As labor shortage increases in the health sector, the demand for assistive robotics grows. However, the needed test data to develop those robots is scarce, especially for the application of active 3D object detection,...
As labor shortage increases in the health sector, the demand for assistive robotics grows. However, the needed test data to develop those robots is scarce, especially for the application of active 3D object detection, where no real data exists at all. This short paper counters this by introducing such an annotated dataset of real environments. The captured environments represent areas which are already in use in the field of robotic health care research. We further provide ground truth data within one room, for assessing SLAM algorithms running directly on a health care robot.
A DC-DC converter that can handle a lot of different power changes. The experts in this study discovered that adding a fuzzy logic circuit helped the system work better. It makes a big difference in how well and consi...
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ISBN:
(数字)9798350365092
ISBN:
(纸本)9798350365108
A DC-DC converter that can handle a lot of different power changes. The experts in this study discovered that adding a fuzzy logic circuit helped the system work better. It makes a big difference in how well and consistently the PV system works that the FLC controls the output power of the converter. Because the FLC works with Microsoft Excel, more people can use this powerful tool for less money and with less trouble. The FLC cuts down on “overshoot,” “settling time,” and steady-state error, as shown in simulations that test how well the controller works. This study may have made it easier for people to start making “fuzzy logic controllers” and make them better. This will have a big effect on how far we get in making energy systems that work better and are more stable. Further investigation could be conducted to determine whether or not these concepts are feasible and how they would enhance the FLC in different types. These DC-DC converters have closed loops in their circuitry.
This paper presents control system design, implementation, and experimental validation of a single-stage 400 W, 200 kHz solar photovoltaic (PV) microinverter using hardware-in-the-loop (HIL) and hardware testing. The ...
This paper presents control system design, implementation, and experimental validation of a single-stage 400 W, 200 kHz solar photovoltaic (PV) microinverter using hardware-in-the-loop (HIL) and hardware testing. The selected circuit topology is based on a Gallium Nitride (GaN) direct-matrix based dual active bridge (DAB) converter with a low voltage active power decoupler (APD) circuit. Control performance is verified, smart-grid compatibility is tested, and circuit operation is confirmed. Controller HIL (CHIL) is shown to aid in a complex power electronics system design by 1) enabling detailed control development prior to hardware implementation, 2) expanding the use of automated testing, and 3) increasing confidence in control performance prior to prototype testing. Altogether, these factors make HIL a valuable tool in complex power electronic designs.
Although consortium blockchain has an identification mechanism, the captured internal clients are potentially threatening internal blockchain nodes. Internal Distributed Denial-of-Service (DDoS) attacks threaten the s...
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Navigating unmanned aerial vehicles in environments where GPS signals are unavailable poses a compelling and intricate challenge. This challenge is further heightened when dealing with Nano Aerial Vehicles (NAVs) due ...
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We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area. Adversarial attacks such as Sybil attacks can cause safety violations resulting in colli...
We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area. Adversarial attacks such as Sybil attacks can cause safety violations resulting in collisions and traffic jams. In addition, uncooperative (but not necessarily adversarial) CAVs can also induce similar adversarial effects on the traffic network. We propose a decentralized resilient control and coordination scheme that mitigates the effects of adversarial attacks and uncooperative CAVs by utilizing a trust framework. Our trust-aware scheme can guarantee safe collision free coordination and mitigate traffic jams. Simulation results validate the theoretical guarantee of our proposed scheme, and demonstrate that it can effectively mitigate adversarial effects across different traffic scenarios.
Electric vehicles are attracting great attention with their 48V electrification system. In this paper, the design of a two-stage 400V/48V automotive DC-DC converter based on PCB magnetics is presented. A two-phase buc...
Electric vehicles are attracting great attention with their 48V electrification system. In this paper, the design of a two-stage 400V/48V automotive DC-DC converter based on PCB magnetics is presented. A two-phase buck converter with a coupled inductor is used as the first stage to perform voltage regulation and guarantee good load transient performance. The second stage is an LLC resonant converter with a matrix transformer which provides isolation and behaves as a step-down DC transformer (DCX). The switching frequency is pushed to 500kHz to help reduce converter size and weight. By pushing the operation to high frequencies, the windings of the transformer of the LLC converter and those of the coupled inductor of the buck converter are integrated and built into the PCB. This not only improves the power density, but also minimizes the use of labor-intensive components/processes to enable truly automated manufacture. The thermal management for such converters is especially challenging due to the harsh environments it is situated in. This is accomplished using a custom-engraved aluminum baseplate to provide low thermal resistivity and increase converter reliability. The converter can achieve an efficiency of 97% and a power density of 5 kW/L.
The standard flickermeter (voltage flickermeter) algorithm commonly used for the evaluation of flicker severity in current electromagnetic compatibility standards originates from the 1980 s. It was developed to mimic ...
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Wireless federated learning (FL) is a collaborative machine learning (ML) framework in which wireless client-devices independently train their ML models and send the locally trained models to the FL server for aggrega...
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Wireless federated learning (FL) is a collaborative machine learning (ML) framework in which wireless client-devices independently train their ML models and send the locally trained models to the FL server for aggregation. In this paper, we consider the coexistence of privacy-sensitive client-devices and privacy-insensitive yet computing-resource constrained client-devices, and propose an FL framework with a hybrid centralized training and local training. Specifically, the privacy-sensitive client-devices perform local ML model training and send their local models to the FL server. Each privacy-insensitive client-device can have two options, i.e., (i) conducting a local training and then sending its local model to the FL server, and (ii) directly sending its local data to the FL server for the centralized training. The FL server, after collecting the data from the privacy-insensitive client-devices (which choose to upload the local data), conducts a centralized training with the received datasets. The global model is then generated by aggregating (i) the local models uploaded by the client-devices and (ii) the model trained by the FL server centrally. Focusing on this hybrid FL framework, we firstly analyze its convergence feature with respect to the client-devices' selections of local training or centralized training. We then formulate a joint optimization of client-devices' selections of the local training or centralized training, the FL training configuration (i.e., the number of the local iterations and the number of the global iterations), and the bandwidth allocations to the client-devices, with the objective of minimizing the overall latency for reaching the FL convergence. Despite the non-convexity of the joint optimization problem, we identify its layered structure and propose an efficient algorithm to solve it. Numerical results demonstrate the advantage of our proposed FL framework with the hybrid local and centralized training as well as our proposed alg
Humans employ a fusion of pressure and temperature signals to perceive tactile stimuli. While replicating the complexity of human tactile sensing poses challenges, advancements in artificial tactile sensing skins play...
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