24 research outputs found
Communication Aware UAV Swarm Surveillance Based on Hierarchical Architecture
Get PDFMulti-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low altitude) UAV teaming hierarchical structure is adopted in realizing the accurate object tracking in the area of interest (AOI). By introducing the UAV communication channel model in its path planning, both centralized and decentralized control schemes would be evaluated in the waypoint tracking simulation. The UAV swarm network service and object tracking are measured by metrics of communication link quality and waypoints tracking accuracy. UAV swarm network connectivity are evaluated over different aspects, such as stability and volatility. The comparison of proposed algorithms is presented with simulations. The result shows that the decentralized scheme outperforms the centralized scheme in the mission of persistent surveillance, especially on maintaining the stability of inner UAV swarm network while tracking moving objects
Folate deficiency may increase the risk for elevated TSH in patients with type 2 diabetes mellitus
No full textAbstract Background Type 2 diabetes mellitus (T2DM) and thyroid dysfunction (TD) are two common chronic endocrine disorders that often coexist. Folate deficiency has been reported to be related with the onset and development of T2DM. However, the relationship between folate deficiency and TD remains unclear. This study aims to investigate the association of serum folate with TD in patients with T2DM. Methods The study used data on 268 inpatients with T2DM in the Beijing Chao-yang Hospital, Capital Medical University from October 2020 to February 2021. Thyroid stimulating hormone (TSH), free triiodothyronine (FT3), free thyroxine (FT4), and serum folate were measured with chemiluminescence immunoassay (CLIA), and folate deficiency was defined as a serum folate concentration < 4.4 ng/mL. Ordinary least squares regression models were used to assess the association of serum folate with TSH concentration. Multivariable logistic regression models were performed to explore the correlation of folate deficiency and the risk for elevated TSH. Results 15.3% of T2DM patients had TD. Among those patients with TD, 80.5% had elevated TSH. Compared with the normal-TSH and low-TSH groups, the prevalence of folate deficiency was significantly higher in the elevated-TSH group (P < 0.001). Serum folate level was negatively associated with TSH (β=-0.062, 95%CI: -0.112, -0.012). Folate deficiency was associated with the higher risk for elevated TSH in patients with T2DM (OR = 8.562, 95%CI: 3.108, 23.588). Conclusions A low serum folate concentration was significantly associated with a higher risk for elevated TSH among T2DM patients
Communication Aware UAV Swarm Surveillance Based on Hierarchical Architecture
No full textMulti-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low altitude) UAV teaming hierarchical structure is adopted in realizing the accurate object tracking in the area of interest (AOI). By introducing the UAV communication channel model in its path planning, both centralized and decentralized control schemes would be evaluated in the waypoint tracking simulation. The UAV swarm network service and object tracking are measured by metrics of communication link quality and waypoints tracking accuracy. UAV swarm network connectivity are evaluated over different aspects, such as stability and volatility. The comparison of proposed algorithms is presented with simulations. The result shows that the decentralized scheme outperforms the centralized scheme in the mission of persistent surveillance, especially on maintaining the stability of inner UAV swarm network while tracking moving objects
Communication Aware UAV Swarm Surveillance Based on Hierarchical Architecture
No full textMulti-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low altitude) UAV teaming hierarchical structure is adopted in realizing the accurate object tracking in the area of interest (AOI). By introducing the UAV communication channel model in its path planning, both centralized and decentralized control schemes would be evaluated in the waypoint tracking simulation. The UAV swarm network service and object tracking are measured by metrics of communication link quality and waypoints tracking accuracy. UAV swarm network connectivity are evaluated over different aspects, such as stability and volatility. The comparison of proposed algorithms is presented with simulations. The result shows that the decentralized scheme outperforms the centralized scheme in the mission of persistent surveillance, especially on maintaining the stability of inner UAV swarm network while tracking moving objects
A Data-Driven Approach for Mitigating Dark Current Noise and Bad Pixels in Complementary Metal Oxide Semiconductor Cameras for Space-based Telescopes
Full text linkIn recent years, there has been a gradual increase in the performance of
Complementary Metal Oxide Semiconductor (CMOS) cameras. These cameras have
gained popularity as a viable alternative to charge-coupled device (CCD)
cameras in a wide range of applications. One particular application is the CMOS
camera installed in small space telescopes. However, the limited power and
spatial resources available on satellites present challenges in maintaining
ideal observation conditions, including temperature and radiation environment.
Consequently, images captured by CMOS cameras are susceptible to issues such as
dark current noise and defective pixels. In this paper, we introduce a
data-driven framework for mitigating dark current noise and bad pixels for CMOS
cameras. Our approach involves two key steps: pixel clustering and function
fitting. During pixel clustering step, we identify and group pixels exhibiting
similar dark current noise properties. Subsequently, in the function fitting
step, we formulate functions that capture the relationship between dark current
and temperature, as dictated by the Arrhenius law. Our framework leverages
ground-based test data to establish distinct temperature-dark current relations
for pixels within different clusters. The cluster results could then be
utilized to estimate the dark current noise level and detect bad pixels from
real observational data. To assess the effectiveness of our approach, we have
conducted tests using real observation data obtained from the Yangwang-1
satellite, equipped with a near-ultraviolet telescope and an optical telescope.
The results show a considerable improvement in the detection efficiency of
space-based telescopes.Comment: Accepted by the AJ, comments are welcome. The complete code could be
downloaded from: DOI: 10.12149/10138
Communication Aware UAV Swarm Surveillance Based on Hierarchical Architecture
No full textMulti-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low altitude) UAV teaming hierarchical structure is adopted in realizing the accurate object tracking in the area of interest (AOI). By introducing the UAV communication channel model in its path planning, both centralized and decentralized control schemes would be evaluated in the waypoint tracking simulation. The UAV swarm network service and object tracking are measured by metrics of communication link quality and waypoints tracking accuracy. UAV swarm network connectivity are evaluated over different aspects, such as stability and volatility. The comparison of proposed algorithms is presented with simulations. The result shows that the decentralized scheme outperforms the centralized scheme in the mission of persistent surveillance, especially on maintaining the stability of inner UAV swarm network while tracking moving objects
Multi-Source Domain Fusion Cross-Domain Pedestrian Recognition Based on High-Quality Intermediate Domains
No full textPedestrian detection has received considerable attention over the last few years because it can be combined with pedestrian tracking and re-identification in areas such as vehicle-assisted driving and intelligent video surveillance. Although existing pedestrian detection techniques have achieved excellent results, problems such as domain gaps lead to poor generalization performance in these techniques, thereby limiting its application and practical value. This study proposed a high-quality integration domain framework for pedestrian recognition. First, the source domains are produced as super-resolution training data. The HCycleGAN model uses super-resolution algorithms and a generative framework to generate high-quality intermediate domains. Second, a multi-source domain fusion scheme based on the NPIQE module is proposed to improve the generated framework’s quality and reduce overfitting of the dataset. It fuses images in three aspects: similarity, blurriness and unsupervised image quality score values. Finally, we use an anchor-free center and scale prediction model for pedestrian detection. The experimental dataset contained two common pedestrian detection datasets, Caltech and CityPersons. Cross-domain experimental results show that the framework can reduce cross-domain detection miss rate from CityPersons to Caltech by 6.3% and from Caltech to CityPersons by 4.4%. The training of CityPersons in Caltech achieves almost the same detection accuracy as that of the Caltech original domain. In conclusion, the framework presented in this study is effective for cross-domain pedestrian detection and can provide ideas and inspiration for future practical applications
