Effective exploitation of the application-specific parallel patterns and computation operations through their direct implementation in hardware is the base for construction of high-quality application-specific (re-) c...
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This research presents a novel electromagnetic-based sensor for inline measurement of unmilled rice paddy moisture content in the rice mill factory. The proposed sensor has been designed based on the modified planar d...
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This paper describes the determination of the fault location in the power system. This problem is solved in two steps: by determining the line on which the fault occurred using the classification algorithm of the deci...
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ISBN:
(数字)9781728197593
ISBN:
(纸本)9781728197609
This paper describes the determination of the fault location in the power system. This problem is solved in two steps: by determining the line on which the fault occurred using the classification algorithm of the decision tree and determining the fault location on the line by linear regression. In the first step, the decision tree algorithm is used to classify the short circuit and to determine the faulted line based on the information about the residual voltages (voltage dips) on the buses due to the occurrence of a short circuit. In the second step, linear regression is used to find the fault location on the faulted line. The algorithm is tested using the 39-bus IEEE test system.
A 1 st order current-mode continuous-time delta-sigma modulator architecture is presented for in-sensor-site readout in electrochemical sensor arrays. The electrode-to-electrolyte interface is used as integration cap...
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A 1 st order current-mode continuous-time delta-sigma modulator architecture is presented for in-sensor-site readout in electrochemical sensor arrays. The electrode-to-electrolyte interface is used as integration capacitance, followed by a Current-Controlled Oscillator-based quantizer. A relaxation oscillator is optimized to meet the requirements of Cyclic Voltammetry. Two circuit realizations are presented and investigated by means of simulation. Both modulators achieve 30 dB/decade noise shaping and reach an SNDR of 67 dB and 62 dB, respectively, at a signal bandwidth of 10 kHz. The reported modulators are highly efficient regarding area and power, and immune to noise and supply voltage variations.
This paper investigates the differences in dipole current and input impedance due to different source models in the framework of boundary element formalism. The half-wavelength and full-wavelength dipole antennas are ...
This paper investigates the differences in dipole current and input impedance due to different source models in the framework of boundary element formalism. The half-wavelength and full-wavelength dipole antennas are placed in free space and above a lossy medium. Antenna current and input impedance are obtained by numerically solving the Pocklington’s integro-differential equation via Galerkin-Bubnov Indirect Boundary Element Method (GB-IBEM). Two different feeding structures are used as excitation sources, a delta gap source model usually used under GB-IBEM formalism and a magnetic frill source model. Different segment numbers are also used. The results indicate that the current magnitude in case of half-wavelength dipole antenna varies to a relatively great extent depending on the applied voltage generator model. Input impedance does not vary due to different source models, however, its value changes greatly with segment number.
Decision Diagrams (DDs) are a data structure for the representation and manipulation of discrete logic functions often applied in VLSI CAD. Common DDs to represent Boolean functions are Binary Decision Diagrams (BDDs)...
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Decision Diagrams (DDs) are a data structure for the representation and manipulation of discrete logic functions often applied in VLSI CAD. Common DDs to represent Boolean functions are Binary Decision Diagrams (BDDs). Multiple-valued logic functions can be represented by multiple-valued Decision Diagrams (MDDs). The effiency of a DD representation strongly depends on the variable ordering; the size may vary from linear to exponential. Finding a good ordering is an NP-hard problem that has received considerable attention resulting in many minimization methods. Sifting is the most popular heuristic for dynamic DD minimization. In this paper we give lower bounds for sifting of MDDs. Based on them, both lower bound sifting for MDD minimization and lower bound group sifting for BDD minimization are proposed. By the computation of good lower bounds large parts of the search space can be pruned resulting in very fast computations. This is demonstrated by experimental results.
High reliability and high availability are essential aspects for all critical elements used in automotive applications. This is particularly true for control and steering systems. In this regard, numerous steer by wir...
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High reliability and high availability are essential aspects for all critical elements used in automotive applications. This is particularly true for control and steering systems. In this regard, numerous steer by wire (x-by-wire) concepts were developed over the years. Most of them considered only standard single microcontroller system architectures with a low degree of reliability according to international reliability and safety standards. This paper presents a novel concept for a degradable safety controller for steer-by-wire systems. Based on a safety-related 1004-architecture, the presented concept offers higher safety, reliability and availability.
Mobile robots face a significant challenge when navigating in dynamic environments such as human crowds. Existing research works typically employ separate data or simulators for dynamic object detection and navigation...
Mobile robots face a significant challenge when navigating in dynamic environments such as human crowds. Existing research works typically employ separate data or simulators for dynamic object detection and navigation tasks. This paper combines the photo-realistic simulator Habitat with embedded dynamic objects to create a playground for optimizing vision-based navigation algorithms. To validate our system, we implement and train three approaches - zero masks, image memory inpainting, and semantic map filter - using semantically segmented information. We then implement and evaluate an adapted reinforcement-learning-based SLAM algorithm using the validation Gibson dataset. The results indicate that moderate localization bias occurs when the environment is small and the navigation process is short. However, the error will accumulate over time. Additionally, a dynamic environment leads to less accurate localization. All three approaches can reduce the localization error, while the semantic map filter approach shows the best overall performance.
Assistance robots have gained widespread attention in various industries such as logistics and human assistance. The tasks of guiding or following a human in a crowded environment such as airports or train stations to...
Assistance robots have gained widespread attention in various industries such as logistics and human assistance. The tasks of guiding or following a human in a crowded environment such as airports or train stations to carry weight or goods is still an open problem. In these use cases, the robot is not only required to intelligently interact with humans, but also to navigate safely among crowds. Thus, especially highly dynamic environments pose a grand challenge due to the volatile behavior patterns and unpredictable movements of humans. In this paper, we propose a Deep-Reinforcement-Learning-based agent for human-guiding and -following tasks in crowded environments. Therefore, we incorporate semantic information to provide the agent with high-level information like the social states of humans, safety models, and class types. We evaluate our proposed approach against a benchmark approach without semantic information and demonstrated enhanced navigational safety and robustness. Moreover, we demonstrate that the agent could learn to adapt its behavior to humans, which improves the human-robot interaction significantly.
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