Fully symbolic-based technique for solving complex state-space control systems

Despite the superiority of symbolic approaches over the purely numerical approaches in many aspects, it does not receive the proper attention due to its significant complexity, high resources requirement and long drawn time which even grows significantly with the increase of model dimensions. However, its merits deserve every attempt to overcome the difficulties being faced. In this paper, a fully generic symbolic-based technique is proposed to deal with complex state space control problems. In this technique, depending on the model dimension if exceeds a predefined limit, the state space is solved using the partitioned matrices theory and block wise inversion formula. Experimental results demonstrate that the proposed technique overcomes all the previously mentioned barriers and gives the same results when compared to numerical methods (Simulink). Moreover, it can be used to gain useful information about the system itself, provides an indication of which parameters are more important and reveals the sensitivity of system model to single parameter variations.

Cross-Border Risks as an Impact Factor for International Fintech Business Models

Research background: Cross-border activities for FinTech companies in several markets bring them completely new opportunities and drive the appetite for new deals, but the complexity of doing business internationally is often underestimated: many risks, which have an influence of business models, can be determined. The emphasis of this research is on those risks that can be brought into particularly correlation with the cross-border activities of a FinTech company and at the same time influence the whole business activity of it. Purpose of the article: The aim of this research is to find out what kind of risks corresponds to so called cross-border risk-group and is the most common for internationally designed FinTech business models. Additionally, to determine those business model areas, which are influenced by cross-border risks the most and must be created with focus on avoiding, mitigating or sharing these risks. Methods: To achieve the goal the authors interviewed representatives of different FinTech companies. In these interviews, experts were asked to describe the most significant risks and to assess the importance of them for each business model dimension by using the Likert’s scale as well as to explain the dependencies and the consequences of their influence on different business model areas. Findings & Value added: The result of this research forms the basis for conclusions about the most significant cross-border risks and their impact on dimensions of a business model as well as makes recommendations possible for those FinTech-enthusiasts who are going to model their FinTech business internationally.

The triptych of conceptual modeling

We understand this paper as a contribution to the “anatomy” of conceptual models. We propose a signature of conceptual models for their characterization, which allows a clear distinction from other types of models. The motivation for this work arose from the observation that conceptual models are widely discussed in science and practice, especially in computer science, but that their potential is far from being exploited. We combine our proposal of a more transparent explanation of the nature of conceptual models with an approach that classifies conceptual models as a link between the dimension of linguistic terms and the encyclopedic dimension of notions. As a paradigm we use the triptych, whose central tableau represents the model dimension. The effectiveness of this explanatory approach is illustrated by a number of examples. We derive a number of open research questions that should be answered to complete the anatomy of conceptual models.

Complex Fastener Model for Simulation of Airframe Assembly Process

The complex model of fastener for the global modeling of aircraft assembly with regard to compliance and contact interaction of parts is introduced in the paper. The presented complex fastener model incorporates such effects as the stiffness of fastening elements; the loosening of fasteners and also the failure of fasteners (if the load exceeds the maximal value that fastener can hold). This model can be implemented for all types of fastening elements in variation simulation and assembly optimization analysis. It provides more realistic simulation results at expense of higher model dimension. The fastener is modeled as having an additional stretching stiffness. The option of fastener loosening is included by implementation of additional contact node in each fastening element. This option allows taking into account the pre-tension in fasteners and also enables the modeling of installation and removal of fasteners without change of stiffness matrix.

Bayesian cumulative shrinkage for infinite factorizations

Summary The dimension of the parameter space is typically unknown in a variety of models that rely on factorizations. For example, in factor analysis the number of latent factors is not known and has to be inferred from the data. Although classical shrinkage priors are useful in such contexts, increasing shrinkage priors can provide a more effective approach that progressively penalizes expansions with growing complexity. In this article we propose a novel increasing shrinkage prior, called the cumulative shrinkage process, for the parameters that control the dimension in overcomplete formulations. Our construction has broad applicability and is based on an interpretable sequence of spike-and-slab distributions which assign increasing mass to the spike as the model complexity grows. Using factor analysis as an illustrative example, we show that this formulation has theoretical and practical advantages relative to current competitors, including an improved ability to recover the model dimension. An adaptive Markov chain Monte Carlo algorithm is proposed, and the performance gains are outlined in simulations and in an application to personality data.

Molecular dynamics simulation on the morphology of 1,1-diamino-2,2-dinitroethylene (FOX-7) affected by dimethyl sulfoxide (DMSO) and temperature

The attachment energy (AE) model is adopted to research the influence of dimethyl sulfoxide (DMSO) and temperature on the crystal morphology of 1,1-diamino-2,2-dinitroethylene (FOX-7). FOX-7 crystal habits in DMSO at different temperatures simulated by the AE model have apparently changed compared with the vacuum morphology, indicating that the solvent and temperature can affect FOX-7 morphology. Moreover, the influence of model dimension on the attachment energy has been studied, and a reasonable model size is obtained based on the model dimension study results. Besides, the radial distribution function analysis shows that the solvent molecules adsorb on the FOX-7 surfaces mainly via the solvent–crystal interface interactions of van der Waals forces (vdW) and Coulomb interactions. The analysis of diffusion coefficient of DMSO molecules on the crystal growth surfaces shows that the growth habit is also influenced by the diffusion capacity of DMSO molecules. These simulation results of this study can provide some guidance for the crystallization process of FOX-7.

CHARACTERISTIC OF MUS-01 WING’S STRUCTURE TESTING MODEL

The characteristic model of MUS-01 wing structure testing has been performed. Planned, this model will be used as an unmanned wing of the LSU-03NG. The test model is made of composite type e-glass. At the time of testing the structure test model is loaded according to MTOW weight. This research method also involves the unmanned aircraft mission, especially on the model test structure, model dimension, and direct experiment in the form of loading on the test model. The result of characterization of the test model during test, showed that the indicated test model has the characteristics as a test model that is unable to accept the unmanned operational load of LSU-03NG series aircraft. So it can not be used as a consideration for the structure of the unmanned aircraft.