Neural Network Based Algorithm for Dynamic System Optimization

A class of artificial neural networks with a two‐layer feedback topology to solve nonlinear discrete dynamic optimization problems is developed. Generalized recurrent neuron models are introduced. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. A comparative analysis of the computational requirements is made. The analysis shows advantages of this approach as compared to the standard dynamic programming algorithm. The technique has been applied to several important optimization problems, such as shortest path and control optimal problems.     

Estimating the entropy rate of spike trains via Lempel-Ziv complexity

Normalized Lempel-Ziv complexity, which measures the generation rate of new patterns along a digital sequence, is closely related to such important source properties as entropy and compression ratio, but, in contrast to these, it is a property of individual sequences. In this article, we propose to exploit this concept to estimate (or, at least, to bound from below) the entropy of neural discharges (spike trains). The main advantages of this method include fast convergence of the estimator (as supported by numerical simulation) and the fact that there is no need to know the probability law of the process generating the signal. Furthermore, we present numerical and experimental comparisons of the new method against the standard method based on word frequencies, providing evidence that this new approach is an alternative entropy estimator for binned spike trains.     

Teaching Multibody Dynamics at Warsaw University of Technology

The paper concerns the usage of the method of multibody systems (MBS) in teaching students at the Warsaw University of Technology. Research results from the MBS discipline are being used in several ways. Large-scale computer software is being used to illustrate lecture material, some MBS research results are included in lecture topics and independent courses are taught, based directly on MBS research. During senior courses, advanced software is also used as a computational tool as well as an integral part of Virtual Prototyping. The paper presents also several examples of student projects created with MBS.     

Assessment of Numerical Models for Live Load Distribution in a Road Slab Bridge

This paper presents comparison of numerical models used in an analysis of a road bridge deck. The models were adapted for computing the live load distribution coefficients in composite concrete bridge deck. The load distribution method was chosen for assessment of the usability of different numerical model in slab bridge deck analysis. The goal of the study is to determine a simplest but still accurate numerical model to estimate live load effects on composite slab bridge. In the analysis, the well-established grillage approach was adapted for representation of the bridge deck as a basic model as well as more sophisticated three-dimensional models which was supposed to better represent the real behavior of the deck under concentrated wheel loads. The bridge deck was effectively modeled using beam and shell elements. The grillage method compares well with the finite-element method. This finding is allowed to establish simplification in numerical modeling of slab bridge decks for live load effect computations.     

Inverse Analysis of Axisymmetrical Compression of HSLA Steel

The objective of the present work is to further explore the problem of selection of the flow stress function which will give the best agreement with experiments for a wide range of the Zener‐Hollomon parameter. Analysis of various flow stress functions was performed, with particular emphasis on the Zerilli‐Armstrong model. Inverse analysis was successfully applied to identify the flow stress model for microalloyed steels deformed in ferrite, two‐phase and austenite regions. Inverse method is applied to interpret the results of the axisymmetrical compression tests performed for HSLA steel samples on a Gleeble 3800 and Split Hopkinson Pressure Bar. Sensitivity analysis is performed based on local and global methods. The objective of the sensitivity analysis in the present study is the evaluation to what extent the selected coefficients in the rheological model influence the result of simulations. In the considered tests this result is represented by two dependent variables, the load and the shape of the sample (barrelling). It is confirmed that the Zerilli‐Armstrong equations should be applied at very high strain rates. Physical meaning is an advantage of this model. Difficulties with identification are the main disadvantage.     

A certain class of starlike functions

This paper presents a new class of functions analytic in the open unit disc, and closely related to the class of starlike functions. Besides being an introduction to this field, it provides an interesting connections defined class with well known classes. The paper deals with several ideas and techniques used in geometric function theory. The order of starlikeness in the class of convex functions of negative order is also considered here.     

Integrated Data Management for a Fleet of Search‐and‐rescue Robots

Search‐and‐rescue operations have recently been confronted with the introduction of robotic tools that assist the human search‐and‐rescue workers in their dangerous but life‐saving job of searching for human survivors after major catastrophes. However, the world of search and rescue is highly reliant on strict procedures for the transfer of messages, alarms, data, and command and control over the deployed assets. The introduction of robotic tools into this world causes an important structural change in this procedural toolchain. Moreover, the introduction of search‐and‐rescue robots acting as data gatherers could potentially lead to an information overload toward the human search‐and‐rescue workers, if the data acquired by these robotic tools are not managed in an intelligent way. With that in mind, we present in this paper an integrated data combination and data management architecture that is able to accommodate real‐time data gathered by a fleet of robotic vehicles on a crisis site, and we present and publish these data in a way that is easy to understand by end‐users. In the scope of this paper, a fleet of unmanned ground and aerial search‐and‐rescue vehicles is considered, developed within the scope of the European ICARUS project. As a first step toward the integrated data‐management methodology, the different robotic systems require an interoperable framework in order to pass data from one to another and toward the unified command and control station. As a second step, a data fusion methodology will be presented, combining the data acquired by the different heterogenic robotic systems. The computation needed for this process is done in a novel mobile data center and then (as a third step) published in a software as a service (SaaS) model. The SaaS model helps in providing access to robotic data over ubiquitous Ethernet connections. As a final step, we show how the presented data‐management architecture allows for reusing recorded exercises with real robots and rescue teams for training purposes and teaching search‐and‐rescue personnel how to handle the different robotic tools. The system was validated in two experiments. First, in the controlled environment of a military testing base, a fleet of unmanned ground and aerial vehicles was deployed in an earthquake‐response scenario. The data gathered by the different interoperable robotic systems were combined by a novel mobile data center and presented to the end‐user public. Second, an unmanned aerial system was deployed on an actual mission with an international relief team to help with the relief operations after major flooding in Bosnia in the spring of 2014. Due to the nature of the event (floods), no ground vehicles were deployed here, but all data acquired by the aerial system (mainly three‐dimensional maps) were stored in the ICARUS data center, where they were securely published for authorized personnel all over the world. This mission (which is, to our knowledge, the first recorded deployment of an unmanned aerial system by an official governmental international search‐and‐rescue team in another country) proved also the concept of the procedural integration of the ICARUS data management system into the existing procedural toolchain of the search and rescue workers, and this in an international context (deployment from Belgium to Bosnia). The feedback received from the search‐and‐rescue personnel on both validation exercises was highly positive, proving that the ICARUS data management system can efficiently increase the situational awareness of the search‐and‐rescue personnel.