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The possibilities of using time series for predicting changes in a technical parameter in real time are considered. Forecasting is carried out using simple adaptive models. The prediction procedure should be performed in the background in the microcontroller. Selected adaptive polynomial models of zero, first and second order, based on the method of multiple exponential smoothing. Models are modified...
The paper provides conceptual analysis of creative and entrepreneurial behavior in digital economy. Despite recent advances in statistical inference, the casual interpretation of models that try to predict behavior based on observational data can be dangerous. Causal interpretation can result in reproducing and amplifying unwanted social phenomena e.g. stigmatization. Thus, the information security...
Characterizing neural responses and behavior require large scale simulation of brain circuits. Spatio-temporal information processing in large scale neural simulations often require compromises between computing resources and realistic details to be represented. In this work, we compared the implementations of point neuron models and biophysically detailed neuron models on serial and parallel hardware...
Several interconnected brain circuits such as cerebellum, cerebral cortex, thalamus and basal ganglia process motor information in many species including mammals. Interconnection between basal ganglia and cerebellum through thalamus and cortex may influence the pathways involved in basal ganglia processing. Malfunctions in the neural circuitry of basal ganglia influenced by modifications in the dopaminergic...
Neuronal models and real-time simulations of large-scale neural networks allow hypothesis testing of physiological data and for predicting neurological disorders. Simulators using web technologies serve as educational tools in addition to allowing experimentalists make predictions on experimental hypotheses. In this paper, we have developed a web-based neuron and network simulator to model spatio-temporal...
The plasmodium of the true slime mold, physarum polycephalum is a large amoeboid organism, and it can sense environmental information and change its behavior depending on the situations. For example, when the expanding front touches the wall, other part will start to move and become a new front in a few minutes. It seems physarum transmits information from one side to another. This property must be...
Air-fuel ratio control is a crucial problem for engine control since it is one of the most important issues related to pollution reduction. The main difficulty in air-fuel ratio control is the time-varying delay. We propose a new model that includes the delay. This model is identified using real dataset from an engine test bench. The time-varying delay is made constant by using a change of domain...
This paper considers the problem of block-oriented Wiener systems control. Designing controllers for Wiener systems face many challenges, for instance, parameter uncertainty and lack of state measurement. To address these issues, the input-output response of a class of Wiener systems is represented with a simple fractional-order model, then a closed-loop model reference fractional adaptive controller...
Nowadays complex and dynamic business environments require easy and hands-on methods for enterprise modelling that recalibrate models constantly. This article describes a set of tools and techniques for enriching organizational models with semantic information and adjusting them on request. Firstly, we propose an approach for binding the model with relevant documents and experts. Secondly, we define...
Modelling nonverbal communication in robotics is a crucial issue to improve Human Robot interactions (HRI). Among several nonverbal behaviours we focus in this article on unintentional rhythmic entrainment and synchronization which has been proven to be highly important in intuitive and natural Human Human communication. Hence, the rising question is whether or no this phenomenon can be reproduced...
The concept of smart cities has gained relevance over the years. City leaders plan investments with the aim of evolving the city towards a smart city. Several models and frameworks, of which maturity models, provide directions or support such investment decisions. Nevertheless, it is not always clear whether the maturity models developed so far are able to fulfil their proposed objectives. This paper...
This paper considers the problem of state estimations in virus/ worm epidemic dynamic system with time-dependent parameters in arbitrary sparse networks by using continuous-discrete Extended Kalman Filter (so-called Hybrid Extended Kalman Filter [1]). The virus spreading dynamic model has unmeasurable states and with highly nonlinearities which makes the state estimation complicated and not straightforward...
This project used a ECG simulator built upon the Fourier series principle to study the patterns of normal and abnormal (defined as both above and below normal ranges) heart beats and other important ECG parameters for children of differing age groups. Across age groups with normal and abnormal settings, the heart rate is shown as positively correlated with R wave peaks, and inversely correlated with...
In order to personalize the assessment services, the assessment systems need to build suitable student models for heterogeneous student populations. The present study focuses on efficiently modeling students according to their time-varying behavior during web-based self-assessment, enriching the models with a notion of dynamics. The suggested approach forms and revises the student models on-the-fly,...
Motivated by applications in adaptive control, this article compares two recursive estimation algorithms for sparse estimation of linear dynamical (ARX) models. In most practical situations an accurate mathematical model estimation of a real system using the least number of parameters is highly desirable. The expectation of sparsity is imposed through minimization of an objective function that includes...
The cerebellum is a crucial brain structure in enabling precise motor control in animals. Recent advances suggest that the timing of the plasticity rule of Purkinje cells, the main cells of the cerebellum, is matched to behavioral function. Simultaneously, counter-factual predictive control (CFPC), a cerebellar-based control scheme, has shown that the optimal rule for learning feed-forward action...
This work addresses the automatic generation of the resources required for the assisted creation of domain models according to specialized views of their meta-model. The task of a designer who builds models compliant to a complex domain meta-model is eased if the model editor requests the information according to a specific view of the meta-model based on the conceptualization or the specific construction...
Business process variability is an active research area in the field of business process management and deals with variations and commonalities among processes of a given process family. Many theoretical approaches have been suggested in the last years; however, practical implementations are rare and limited in their functionality. In this paper, we propose a new approach for business process variability...
As energy demand increased and production means diversified, conventional approaches of looking into distribution grids need to evolve. The Smart Grid paradigm introduces new possibilities of real-time market sensing and interaction models between producers and consumers. In particular, by understanding the types of consumers and their potential willingness to adapt their energy demand with price...
The ability of slime mould to learn and adapt to periodic changes in its environment inspired scientists to develop behavioral memristor-based circuit models of its memory organization. The computing abilities of slime mould Physarum polycephalum have been used in several applications, including to solve mazes. This work presents a circuit-level bio-inspired maze-solving approach via an electronic...
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