Unmanned aerial vehicle video-based target tracking algorithm Using sparse representation

Target tracking based on unmanned aerial vehicle (UAV) video is a significant technique in intelligent urban surveillance systems for smart city applications, such as smart transportation, road traffic monitoring, inspection of stolen vehicle, etc. In this paper, a vision-based target tracking algorithm aiming at locating UAV-captured targets, like pedestrian and vehicle, is proposed using sparse representation theory. First of all, each target candidate is sparsely represented in the subspace spanned by a joint dictionary. Then, the sparse representation coefficient is further constrained by an L2 regularization based on the temporal consistency. To cope with the partial occlusion appearing in UAV videos, a Markov Random Field (MRF)-based binary support vector with contiguous occlusion constraint is introduced to our sparse representation model. For long-term tracking, the particle filter framework along with a dynamic template update scheme is designed. Both qualitative and quantitative experiments implemented on visible (Vis) and infrared (IR) UAV videos prove that the presented tracker can achieve better performances in terms of precision rate and success rate when compared with other state-of-the-art tracker

Robust residual-guided iterative reconstruction for sparse-view CT in small animal imaging

Objective. We introduce a robust image reconstruction algorithm named residual-guided Golub–Kahan iterative reconstruction technique (RGIRT) designed for sparse-view computed tomography (CT), which aims at high-fidelity image reconstruction from a limited number of projection views. Approach. RGIRT utilizes an inner-outer dual iteration framework, with a flexible least square QR (FLSQR) algorithm implemented in the inner iteration and a restarted iterative scheme applied in the outer iteration. The inner FLSQR employs a flexible Golub–Kahan bidiagonalization method to reduce the size of the inverse problem, and a weighted generalized cross-validation method to adaptively estimate the regularization hyper-parameter. The inner iteration efficiently yields the intermediate reconstruction result, while the outer iteration minimizes the residual and refines the solution by using the result obtained from the inner iteration. Main results. The reconstruction performance of RGIRT is evaluated and compared to other reference methods (FBPConvNet, SART-TV, and FLSQR) using projection data from both numerical phantoms and real experimental Micro-CT data. The experimental findings, from testing various numbers of projection views and different noise levels, underscore the robustness of RGIRT. Meanwhile, theoretical analysis confirms the convergence of residual for our approach. Significance. We propose a robust iterative reconstruction algorithm for x-ray CT scans with sparse views, thereby shortening scanning time and mitigating excessive ionizing radiation exposure to small animals

Compressed Sensing and Low-Rank Matrix Decomposition in Multisource Images Fusion

We propose a novel super-resolution multisource images fusion scheme via compressive sensing and dictionary learning theory. Under the sparsity prior of images patches and the framework of the compressive sensing theory, the multisource images fusion is reduced to a signal recovery problem from the compressive measurements. Then, a set of multiscale dictionaries are learned from several groups of high-resolution sample image’s patches via a nonlinear optimization algorithm. Moreover, a new linear weights fusion rule is proposed to obtain the high-resolution image. Some experiments are taken to investigate the performance of our proposed method, and the results prove its superiority to its counterparts

Infrared image enhancement using adaptive histogram partition and brightness correction

Infrared image enhancement is a crucial pre-processing technique in intelligent urban surveillance systems for Smart City applications. Existing grayscale mapping-based algorithms always suffer from over-enhancement of the background, noise amplification, and brightness distortion. To cope with these problems, an infrared image enhancement method based on adaptive histogram partition and brightness correction is proposed. First, the grayscale histogram is adaptively segmented into several sub-histograms by a locally weighted scatter plot smoothing algorithm and local minima examination. Then, the fore-and background sub-histograms are distinguished according to a proposed metric called grayscale density. The foreground sub-histograms are equalized using a local contrast weighted distribution for the purpose of enhancing the local details, while the background sub-histograms maintain the corresponding proportions of the whole dynamic range in order to avoid over-enhancement. Meanwhile, a visual correction factor considering the property of human vision is designed to reduce the effect of noise during the procedure of grayscale re-mapping. Lastly, particle swarm optimization is used to correct the mean brightness of the output by virtue of a reference image. Both qualitative and quantitative evaluations implemented on real infrared images demonstrate the superiority of our method when compared with other conventional methods

Preparation of supported skeletal Ni catalyst and its catalytic hydrogenation performance of C9 fraction from coking process

Currently, the inferior compressive strength of traditional Raney-Ni catalyst restricts its application in fixed-bed reactor. To approach this problem a series of supported skeletal Ni catalysts were prepared by mixing pseudo boehmite and Ni-Al alloy powder. In the process,the calcination temperature and atmosphere, mass ratio of pseudo boehmite to Ni-Al alloy powder and the sodium hydroxide solution concentration were investigated. The catalysts characterized by intelligent granule intensity tester(IGIT), scanning electron microscopy(SEM), X-ray photoelectron spectroscopy(XPS), X-ray diffraction (XRD),low temperature nitrogen adsorption, temperature programmed reduction of hydrogen (H2-TPR), and thermogravimetric-differential thermal analysis (TG-DTA).The results were shown that the calcination atmosphere had a considerable impact on the compressive strength of the catalyst. Compared with air atmosphere, the compressive strength of the catalyst increased from 12.62 N/mm to 23.96N/mm, obviously, in argon atmosphere, which was almost twice as much as the former.The inherent reason for this was that the argon obviously inhibited the transform of NiAl3 to Ni2Al3 in which the latter was the key factor to improve compressive strength. Additionally, coke-oven C9 hydrogenation was used to evaluate the performance of the catalyst and the results indicated that the conversion of indene, the key component of coke-oven C9, was as high as 90% in 1000h under the optimum reaction conditions:T=220oC, P(H2)=2.5MPa, H2/oil=200(v/v), LHSV=3.0h-1. Our data demonstrated that the supported skeletal Ni catalyst have a good industrial prospect in the fixed-bed reactor in future

Motion Segmentation by New Three-View Constraint from a Moving Camera

We propose a new method for the motion segmentation using a moving camera. The proposed method classifies each image pixel in the image sequence as the background or the motion regions by applying a novel three-view constraint called the “parallax-based multiplanar constraint.” This new three-view constraint, being the main contribution of this paper, is derived from the relative projective structure of two points in three different views and implemented within the “Plane + Parallax” framework. The parallax-based multiplanar constraint overcomes the problem of the previous geometry constraint and does not require the reference plane to be constant across multiple views. Unlike the epipolar constraint, the parallax-based multiplanar constraint modifies the surface degradation to the line degradation to detect the motion objects followed by a moving camera in the same direction. We evaluate the proposed method with several video sequences to demonstrate the effectiveness and robustness of the parallax-based multiplanar constraint

Emission of PAHs, NPAHs and OPAHs from residential honeycomb coal briquette combustion

Coal combustion is one of the most significant sources of air pollution in China. In this study, emission factors (EFs) of 15 polycyclic aromatic hydrocarbons (PAHs), 26 nitrated PAHs (NPAHs) and 6 oxygenated PAHs (OPAHs) were determined in five different coals with different geological maturity (vitrinite reflectance <i>R</i>_O = 0.77–1.88%) burned in the form of honeycomb briquettes. The total EFs ranged from 9.82 to 215 mg kg^–1 for PAHs, 0.14 to 1.88 mg kg^–1 for NPAHs and 4.47 to 20.8 mg kg^–1 for OPAHs. Measured EFs and gas-particle partitioning varied depending on the geological maturity. The lowest EFs were found in anthracite. The proportion of PAHs, NPAHs and OPAHs in gaseous phase increasing with increased geological maturity. The coal with higher geological maturity produced more 3-ring PAHs. On the basis of the statistical analysis for the residential sector of China in 2008, PAHs, NPAHs and OPAHs emitted from residential honeycomb coal briquettes were 4.36 Gg, 0.03 Gg and 0.47 Gg in 2007, respectively. By 2020, the emission would decrease to 2.18 Gg, 0.02 Gg and 0.24 Gg for PAHs, NPAHs and OPAHs due to the increasing usage of new energy resources. If only anthracite is used as the residential coal, 93% PAHs, 87% NPAHs and 71% OPAHs would be reduced in 2020

Wavelength and pulse duration tunable ultrafast fiber laser mode-locked with carbon nanotubes.

Ultrafast lasers with tunable parameters in wavelength and time domains are the choice of light source for various applications such as spectroscopy and communication. Here, we report a wavelength and pulse-duration tunable mode-locked Erbium doped fiber laser with single wall carbon nanotube-based saturable absorber. An intra-cavity tunable filter is employed to continuously tune the output wavelength for 34 nm (from 1525 nm to 1559 nm) and pulse duration from 545 fs to 6.1 ps, respectively. Our results provide a novel light source for various applications requiring variable wavelength or pulse duration

The protective effect of DNase I in retinal vein occlusion

Retinal vein occlusion (RVO) ranks as the second most prevalent retinal vascular disease, following diabetic retinopathy. Neutrophil extracellular traps (NETs) play an important role in vascular diseases. This study aimed to elucidate the relationship between NETs and RVO, and to discern the potential role of deoxyribonuclease I (DNase I) in the prevention and treatment of RVO through the modulation of NETs. We analyzed circulating NETs biomarkers, namely cell-free DNA (cf-DNA), myeloperoxidase (MPO)-DNA, and neutrophil elastase (NE), in 30 RVO patients and 30 healthy individuals. We established an RVO mouse model using a retinal laser, and the mice were categorized into two groups: the DNase I group and the control group. Retinal images were taken at predetermined time points, and the state of the retinal vessels was assessed. Both tissue and blood samples were harvested for analysis of NETs expression through methods such as western blotting, immunofluorescence staining, and enzyme-linked immunosorbent assay (ELISA). Our finding indicate an increase in circulating NETs biomarkers in human and mouse RVO cases, while also verifying the presence of NETs in the retinal thrombus of the RVO model. Both in vitro and in vivo tests revealed that DNase I attenuated NETs formation. Moreover, DNase I injections led to diminished NETs biomarker levels and a reduced duration of the thrombus after the RVO model establishment. Consequently, DNase I, a well-established modulator of NETs formation, might exhibit protective properties in the prevention and treatment of RVO

Qi-Shen-Yi-Qi Dripping Pills for the Secondary Prevention of Myocardial Infarction: A Randomised Clinical Trial

Background. Several types of drugs have been recommended for the secondary prevention of myocardial infarction (MI). However, these conventional strategies have several limitations, such as low adherence, high cost, and side effects during long time use. Novel approaches to this problem are still needed. This trial aimed to test the effectiveness and safety of Qi-Shen-Yi-Qi Dripping Pills (QSYQ), a multi-ingredient Chinese patent medicine, for the secondary prevention of MI. Methods and Findings. A total of 3505 eligible patients were randomly assigned to QSYQ group (1746 patients) or aspirin group (1759). Patients took their treatments for 12 months. The final follow-up visit took place 6 months after the end of the trial drugs. The 12-month and 18-month estimated incidences of the primary outcome were 2.98% and 3.67%, respectively, in the QSYQ group. The figures were 2.96% and 3.81% in the aspirin group. No significant difference was identified between the groups. Conclusions. This trial did not show significant difference of primary and secondary outcomes between aspirin and QSYQ in patients who have had an MI. Though inconclusive, the result suggests that QSYQ has similar effects to aspirin in the secondary prevention of MI