Refine your search
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Li, Yue
- Research on Content, Distribution and Health Risk Assessment of PAHs in Surface Dust in Shenyang City
Abstract Views :116 |
PDF Views:0
Authors
Affiliations
1 College of Environmental Science, Liaoning University, 66 Chongshan Middle Road, Huanggu District, Shenyang 110036, CN
2 Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, 72 Wenhua Street, Shenhe District, Shenyang 110016, CN
1 College of Environmental Science, Liaoning University, 66 Chongshan Middle Road, Huanggu District, Shenyang 110036, CN
2 Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, 72 Wenhua Street, Shenhe District, Shenyang 110016, CN
Source
Nature Environment and Pollution Technology, Vol 14, No 3 (2015), Pagination: 721-726Abstract
As the "source" and "collector" of PAHs, surface dust in cities, cause invisible, potential and long-term destructions to ecosystems. PAHs content in the surface dust and distributions of functional areas in Shenyang city was discussed systematically. PAHs composition differences in different functional areas were analysed. It was concluded that parks and residential districts present the least PAHs pollution, while commercial districts and roads suffer the heaviest PAHs pollution. Different functional areas show similar composition of PAHs. Most PAHs are high-ring ones, accompanied with some low-ring PAHs. The content of high-ring PAHs is proportional to the number of rings or molecular weight. PAHs pollution and health risk in Shenyang city were evaluated through various methods. Results demonstrated that PAHs pollution in Shenyang city has reached a high level, which is threatening the local ecological environment and human health significantly.Keywords
PAHs, Surface Dust, Health Risk Assessment.Full Text
- Automated Corpus Callosum Segmentation in Midsagittal Brain MR Images
Abstract Views :219 |
PDF Views:7
Authors
Affiliations
1 Department of Electrical and Computer Engineering, University of Alberta, CA
2 Department of Medicine, University of Alberta, CA
1 Department of Electrical and Computer Engineering, University of Alberta, CA
2 Department of Medicine, University of Alberta, CA
Source
ICTACT Journal on Image and Video Processing, Vol 8, No 1 (2017), Pagination: 1554-1565Abstract
Corpus Callosum (CC) is an important white-matter structure in the human brain. Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that provides high resolution images for the structures. Segmentation is an important step in medical image analysis. This paper proposes a fully automated technique for segmentation of CC on the midsagittal slice of T1-weighted brain MR images. The proposed technique consists of three modules. First it clusters all homogenous regions in the image with an adaptive mean shift (AMS) technique. The automatic CC contour initialization (ACI) is achieved using the region analysis, template matching and location analysis, thus identify the CC region. Finally, the boundary of recognized CC region is used as the initial contour in the Geometric Active Contour (GAC) model, and is evolved to obtain the final segmentation result of CC. Experimental results demonstrate that the proposed AMS-ACI technique is able to provide accurate initial CC contour, and the proposed AMS-ACI-GAC technique overcomes the problem of user-guided initialization in existing GAC techniques, and provides a reliable and accurate performance in CC segmentation.Keywords
Adaptive Mean Shift Clustering, Automated Segmentation, Corpus Callosum, Geometric Active Contour, Template Matching.
References
- P. Conlon and M.R. Trimble, “A Study of the Corpus Callosum in Epilepsy using Magnetic Resonance Imaging”, Epilepsy Research, Vol. 2, No. 2, pp. 122-126, 1988.
- H. Chahboune et al., “DTI Abnormalities in Anterior Corpus Callosum of Rats with Spike-Wave Epilepsy,” Neuroimage, Vol. 47, No. 2, pp. 459-466, 2009.
- Q. He, Y. Duan, J. Miles and N. Takahashi, “Statistical Shape Analysis of the Corpus Callosum in Subtypes of Autism”, Proceedings of 7th Annual International Conference on Bio Engineering, pp. 1087-1091, 2007.
- Q. He, K. Karsch and Y. Duan, “Abnormalities in MRI Traits of Corpus Callosum in Autism Subtype”, Proceedings of 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 39003903, 2008.
- K. Von Plessen, A. Lundervold, N. Duta, E. Heiervang, F. Klauschen, A. Smievoll, L. Ersland and K. Hugdahl, “Less Developed Corpus Callosum in Dysplexic Subjects-A Structural MRI Study”, Neuropsychologia, Vol. 40, No. 7, pp. 1035-1044, 2002.
- J.G. Fine, M. Semrud-Clikeman, T.Z. Keith, L.M. Stapleton and G.W. Hynd, “Reading and the Corpus Callosum: An MRI Family Study of Volume and Area”, Neuropsychology, Vol. 21, No. 2, pp. 235-241, 2007.
- Medical Imaging, Available at:
- http://www.cihi.ca/CIHI-extportal/internet/EN/TabbedContent/types+of+care/specialize d+services/medical+imaging/cihi010642.
- H.T. Chugani, “Neuroimaging in Epilepsy”, Oxford University Press, 2011.
- M. Brejl and M. Sonka, “Object Localization and Border Detection Criteria Design in Edge-based Image Segmentation: Automated Learning from Examples”, IEEE Transactions on Medical Imaging, Vol. 19, No. 10, pp. 973985, 2000.
- B.V. Ginneken, A.F. Frangi, J.J. Staal, B.M.T.H. Romeny and M.A. Viergever, “Active Shape Model Segmentation with Optimal Features”, IEEE Transactions on Medical Imaging, Vol. 21, No. 8, pp. 924-933, 2002.
- M. Jacob, T. Blu and M. Unser, “Efficient Energies and Algorithms for Parametric Snakes”, IEEE Transactions on Image Processing, Vol. 13, No. 9, pp. 1231-1244, 2004.
- R. Sandhu, T. Georgiou, and A. Tannenbaum, “A New Distribution Metric for Image Segmentation”, Technical Paper, Georgia Institute of Technology, pp. 1-9, 2008.
- J. Zhou, S. Chang, S. Zhang, G. Pappas, M. Michaelides, F. Delis, N. Volkow, P. Thanos and D. Metaxas, “A Novel Learning based Segmentation Method for Rodent Brain Structures using MRI”, Proceedings of 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 61-64, 2008.
- N. El-Zehiry, M. Casanova and A. Elmaghraby, “Variability of the Relative Corpus Callosum Cross Sectional Area between Dyslexic and Normally Developed Brains”, Proceedings of 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 436-439, 2008.
- Rongjie Lai, Yonggang Shi, Nancy Sicotte and Arthur W. Toga, “Automated Corpus Callosum Extraction via Laplace-Beltrami Nodal Parcellation and Intrinsic Geodesic Curvature Flows on Surfaces”, Proceedings of IEEE International Conference on Computer Vision, pp. 20342040, 2011.
- A. Mayer and H. Greenspan, “An Adaptive Mean-Shift Framework for MRI Brain Segmentation”, IEEE Transactions on Medical Imaging, Vol. 28, No. 8, pp. 12381250, 2009.
- Tao Xu, Irene Cheng and Mrinal Mandal, “Automated Cavity Detection of Infectious Pulmonary Tuberculosis in Chest Radiographs”, Proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 5178-5181, 2011.
- Daniel S. Marcus, Tracy H. Wang, Jamie Parker and John G. Csernansky, “Open Access Series of Imaging Studies (OASIS):Cross-Sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults”, Journal of Cognitive Neuroscience, Vol. 19, No. 9, pp. 1498-1507, 2007.
- T. Xu, M. Mandal, R. Long, I. Cheng and A. Basu, “An Edge-Region Force Guided Active Shape Approach for Automatic Lung Field Detection in Chest Radiographs”, Computerized Medical Imaging and Graphics, Vol. 36, No. 6, pp. 452-63, 2012.
- S. Anand, S. Mittal, O. Tuzel and P. Meer, “Semi-Supervised Kernel Mean Shift Clustering”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 36, No. 6, pp. 1201-1215, 2014.
- Slope Stability Analysis with Reference to Rainfall Infiltration in the Yongping Copper Mine, China
Abstract Views :233 |
PDF Views:74
Authors
Affiliations
1 Hohai University, Nanjing, 210098, CN
2 Nanjing Tech University, Nanjing, 210098, CN
3 State Key Laboratory of Safety and Health for Metal Mines, Sinosteel Maanshan Institute of Mining Research, Co, Ltd, Anhui, 243000, CN
1 Hohai University, Nanjing, 210098, CN
2 Nanjing Tech University, Nanjing, 210098, CN
3 State Key Laboratory of Safety and Health for Metal Mines, Sinosteel Maanshan Institute of Mining Research, Co, Ltd, Anhui, 243000, CN
Source
Current Science, Vol 116, No 4 (2019), Pagination: 536-543Abstract
Due to the influence of rainfall infiltration, the slope of Yongping Copper Mine appears to have a high probability of instability, posing a great threat to the mineral transportation roads and mining safety. In this study, the hydraulic response of the slope under rainfall conditions is simulated, the response of the slope under different rainfall conditions is discussed, and the safety factor (FS) and the probability of failure (Pf) of the slope during and after a rainfall are analysed. The results indicate that rainfall infiltration has a hysteretic effect on slope instability. The failure of the mining slope at the elevation between 178 m and 226 m is likely to occur in three days after a rainfall. The activity distribution of the slope indicates that it is an advancing landslide.Keywords
Failure Probability, Open-Pit Mine, Rainfall Infiltration, Safety Factor, Slope Stability.Full Text
References
- Dou, H., Han, T., Gong, X. and Zhang, J., Probabilistic slope stability analysis considering the variability of hydraulic conductivity under rainfall infiltration–redistribution conditions. Eng. Geol., 2014, 183, 1–13.
- Calvello, M., D’Orsi, R. N., Piciullo, L., Paes, N., Magalhaes, M. and Lacerda, W. A., The Rio de Janeiro early warning system for rainfall-induced landslides: Analysis of performance for the years 2010–2013. Int. J. Disaster Risk Reduct., 2015, 12, 3–15.
- Rosi, A., Peternel, T., Jemec-Auflič, M., Komac, M., Segoni, S. and Casagli, N., Rainfall thresholds for rainfall-induced landslides in Slovenia. Landslides, 2016, 13, 1571–1577.
- Zhang, L. L., Zhang, J., Zhang, L. M. and Tang, W. H., Stability analysis of rainfall induced slope failure: A review. Proc. Inst. Civil Eng. Geotech. Eng., 2011, 164, 299–316.
- Satyanaga, A., Rainfall-Induced Slope Failures and Preventive Measures in Singapore, Nanyang Technological University, Singapore, 2014.
- Iverson, R. M., Landslide triggering by rain infiltration. Water Resour. Res., 2000, 36, 1897–1910.
- Tsai, T. L. and Yang, J. C., Modeling of rainfall-triggered shallow landslide. Environ. Geol., 2006, 50, 525–534.
- Caine, N., The rainfall intensity-duration control of shallow landslides and debris flows. Geogr. Ann. Ser. A, Phys. Geogr., 1980, 62, 23–27.
- Guzzetti, F., Peruccacci, S., Rossi, M. and Stark, C. P., The rainfall intensity–duration control of shallow landslides and debris flows: an update. Landslides, 2008, 5, 3–17.
- Fourie, A. B., Predicting rainfall-induced slope instability. Proc. ICE – Geotech. Eng., 1996, 119, 211–218.
- Muntohar, A. S. and Liao, H. J., Rainfall infiltration: infinite slope model for landslides triggering by rainstorm. Nat. Hazards, 2010, 54, 967–984.
- White, J. A. and Singham, D. I., Slope stability assessment using stochastic rainfall simulation. Proc. Comput. Sci., 2012, 9, 699–706.
- Chen, R. H., Chen, H. P., Chen, K. S. and Zhung, H. B., Simulation of a slope failure induced by rainfall infiltration. Environ. Geol., 2009, 58, 943–952.
- Raj, M. and Sengupta, A., Rain-triggered slope failure of the railway embankment at Malda, India. Acta Geotech., 2014, 9, 789–798.
- Lee, M. L., Ng, K. Y., Huang, Y. F. and Li, W. C., Rainfallinduced landslides in Hulu Kelang area, Malaysia. Nat. Hazards, 2014, 70, 353–375.
- Tan, X., Hu, N., Li, D., Shen, M. and Hou, X., Time-variant reliability analysis of unsaturated soil slopes under rainfall. Geotech. Geol. Eng., 2013, 31, 319–327.
- Zhu, H., Zhang, L. M., Zhang, L. L. and Zhou, C. B., Twodimensional probabilistic infiltration analysis with a spatially varying permeability function. Comput. Geotech., 2013, 48, 249– 259.
- Huang, F., Wang, G. S. and Tsai, Y., Rainfall reliability evaluation for stability of municipal solid waste landfills on slope. Math. Probl. Eng., 2013, 2013, 1848–1856.
- Sinosteel Maanshan Institute of Mining Research, Geotechnical Investigation Report for the Yongping Hujiashan Slope, Maanshan, Anhui, 2007.
- Fredlund, D. G. and Rahardjo, H., The role of unsaturated soil behaviour in geotechnical engineering practice. In 11th Southeast Asian Geotechnical Conference, 1993.
- Vanapalli, S. K., Fredlund, D. G., Pufahl, D. E. and Clifton, A. W., Model for the prediction of shear strength with respect to soil suction. Can. Geotech. J., 1996, 33, 379–392.
- Richards, L. A., Capillary conduction of liquids through porous mediums. Physics (College. Park. Md)., 1931, 1, 318–333.
- van Genuchten, M. T., A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J., 1980, 44, 892–898.
- China Meteorological Administration, Rainfall level; http://www.cma.gov.cn/2011xzt/2013zhuant/20130620_3/2013062002/201308/t20130816_223400.html, 2013.
- Zhu, Y., Reliability Analysis of Slope (in Chinese), Metallurgical Industry Press of China, Beijing, China, 1993.