Search Results

1 - 10 of 39 items :

  • "source identification" x
Clear All

:// Sinopoli, B., Sharp, C., Schenato, L., Schaffert, S. and Sastry, S. S. (2003). Distributed control applications within sensor networks, Proceedings of the IEEE   91 (8): 1235-1246. Sivergina, I. F. and Polis, M. P. (2002). Comments on "Model-based solution techniques for the source localization problem", IEEE Transactions on Control Systems Technology   10 (4): 633-633. Sivergina, I. F., Polis, M. P. and Kolmanovsky, I. (2003). Source identification for parabolic equations, Mathematics of Control, Signals, and Systems   16 : 141-157. Song, Z., Chen, Y., Sastry, C. R

. Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008. 23. Begun, B. A., Hopke, P. K., & Zhao, W. (2005). Source identification of fine particles in Washington, DC, by expanded factor analysis modelling. Environ. Sci. Technol ., 39 , 1129–1137. DOI: 10.1021/es049804v. 24. Samek, L., Zwozdziak, A., & Sowka, I. (2013). Chemical characterization and source identification of particulate matter PM10 in a rural and urban site in Poland. EPE , 39 , 91–103. DOI: 10.5277/epe130408. 25. Lammel, G., Rohrl, A., & Schreiber, H. (2002). Atmospheric lead

.gexplo.2007.05.001. Matschullat, J., Ottenstein, R., & Reimann, C. (2000). Geochemical background - can we calculate it? Environmental Geology, 39 , 990-1000. DOI: 0.1007/s002549900084. Mudge, S. M. (2008). Environmental forensics and the importance of source identification. In: R. E. Hester & R. M. Harrison. (Eds.) Environmental Forensics (pp. 1-16). Cambridge: Royal Society of Chemistry. Müller, G. (1969). Index of geoaccumulation in sediments of the Rhine River. Geojournal, 2 , 108-118. Norrström, A. C. (2005). Metal mobility by de-icing salt from an infiltration


An expert system aided method of the blade-tip signal decomposition to the turbine blade vibration sources identification is presented. The method utilises a multi-valued diagnostic model based on the discrete wavelet transform. Proposed algorithm consists of four stages: signal decomposition into low- and high-frequency components (approximations and details), approximations and details parameterization, multi-valued encoding of parameters obtained at the second stage, an expert system use of the turbine blade vibration sources identification.


This study illustrates the benefits of statistical techniques to analyze spatial and temporal variations in water quality. In this scope water quality differentiation caused by anthropogenic and natural factors in the Tahtali and Balçova reservoirs in western Turkey was investigated using discriminant analysis-DA, Mann Whitney U techniques. Effectiveness of pollution prevention measures was analyzed by Mann Kendall and Sen’s Slope estimator methods. The water quality variables were divided into three groups as physical-inorganic, organic and inorganic pollution parameters for the study. Results showed that water quality between reservoirs was differentiated for “physical-inorganic” and “organic pollution” parameters. Degree of influence of water quality by urbanization was higher in the Tahtali reservoir and in general, no trend detection at pollution indicators explained by effective management practices at both sites.


This article elaborates on the development of a dedicated model of a tacit knowledge transformation for the service department in a manufacturing company. The four main components of the tacit knowledge transformation process are formulated: (1) tacit knowledge source identification, (2) tacit knowledge acquisition, (3) tacit knowledge determination and formalization, and (4) knowledge classification. The proposed model is illustrated by examples on the use of the methods: automatic recognition of speech, natural language processing, and automatic object recognition in the tacit knowledge transformation process in order to obtain a formalized procedure for the service department in a manufacturing company. This is followed by a discussion of the results of the research experiments.


An existence, uniqueness and continuous dependence on the data result for a source term identification problem in a semilinear functional delay differential equation in a general Banach space is established. As additional condition, it is assumed that the mean of the solution, with respect to a non-atomic Borel measure, is a preassigned element in the domain of the linear part of the right-hand side of the equation. Two applications to source identification, one in a parabolic functional delay equation and another one in a hyperbolic delay equation, are also discussed.

marine environment , Journal of the European Optical Society – Rapid Publications, Vol. 9, pp. 14029.1-14029.7, 2014. [4] Frank, U., A review of fluorescence spectroscopic method for oil spill source identification , Toxicological & Environmental Chemistry Reviews, Vol. 2, Iss. 3, pp. 163-185, 1978. [5] Meier, D., Voß, D., Zielinski, O., Heuermann, R., Horn, M., Krause, S.-E., Machulik, U., Munderloh, K., Oest, J., Spitzy, A., Development of an online detection system for determination and characterization of dissolved organic substances in water via fluorescence

): 121–124. Lefèvre, F. and Le Niliot, C.L. (2002). Multiple transient point heat sources identification in heat diffusion: Application to experimental 2D problems, Journal of Heat and Mass Transfer 45 (9): 1951–1964. Le Niliot, C. and Lefèvre, F. (2001). A method for multiple steady line heat sources identification in diffusive system: Application to an experimental 2D problem, Journal of Heat and Mass Transfer 44 (7): 1425–1438. Le Niliot, C. and Lefèvre, F. (2004). A parameter estimation approach to solve the inverse problem of point heat sources identification

aggregates. In: Journal of Hazardous Materials, 132(1 SPEC. ISS.), 2006, p. 39 - 46. [9] Wheel tracking machine DYNA-TRACK. Cernusco, Italy: Controls S.R.L., 2000. [10] LIČBINSKÝ, R. - FRÝBORT, A. - HUZLÍK, J. - ADAMEC, V. - EFFENBERGER, K. - MIKUŠKA, P. - VOJTĚŠEK, M. - KŘŮMAL, K.: Usage of Scanning Electron Microscopy for Particulate Matter Sources Identification. In: Transactions on transport sciences, Number 3/2010. Ministry of Transport, 2010, p. 137 - 144. [11] WILLIS, ROBERT D. - BLANCHARD, FREDRICK T. - CONNER, TERI L.: Guidelines for the Application of SEM