109 research outputs found
Scale jump-aware pose graph relaxation for monocular SLAM with re-initializations
Pose graph relaxation has become an indispensable addition to SLAM enabling
efficient global registration of sensor reference frames under the objective of
satisfying pair-wise relative transformation constraints. The latter may be
given by incremental motion estimation or global place recognition. While the
latter case enables loop closures and drift compensation, care has to be taken
in the monocular case in which local estimates of structure and displacements
can differ from reality not just in terms of noise, but also in terms of a
scale factor. Owing to the accumulation of scale propagation errors, this scale
factor is drifting over time, hence scale-drift aware pose graph relaxation has
been introduced. We extend this idea to cases in which the relative scale
between subsequent sensor frames is unknown, a situation that can easily occur
if monocular SLAM enters re-initialization and no reliable overlap between
successive local maps can be identified. The approach is realized by a hybrid
pose graph formulation that combines the regular similarity consistency terms
with novel, scale-blind constraints. We apply the technique to the practically
relevant case of small indoor service robots capable of effectuating purely
rotational displacements, a condition that can easily cause tracking failures.
We demonstrate that globally consistent trajectories can be recovered even if
multiple re-initializations occur along the loop, and present an in-depth study
of success and failure cases.Comment: 8 pages, 23 figures, International Conference on Intelligent Robots
and Systems 202
A Blockchain-Enabled Framework of UAV Coordination for Post-Disaster Networks
Emergency communication is critical but challenging after natural disasters
when ground infrastructure is devastated. Unmanned aerial vehicles (UAVs) offer
enormous potential for agile relief coordination in these scenarios. However,
effectively leveraging UAV fleets poses additional challenges around security,
privacy, and efficient collaboration across response agencies. This paper
presents a robust blockchain-enabled framework to address these challenges by
integrating a consortium blockchain model, smart contracts, and cryptographic
techniques to securely coordinate UAV fleets for disaster response.
Specifically, we make two key contributions: a consortium blockchain
architecture for secure and private multi-agency coordination; and an optimized
consensus protocol balancing efficiency and fault tolerance using a delegated
proof of stake practical byzantine fault tolerance (DPoS-PBFT). Comprehensive
simulations showcase the framework's ability to enhance transparency,
automation, scalability, and cyber-attack resilience for UAV coordination in
post-disaster networks.Comment: 6 pages, 4 figures,IEEE 99th Vehicular Technology Conference:
VTC2024-Spring, Singapor
Terahertz magnetic field induced coherent spin precession in YFeO3
We present the magnetic dipole transition at 0.299 THz excited by magnetic component of terahertz electromagnetic pulse in an antiferromagnetic YFeO3 crystal. The impulsive magnetic field of the terahertz pulse tilts the macroscopic magnetization, causing deviation from the equilibrium position, which is manifested by a sharp absorption at the frequency of the quasiferromagnetic mode of the crystal. The rotating coherent macroscopic magnetization radiates elliptically polarized emission at the frequency of the quasiferromagnetic resonance due to the dichroic absorption in the crystal
A Wireless AI-Generated Content (AIGC) Provisioning Framework Empowered by Semantic Communication
Generative AI applications are recently catering to a vast user base by
creating diverse and high-quality AI-generated content (AIGC). With the
proliferation of mobile devices and rapid growth of mobile traffic, providing
ubiquitous access to high-quality AIGC services via wireless communication
networks is becoming the future direction for AIGC products. However, it is
challenging to provide optimal AIGC services in wireless networks with unstable
channels, limited bandwidth resources, and unevenly distributed computational
resources. To tackle these challenges, we propose a semantic communication
(SemCom)-empowered AIGC (SemAIGC) generation and transmission framework, where
only semantic information of the content rather than all the binary bits should
be extracted and transmitted by using SemCom. Specifically, SemAIGC integrates
diffusion-based models within the semantic encoder and decoder for efficient
content generation and flexible adjustment of the computing workload of both
transmitter and receiver. Meanwhile, we devise a resource-aware workload
trade-off (ROOT) scheme into the SemAIGC framework to intelligently decide
transmitter/receiver workload, thus adjusting the utilization of computational
resource according to service requirements. Simulations verify the superiority
of our proposed SemAIGC framework in terms of latency and content quality
compared to conventional approaches
LncRNA-p21 alters the antiandrogen enzalutamide-induced prostate cancer neuroendocrine differentiation via modulating the EZH2/STAT3 signaling
While the antiandrogen enzalutamide (Enz) extends the castration resistant prostate cancer (CRPC) patients' survival an extra 4.8 months, it might also result in some adverse effects via inducing the neuroendocrine differentiation (NED). Here we found that lncRNA-p21 is highly expressed in the NEPC patients derived xenograft tissues (NEPC-PDX). Results from cell lines and human clinical sample surveys also revealed that lncRNA-p21 expression is up-regulated in NEPC and Enz treatment could increase the lncRNA-p21 to induce the NED. Mechanism dissection revealed that Enz could promote the lncRNA-p21 transcription via altering the androgen receptor (AR) binding to different androgen-response-elements, which switch the EZH2 function from histone-methyltransferase to non-histone methyltransferase, consequently methylating the STAT3 to promote the NED. Preclinical studies using the PDX mouse model proved that EZH2 inhibitor could block the Enz-induced NED. Together, these results suggest targeting the Enz/AR/lncRNA-p21/EZH2/STAT3 signaling may help urologists to develop a treatment for better suppression of the human CRPC progression
Examining the Effect of Pre-training on Time Series Classification
Although the pre-training followed by fine-tuning paradigm is used
extensively in many fields, there is still some controversy surrounding the
impact of pre-training on the fine-tuning process. Currently, experimental
findings based on text and image data lack consensus. To delve deeper into the
unsupervised pre-training followed by fine-tuning paradigm, we have extended
previous research to a new modality: time series. In this study, we conducted a
thorough examination of 150 classification datasets derived from the Univariate
Time Series (UTS) and Multivariate Time Series (MTS) benchmarks. Our analysis
reveals several key conclusions. (i) Pre-training can only help improve the
optimization process for models that fit the data poorly, rather than those
that fit the data well. (ii) Pre-training does not exhibit the effect of
regularization when given sufficient training time. (iii) Pre-training can only
speed up convergence if the model has sufficient ability to fit the data. (iv)
Adding more pre-training data does not improve generalization, but it can
strengthen the advantage of pre-training on the original data volume, such as
faster convergence. (v) While both the pre-training task and the model
structure determine the effectiveness of the paradigm on a given dataset, the
model structure plays a more significant role
WiserVR: Semantic Communication Enabled Wireless Virtual Reality Delivery
Virtual reality (VR) over wireless is expected to be one of the killer
applications in next-generation communication networks. Nevertheless, the huge
data volume along with stringent requirements on latency and reliability under
limited bandwidth resources makes untethered wireless VR delivery increasingly
challenging. Such bottlenecks, therefore, motivate this work to seek the
potential of using semantic communication, a new paradigm that promises to
significantly ease the resource pressure, for efficient VR delivery. To this
end, we propose a novel framework, namely WIreless SEmantic deliveRy for VR
(WiserVR), for delivering consecutive 360{\deg} video frames to VR users.
Specifically, deep learning-based multiple modules are well-devised for the
transceiver in WiserVR to realize high-performance feature extraction and
semantic recovery. Among them, we dedicatedly develop a concept of semantic
location graph and leverage the joint-semantic-channel-coding method with
knowledge sharing to not only substantially reduce communication latency, but
also to guarantee adequate transmission reliability and resilience under
various channel states. Moreover, implementation of WiserVR is presented,
followed by corresponding initial simulations for performance evaluation
compared with benchmarks. Finally, we discuss several open issues and offer
feasible solutions to unlock the full potential of WiserVR.Comment: This article has been submitted to IEEE Wireless Communications
Magazine (after major revisions) for possible publicatio
A novel method of weakness imbalance fault identification and application in aero-hydraulic pump
A method of combining auto-correlation and Hilbert envelope analysis is proposed and used to identify weakness imbalance fault of aero-hydraulic pump, the central part of hydraulic system of aircraft. Firstly, the integral and polynomial least square fitting is applied to convert acceleration signal to velocity one; secondly, the Hilbert envelope spectrum of auto-correlation function of velocity signal is obtained and used to identify the weakness imbalance fault of aero-hydraulic pump; finally, the energy ratio of velocity signal is calculated according to Hilbert envelope spectrum for identifying imbalance fault of aero-hydraulic pump by means of easier and more visual method. Meanwhile, the comparing analysis is carried out between traditional research method and proposed new one. The result shows that the weakness imbalance fault of aero-hydraulic pump can be identified and diagnosed effectively and correctly according to the velocity signal whether Hilbert envelope spectrum or calculation energy ratio while direct acceleration signal cannot
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