222 research outputs found
Game among Interdependent Networks: The Impact of Rationality on System Robustness
Many real-world systems are composed of interdependent networks that rely on
one another. Such networks are typically designed and operated by different
entities, who aim at maximizing their own payoffs. There exists a game among
these entities when designing their own networks. In this paper, we study the
game investigating how the rational behaviors of entities impact the system
robustness. We first introduce a mathematical model to quantify the interacting
payoffs among varying entities. Then we study the Nash equilibrium of the game
and compare it with the optimal social welfare. We reveal that the cooperation
among different entities can be reached to maximize the social welfare in
continuous game only when the average degree of each network is constant.
Therefore, the huge gap between Nash equilibrium and optimal social welfare
generally exists. The rationality of entities makes the system inherently
deficient and even renders it extremely vulnerable in some cases. We analyze
our model for two concrete systems with continuous strategy space and discrete
strategy space, respectively. Furthermore, we uncover some factors (such as
weakening coupled strength of interdependent networks, designing suitable
topology dependency of the system) that help reduce the gap and the system
vulnerability
Real-Time Vehicle Detection from Short-range Aerial Image with Compressed MobileNet
Vehicle detection from short-range aerial image faces challenges including vehicle blocking, irrelevant object interference, motion blurring, color variation etc., leading to the difficulty to achieve high detection accuracy and real-time detection speed. In this paper, benefiting from the recent development in MobileNet family network engineering, we propose a compressed MobileNet which is not only internally resistant to the above listed challenges but also gains the best detection accuracy/speed tradeoff when comparing with the original MobileNet. In a nutshell, we reduce the bottleneck architecture number during the feature map downsampling stage but add more bottlenecks during the feature map plateau stage, neither extra FLOPs nor parameters are thus involved but reduced inference time and better accuracy are expected. We conduct experiment on our collected 5-k short-range aerial images, containing six vehicle categories: truck, car, bus, bicycle, motorcycle, crowded bicycles and crowded motorcycles. Our proposed compressed MobileNet achieves 110 FPS (GPU), 31 FPS (CPU) and 15 FPS (mobile phone), 1.2 times faster and 2% more accurate (mAP) than the original MobileNet
Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage
This paper presents a doubly fed induction generator (DFIG) wind power system with hydrogen energy storage, with a focus on its virtual inertia adaptive control. Conventionally, a synchronous generator has a large inertia from its rotating rotor, and thus its kinetic energy can be used to damp out fluctuations from the grid. However, DFIGs do not provide such a mechanism as their rotor is disconnected with the power grid, owing to the use of back-to-back power converters between the two. In this paper, a hydrogen energy storage system is utilized to provide a virtual inertia so as to dampen the disturbances and support the grid’s stability. An analytical model is developed based on experimental data and test results show that: (1) the proposed method is effective in supporting the grid frequency; (2) the maximum power point tracking is achieved by implementing this proposed system; and, (3) the DFIG efficiency is improved. The developed system is technically viable and can be applied to medium and large wind power systems. The hydrogen energy storage is a clean and environmental-friendly technology, and can increase the renewable energy penetration in the power network
PP-MeT: a Real-world Personalized Prompt based Meeting Transcription System
Speaker-attributed automatic speech recognition (SA-ASR) improves the
accuracy and applicability of multi-speaker ASR systems in real-world scenarios
by assigning speaker labels to transcribed texts. However, SA-ASR poses unique
challenges due to factors such as speaker overlap, speaker variability,
background noise, and reverberation. In this study, we propose PP-MeT system, a
real-world personalized prompt based meeting transcription system, which
consists of a clustering system, target-speaker voice activity detection
(TS-VAD), and TS-ASR. Specifically, we utilize target-speaker embedding as a
prompt in TS-VAD and TS-ASR modules in our proposed system. In constrast with
previous system, we fully leverage pre-trained models for system
initialization, thereby bestowing our approach with heightened generalizability
and precision. Experiments on M2MeT2.0 Challenge dataset show that our system
achieves a cp-CER of 11.27% on the test set, ranking first in both fixed and
open training conditions
One-pot melamine derived nitrogen doped magnetic carbon nanoadsorbents with enhanced chromium removal
Novel nitrogen doped magnetic carbons (NMC), in-situ synthesized through facile pyrolysis-carbonization processes using Fe(NO3)3 and melamine as precursors, were demonstrated as excellent nanoadsorbents to remove Cr(VI) effectively. The achieved removal capacity in both neutral and acidic solution was 29.4 and 2001.4 mg g−1 respectively, much higher than the reported adsorbents so far. The unprecedented high adsorption performance can be attributed to the incorporation of the nitrogen dopant, which increased the negative charge density on the surface of adsorbent and thereby enhanced the interaction between the adsorbents and Cr(VI) ions. The density functional theory (DFT) calculation demonstrated that the nitrogen dopants can decrease the adsorption energy between the Cr(VI) ions and NMC (−3.456 kJ mol−1), lower than the undoped sample (−3.344 kJ mol−1), which boosted the adsorption behavior. Chemical rather than physical adsorption was followed for these magnetic nanoadsorbents as revealed from the pseudo-second-order kinetic study. Furthermore, the NMC showed high stability with recycling tests for the Cr(VI) removal
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