Cross-CBAM: A Lightweight network for Scene Segmentation

Scene parsing is a great challenge for real-time semantic segmentation. Although traditional semantic segmentation networks have made remarkable leap-forwards in semantic accuracy, the performance of inference speed is unsatisfactory. Meanwhile, this progress is achieved with fairly large networks and powerful computational resources. However, it is difficult to run extremely large models on edge computing devices with limited computing power, which poses a huge challenge to the real-time semantic segmentation tasks. In this paper, we present the Cross-CBAM network, a novel lightweight network for real-time semantic segmentation. Specifically, a Squeeze-and-Excitation Atrous Spatial Pyramid Pooling Module(SE-ASPP) is proposed to get variable field-of-view and multiscale information. And we propose a Cross Convolutional Block Attention Module(CCBAM), in which a cross-multiply operation is employed in the CCBAM module to make high-level semantic information guide low-level detail information. Different from previous work, these works use attention to focus on the desired information in the backbone. CCBAM uses cross-attention for feature fusion in the FPN structure. Extensive experiments on the Cityscapes dataset and Camvid dataset demonstrate the effectiveness of the proposed Cross-CBAM model by achieving a promising trade-off between segmentation accuracy and inference speed. On the Cityscapes test set, we achieve 73.4% mIoU with a speed of 240.9FPS and 77.2% mIoU with a speed of 88.6FPS on NVIDIA GTX 1080Ti

Exploring the core knowledge of business intelligence

With the rapid development of data analysis, there is few research on the core knowledge of business intelligence system (BIS). In order to fill this research gap, this paper collected the 1003 articles and 31345 references from the Web of Science database, and then applied co-citation analysis and factor analysis, to analyze their core knowledge. We identified 52 highly cited articles and obtained 9 core knowledge categories in the field of BI: BI success, IT acceptance and measurement, big data analysis,dataanalysis anddecision making,business strategy, BIS,consumer behavior, knowledge management, business adoption. Research shows that BISs are still in the growing trend and core knowledge helps researchers and managers better understand the core concepts and relevance of BI, so as to quickly discover possible research directionsinthisresearchfieldandusefulapplicationsintheenterprise

MOQPSO-D/S for Air and Missile Defense WTA Problem under Uncertainty

Aiming at the shortcomings of single objective optimization for solving weapon target assignment (WTA) and the existing multiobjective optimization based WTA method having problems being applied in air and missile defense combat under uncertainty, a fuzzy multiobjective programming based WTA method was proposed to enhance the adaptability of WTA decision to the changes of battlefield situation. Firstly, a multiobjective quantum-behaved particle swarm optimization with double/single-well (MOQPSO-D/S) algorithm was proposed by adopting the double/single-well based position update method, the hybrid random mutation method, and the two-stage based guider particles selection method. Secondly, a fuzzy multiobjective programming WTA model was constructed with consideration of air and missile defense combat’s characteristics. And, the uncertain WTA model was equivalently clarified based on the necessity degree principle of uncertainty theory. Thirdly, with particles encoding and illegal particles adjusting, the MOQPSO-D/S algorithm was adopted to solve the fuzzy multiobjective programming based WTA model. Finally, example simulation was conducted, and the result shows that the WTA model constructed is rational and MOQPSO-D/S algorithm is efficient

Molecular Composition of Oxygenated Organic Molecules and Their Contributions to Organic Aerosol in Beijing

The understanding at a molecular level of ambient secondary organic aerosol (SOA) formation is hampered by poorly constrained formation mechanisms and insufficient analytical methods. Especially in developing countries, SOA related haze is a great concern due to its significant effects on climate and human health. We present simultaneous measurements of gas-phase volatile organic compounds (VOCs), oxygenated organic molecules (OOMs), and particle-phase SOA in Beijing. We show that condensation of the measured OOMs explains 26-39% of the organic aerosol mass growth, with the contribution of OOMs to SOA enhanced during severe haze episodes. Our novel results provide a quantitative molecular connection from anthropogenic emissions to condensable organic oxidation product vapors, their concentration in particle-phase SOA, and ultimately to haze formation.Peer reviewe

Rosiglitazone Inhibits Transforming Growth Factor-β1 Mediated Fibrogenesis in ADPKD Cyst-Lining Epithelial Cells

BACKGROUND: Interstitial fibrosis plays an important role in progressive renal dysfunction in autosomal dominant polycystic kidney disease (ADPKD). In our previous studies, we confirmed that PPAR-γ agonist, rosiglitazone could protect renal function and prolong the survival of a slowly progressive ADPKD animal model by reducing renal fibrosis. However, the mechanism remains unknown. METHODS: Primary culture epithelial cells pretreated with TGF-β1 were incubated with rosiglitazone. Extracellular matrix proteins were detected using real-time PCR and Western blotting. MAPK and Smad2 phosphorylation were measured with western blot. ERK1/2 pathway and P38 pathway were inhibited with the specific inhibitors PD98059 and SB203580. The Smad2 pathway was blocked with the siRNA. To address whether PPAR-γ agonist-mediated inhibition of TGF-β1-induced collagen type I expression was mediated through a PPAR-γ dependent mechanism, genetic and pharmaceutical approaches were used to block the activity of endogenous PPARγ. RESULTS: TGF-β1-stimulated collagen type I and fibronectin expression of ADPKD cyst-lining epithelia were inhibited by rosiglitazone in a dosage-dependent manner. Smad2, ERK1/2 and P38 pathways were activated in response to TGF-β1; however, TGF-β1 had little effect on JNK pathway. Rosiglitazone suppressed TGF-β1 induced Smad2 activation, while ERK1/2 and P38MAPK signals remained unaffected. Rosiglitazone could also attenuate TGF-β1-stimulated collagen type I and fibronectin expression in primary renal tubular epithelial cells, but had no effect on TGF-β1-induced activation of Smad2, ERK1/2 and P38 pathways. There was no crosstalk between the Smad2 and MAPK pathways in ADPKD cyst-lining epithelial cells. These inhibitory effects of rosiglitazone were reversed by the PPARγ specific antagonist GW9662 and PPARγ siRNA. CONCLUSION: ADPKD cyst-lining epithelial cells participate in TGF-β1 mediated fibrogenesis. Rosiglitazone could suppress TGF-β1-induced collagen type I and fibronectin expression in ADPKD cyst-lining epithelia through modulation of the Smad2 pathway. Our study may provide therapeutic basis for clinical applications of rosiglitazone in retarding the progression of ADPKD

Multiscale method for identifying and marking the multiform fractures from visible-light rock-mass images

Multiform fractures have a direct impact on the mechanical performance of rock masses. To accurately identify multiform fractures, the distribution patterns of grayscale and the differential features of fractures in their neighborhoods are summarized. Based on this, a multiscale processing algorithm is proposed. The multiscale process is as follows. On the neighborhood of pixels, a grayscale continuous function is constructed using bilinear interpolation, the smoothing of the grayscale function is realized by Gaussian local filtering, and the grayscale gradient and Hessian matrix are calculated with high accuracy. On small-scale blocks, the pixels are classified by adaptively setting the grayscale threshold to identify potential line segments and mini-fillings. On the global image, potential line segments and mini-fillings are spliced together by progressing the block frontier layer-by-layer to identify and mark multiform fractures. The accuracy of identifying multiform fractures is improved by constructing a grayscale continuous function and adaptively setting the grayscale thresholds on small-scale blocks. And the layer-by-layer splicing algorithm is performed only on the domain of the 2-layer small-scale blocks, reducing the complexity. By using rock mass images with different fracture types as examples, the identification results show that the proposed algorithm can accurately identify the multiform fractures, which lays the foundation for calculating the mechanical parameters of rock masses

Design and Joint Position Control of Bionic Jumping Leg Driven by Pneumatic Artificial Muscles

Using the skeletal structure and muscle distribution of the hind limbs of a jumping kangaroo as inspiration, a bionic jumping leg was designed with pneumatic artificial muscles (PAMs) as actuators. Referring to the position of biarticular muscles in kangaroos, we constructed a bionic joint using biarticular and monoarticular muscle arrangements. At the same time, the problem of the joint rotation angle limitations caused by PAM shrinkage was solved, and the range of motion of the bionic joint was improved. Based on the output force model of the PAM, we established a dynamic model of the bionic leg using the Lagrange method. In view of the coupling problem caused by the arrangement of the biarticular muscle, an extended state observer was used for decoupling. The system was decoupled into two single-input and single-output systems, and angle tracking control was carried out using active disturbance rejection control (ADRC). The simulation and experimental results showed that the ADRC algorithm had a better decoupling effect and shorter adjustment time than PID control. The jumping experiments showed that the bionic leg could jump with a horizontal displacement of 320 mm and a vertical displacement of 150 mm