness; control-oriented model; takeover; hands-off control