In this work, we’ve made SnO<sub>2</sub> flower formed with the aid of using easy test steps, and without cost, which is the hydrothermal approach and without a template. We have used a variety of techniq...In this work, we’ve made SnO<sub>2</sub> flower formed with the aid of using easy test steps, and without cost, which is the hydrothermal approach and without a template. We have used a variety of techniques to characterize SnO<sub>2</sub> flower-shaped by (SEM, TEM, XRD, BET and XPS) instruments. Confirmatory tests carried out have proven that the surface of the tetragonal structure of SnO<sub>2</sub> has a rough surface which makes it excellent for its gas-sensing properties. The gas detection test of SnO<sub>2</sub> flower-shaped proved that it possesses the selectivity of formaldehyde gas (about 30), the optimum operating temperature of the sensor is 220<span style="white-space:nowrap;"><span style="white-space:nowrap;">°</span></span>C, and also the sensor has a high response time and recovery time is (5 s and 22 s) to 100 ppm, respectively. Particularly, the sensor has an obvious response value (2) when exposed to 5 ppm formaldehyde. As well, the mechanism of gas-sensing was also discussed.展开更多
Carbon nanotubes flower (CNTs-F) films were prepared by catalytic chemical vapor deposition (CVD) on a platinum (Pt) thin layer, supported on a silicon wafer. The products were synthesized from an aerosol composed of ...Carbon nanotubes flower (CNTs-F) films were prepared by catalytic chemical vapor deposition (CVD) on a platinum (Pt) thin layer, supported on a silicon wafer. The products were synthesized from an aerosol composed of ferrocene and toluene, as catalyst and carbon precursor respectively, at 820. The high synthesis temperature induces a modification of a Pt thin layer to a nano-structured island giving rise to the formation of CNTs-F during the following films growth step by CVD process. The suggested mechanism involves the selective diffusion of the catalyst and carbon atoms through the Pt grain boundaries. This results in the appearance of flower-like structures with 3-and 4-fold symmetries.展开更多
Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower...Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).展开更多
文摘In this work, we’ve made SnO<sub>2</sub> flower formed with the aid of using easy test steps, and without cost, which is the hydrothermal approach and without a template. We have used a variety of techniques to characterize SnO<sub>2</sub> flower-shaped by (SEM, TEM, XRD, BET and XPS) instruments. Confirmatory tests carried out have proven that the surface of the tetragonal structure of SnO<sub>2</sub> has a rough surface which makes it excellent for its gas-sensing properties. The gas detection test of SnO<sub>2</sub> flower-shaped proved that it possesses the selectivity of formaldehyde gas (about 30), the optimum operating temperature of the sensor is 220<span style="white-space:nowrap;"><span style="white-space:nowrap;">°</span></span>C, and also the sensor has a high response time and recovery time is (5 s and 22 s) to 100 ppm, respectively. Particularly, the sensor has an obvious response value (2) when exposed to 5 ppm formaldehyde. As well, the mechanism of gas-sensing was also discussed.
基金the Conseil Regional of PACA,the Conseil Général du Var,and Toulon Provence Mediterranean for their financial support.
文摘Carbon nanotubes flower (CNTs-F) films were prepared by catalytic chemical vapor deposition (CVD) on a platinum (Pt) thin layer, supported on a silicon wafer. The products were synthesized from an aerosol composed of ferrocene and toluene, as catalyst and carbon precursor respectively, at 820. The high synthesis temperature induces a modification of a Pt thin layer to a nano-structured island giving rise to the formation of CNTs-F during the following films growth step by CVD process. The suggested mechanism involves the selective diffusion of the catalyst and carbon atoms through the Pt grain boundaries. This results in the appearance of flower-like structures with 3-and 4-fold symmetries.
基金Project (Nos. 60302012 60202002) supported by the Nationa
Natural Science Foundation of China and the Research Grant
Council of the Hong Kong Special Administrative Region (No
PolyU 5119.01E) China
文摘Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).
