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A constructive method for the design of nonlinear observers is discussed. To formulate conditions for the construction of the observer gains, stability results for nonlinear singularly perturbed systems are utilised. The nonlinear observer is designed directly in the given coordinates, where the error dynamics between the plant and the observer becomes singularly perturbed by a high-gain part of the observer injection, and the information of the slow manifold is exploited to construct the observer gains of the reduced-order dynamics. This is in contrast to typical high-gain observer approaches, where the observer gains are chosen such that the nonlinearities are dominated by a linear system. It will be demonstrated that the considered approach is particularly suited for self-sensing electromechanical systems. Two variants of the proposed observer design are illustrated for a nonlinear electromagnetic actuator, where the mechanical quantities, i.e. the position and the velocity, are not measured
The introduction of multiple-level cell (MLC) and triple-level cell (TLC) technologies reduced the reliability of flash memories significantly compared with single-level cell flash. With MLC and TLC flash cells, the error probability varies for the different states. Hence, asymmetric models are required to characterize the flash channel, e.g., the binary asymmetric channel (BAC). This contribution presents a combined channel and source coding approach improving the reliability of MLC and TLC flash memories. With flash memories data compression has to be performed on block level considering short-data blocks. We present a coding scheme suitable for blocks of 1 kB of data. The objective of the data compression algorithm is to reduce the amount of user data such that the redundancy of the error correction coding can be increased in order to improve the reliability of the data storage system. Moreover, data compression can be utilized to exploit the asymmetry of the channel to reduce the error probability. With redundant data, the proposed combined coding scheme results in a significant improvement of the program/erase cycling endurance and the data retention time of flash memories.
Input–Output modellers are often faced with the task of estimating missing Use tables at basic prices and also valuation matrices of the individual countries. This paper examines a selection of estimation methods applied to the European context where the analysts are not in possession of superior data. The estimation methods are restricted to the use of automated methods that would require more than just the row and column sums of the tables (as in projections) but less than a combination of various conflicting information (as in compilation). The results are assessed against the official Supply, Use and Input–Output tables of Belgium, Germany, Italy, Netherlands, Finland, Austria and Slovakia by using matrix difference metrics. The main conclusion is that using the structures of previous years usually performs better than any other approach.
Objective: This paper presents an algorithm for non-invasive sleep stage identification using respiratory, heart rate and movement signals. The algorithm is part of a system suitable for long-term monitoring in a home environment, which should support experts analysing sleep. Approach: As there is a strong correlation between bio-vital signals and sleep stages, multinomial logistic regression was chosen for categorical distribution of sleep stages. Several derived parameters of three signals (respiratory, heart rate and movement) are input for the proposed method. Sleep recordings of five subjects were used for the training of a machine learning model and 30 overnight recordings collected from 30 individuals with about 27 000 epochs of 30 s intervals each were evaluated. Main results: The achieved rate of accuracy is 72% for Wake, NREM, REM (with Cohen's kappa value 0.67) and 58% for Wake, Light (N1 and N2), Deep (N3) and REM stages (Cohen's kappa is 0.50). Our approach has confirmed the potential of this method and disclosed several ways for its improvement. Significance: The results indicate that respiratory, heart rate and movement signals can be used for sleep studies with a reasonable level of accuracy. These inputs can be obtained in a non-invasive way applying it in a home environment. The proposed system introduces a convenient approach for a long-term monitoring system which could support sleep laboratories. The algorithm which was developed allows for an easy adjustment of input parameters that depend on available signals and for this reason could also be used with various hardware systems.
Business units are increasingly able to fuel the transformation that digitalization demands of organizations. Thereby, they can implement Shadow IT (SIT) without involving a central IT department to create flexible and innovative solutions. Self-reinforcing effects lead to an intertwinement of SIT with the organization. As a result, high complexities, redundancies, and sometimes even lock-ins occur. IT Integration suggests itself to meet these challenges. However, it can also eliminate the benefits that SIT presents. To help organizations in this area of conflict, we are conducting a literature review including a systematic search and an analysis from a systemic viewpoint using path dependency and switching costs. Our resulting conceptual framework for SIT integration drawbacks classifies the drawbacks into three dimensions. The first dimension consists of switching costs that account for the financial, procedural, and emotional drawbacks and the drawbacks from a loss of SIT benefits. The second dimension includes organizational, technical, and level-spanning criteria. The third dimension classifies the drawbacks into the global level, the local level, and the interaction between them. We contribute to the scientific discussion by introducing a systemic viewpoint to the research on shadow IT. Practitioners can use the presented criteria to collect evidence to reach an IT integration decision.
E-mobility in Tourism
(2018)
This article examines chances for and obstacles to e-mobility in tourism at the cross-border region of Lake Constance, Germany. Using secondary internet research, a database of key e-mobility supply factors was generated and visualized utilizing a geographical information system. The results show that fragmentation in infrastructure and information due to the cross-border situation of the four-country region is the main obstacle for e-mobility in tourism in the Lake Constance region. Cooperation and coordination of the supply side of e-mobility in the Lake Constance region turned out to be weak. To improve the chances of e-mobility in cross-border tourism a more client-oriented approach regarding information, accessibility, and conditions of use is necessary.
Due to their structure of crossed yarns embedded in coating, woven fabric membranes are characterised by a highly nonlinear stress-strain behaviour. In order to determine an accurate structural response of membrane structures, a suitable description of the material behaviour is required. Typical phenomenological material models like linear-elastic orthotropic models only allow a limited determination of the real material behaviour. A more accurate approach becomes evident by focusing on the meso-scale, which reveals an inhomogeneous however periodic structure of woven fabrics. The present work focuses on an established meso-scale model. The novelty of this work is an enhancement of this model with regard to the coating stiffness. By performing an inverse process of parameter identification using a state-of-the-art Levenberg-Marquardt algorithm, a close fit w.r.t. measured data from a common biaxial test is shown and compared to results applying established models. Subsequently, the enhanced meso-scale model is processed into a multi-scale model and is implemented as a material law into a finite element program. Within finite element analyses of an exemplary full scale membrane structure by using the implemented material model as well as by using established material models, the results are compared and discussed.
Further applications of the Cauchon algorithm to rank determination and bidiagonal factorization
(2018)
For a class of matrices connected with Cauchon diagrams, Cauchon matrices, and the Cauchon algorithm, a method for determining the rank, and for checking a set of consecutive row (or column) vectors for linear independence is presented. Cauchon diagrams are also linked to the elementary bidiagonal factorization of a matrix and to certain types of rank conditions associated with submatrices called descending rank conditions.
This letter proposes two contributions to improve the performance of transmission with generalized multistream spatial modulation (SM). In particular, a modified suboptimal detection algorithm based on the Gaussian approximation method is proposed. The proposed modifications reduce the complexity of the Gaussian approximation method and improve the performance for high signal-to-noise ratios. Furthermore, this letter introduces signal constellations based on Hurwitz integers, i.e., a 4-D lattice. Simulation results demonstrate that these signal constellations are beneficial for generalized SM with two active antennas.