An investigation on the heat dissipation in Zn-substituted magnetite nanoparticles, coated with citric acid and pluronic F127 for hyperthermia application. - In: Physica, ISSN 1873-2135, Bd. 625 (2022), 413468
Zinc substituted spinel ferrite nanoparticles are appropriate for magnetic fluid hyperthermia. Stable suspensions of Zn2+ substituted magnetite (ZnxFe3-xO4, 0 ≤ x ≤ 0.20) nanoparticles in aqueous solutions (pH 5.5) were synthesized by means of co-precipitation approach, using citric acid (CA) and pluronic F127 as surfactants for hyperthermia application. The specimens were characterized by different methods. XRD patterns of the precipitates confirmed that all specimens have single phase cubic spinel structures and their lattice parameters increased as Zn2+ content increased. Mean crystallite sizes of the uncoated specimens were determined to be around 28 nm, using Scherrer's formula. By increasing the Zn2+ content, Curie temperature of the uncoated specimens reduced from 545 to 410 ˚C monotonically caused by reduction in super-exchange interactions. Room temperature saturation magnetizations of the uncoated specimens increased to 98.8 emu/g for x = 0.10 initially, and then decreased to 79.6 emu/g for x = 0.20. It is attributed to the replacement of paramagnetic Fe3+ ions by diamagnetic Zn2+ ones and spin canting. FTIR spectra reconfirmed formation of pure magnetite and Zn2+ substituted magnetite nanoparticles and also proved the presence of ligands on the surface of the nanoparticles. TEM investigation showed that mean particle sizes of the coated nanoparticles were in the range of 35-40 nm. The obtained ferrofluids showed a good stability in aqueous medium (pH 5.5) and according to the room temperature magnetic measurements, heating efficiency is scarcely released due to relaxation processes. Maximum obtained specific loss power (SLP) was 539 W/g and that of intrinsic loss power (ILP) was 7.26 nHm2/kg for x = 0.05 (f = 290 kHz, H = 16 kA/m) with a nanoparticle concentration as low as 1.2 mg/ml, which is a promising candidate for magnetic hyperthermia applications potentially.
Deep security analysis of program code : a systematic literature review. - In: Empirical software engineering, ISSN 1573-7616, Bd. 27 (2022), 1, 2, S. 1-39
Due to the continuous digitalization of our society, distributed and web-based applications become omnipresent and making them more secure gains paramount relevance. Deep learning (DL) and its representation learning approach are increasingly been proposed for program code analysis potentially providing a powerful means in making software systems less vulnerable. This systematic literature review (SLR) is aiming for a thorough analysis and comparison of 32 primary studies on DL-based vulnerability analysis of program code. We found a rich variety of proposed analysis approaches, code embeddings and network topologies. We discuss these techniques and alternatives in detail. By compiling commonalities and differences in the approaches, we identify the current state of research in this area and discuss future directions. We also provide an overview of publicly available datasets in order to foster a stronger benchmarking of approaches. This SLR provides an overview and starting point for researchers interested in deep vulnerability analysis on program code.
Large animal lightning accidents - determining possible injury mechanisms by simulations :
Großtier-Blitzunfälle - Ermittlung möglicher Schädigungsmechanismen durch Simulationen. - In: 14. VDE Blitzschutztagung, (2021), S. 136-142
Modulation-function-based finite-horizon sensor fault detection for salient-pole PMSM using parity-space residuals. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 54 (2021), 7, S. 61-66
An online model-based fault detection and isolation method for salient-pole permanent magnet synchronous motors over a finite horizon is proposed. The proposed approach combines parity-space-based residual generation and modulation-function-based filtering. Given the polynomial model equations, the unknown variables (i.e. the states, unmeasured inputs) are eliminated resulting in analytic redundancy relations used for residual generation. Furthermore, in order to avoid needing the derivatives of measured signals required by such analytic redundancy relations, a modulation-function-based evaluation is proposed. This results in a finite-horizon filtered version of the original residual. The fault detection and isolation method is demonstrated using simulation of various fault scenarios for a speed controlled salient motor showing the effectiveness of the presented approach.
Modulating function based fault diagnosis using the parity space method. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 54 (2021), 7, S. 268-273
A model-based method for the detection and estimation of faults in dynamic systems is proposed. The method is based on the combination of the parity space approach and the modulating function framework for estimation. The parity space method is employed as an efficient geometric procedure determining null subspaces for annihilating unknown terms and formulating residuals. With the modulating functions technique the dynamic relation from output differentiation is reformulated as an algebraic expression. This substantially reduces the noise sensitivity of the output derivatives required. The design allows for the robust fault detection and isolation also for some nonlinear systems. The robustness of the approach is demonstrated on a nonlinear model of a four-tank process.
Long-term dependency slow feature analysis for dynamic process monitoring. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 54 (2021), 3, S. 421-426
Industrial processes are large scale, highly complex systems. The complex flow of mass and energy, as well as the compensation effects of closed-loop control systems, cause significance cross-correlation and autocorrelation between process variables. To operate the process systems stably and efficiently, it is crucial to uncover the inherent characteristics of both variance structure and dynamic relationship. Long-term dependency slow feature analysis (LTSFA) is proposed in this paper to overcome the Markov assumption of the original slow feature analysis to understand the long-term dynamics of processes, based on which a monitoring procedure is designed. A simulation example and the Tennessee Eastman process benchmark are studied to show the performance of LTSFA. The proposed method can better extract the system dynamics and monitor the process variations using fewer slow features.
A novel attitude representation in view of spacecraft attitude reconstruction using temperature data. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 54 (2021), 14, S. 500-505
There are various different attitude representations that describe the orientation of a rigid body in space and allow the transformation between different coordinate systems. Among others, they differ in number of variables, uniqueness of the representation and their continuity. However, in spite of some of them being based on angles, none of them constitutes a simple representation of an angle between two arbitrary vectors. We tackle this issue by proposing a novel attitude representation that directly incorporates the desired angle. The usefulness of this representation is demonstrated in the attitude reconstruction from temperature data, which then leads to an order reduction of a non-linear system.
Dynamic extension for adaptive backstepping control of uncertain pure-feedback systems. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 54 (2021), 14, S. 307-312
An adaptive backstepping algorithm is developed for a class of uncertain systems in pure-feedback form. The control is based on a dynamic state feedback that allows to compensate for parametric uncertainties which enter linearly into the system. As possible in the nominal case, a dynamic extension of just order one is required, in addition to the dynamics of the identifiers for the adaptation. The regularity of the control law only requires standard assumptions.
Energy shaping and partial feedback linearization of mechanical systems with kinematic constraints. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 54 (2021), 19, S. 243-248
Traditionally, the energy shaping for mechanical systems requires the elimination of holonomic and nonholonomic constraints. In recent years, it was argued that such elimination might be unnecessary, leading to a possible simplification of the matching conditions in energy shaping. On the other hand, the partial feedback linearization (PFL) approach has been widely applied to unconstrained mechanical systems, but there is no general result for the constrained case. In this regard, this paper formalizes the PFL for mechanical systems with kinematic constraints and extends the energy shaping of such systems by including systems with singular inertia matrix and non-workless constraint forces, which can arise from the coordinate selection and PFL. We validated the proposed methodology on a 5-DoF portal crane via simulation.
Direct current stimulation of the entire visual pathway does not affect the full field electroretinogram. - In: Brain stimulation, ISSN 1876-4754, Bd. 14 (2021), 6, S. 1674-1675