Hierarchical Order Statistics Filtering for Fast Bi‐Dimensional Empirical Mode Decomposition

A hierarchical approach for fast bi‐dimensional empirical mode decomposition (B‐EMD) is proposed. The presented approach utilizes an efficient window size determination scheme that enables the multi‐level computation of the order statistics filter (OSF). Our detailed experiments show that the proposed OSF computation approach allows a significantly faster computation of an EMD without degrading the decomposition accuracy.     

Improving Interoperability by Incorporating UnitsML Into Markup Languages

Maintaining the integrity of analytical data over time is a challenge. Years ago, data were recorded on paper that was pasted directly into a laboratory notebook. The digital age has made maintaining the integrity of data harder. Nowadays, digitized analytical data are often separated from information about how the sample was collected and prepared for analysis and how the data were acquired. The data are stored on digital media, while the related information about the data may be written in a paper notebook or stored separately in other digital files. Sometimes the connection between this “scientific meta-data” and the analytical data is lost, rendering the spectrum or chromatogram useless. We have been working with ASTM Subcommittee E13.15 on Analytical Data to create the Analytical Information Markup Language or AnIML—a new way to interchange and store spectroscopy and chromatography data based on XML (Extensible Markup Language). XML is a language for describing what data are by enclosing them in computer-useable tags. Recording the units associated with the analytical data and metadata is an essential issue for any data representation scheme that must be addressed by all domain-specific markup languages. As scientific markup languages proliferate, it is very desirable to have a single scheme for handling units to facilitate moving information between different data domains.At NIST, we have been developing a general markup language just for units that we call UnitsML. This presentation will describe how UnitsML is used and how it is being incorporated into AnIML.     

A study of indoor radon levels in rural dwellings of Ezine (Canakkale, Turkey) using solid-state nuclear track detectors

Indoor radon activity level and radon effective dose (ED) rate have been carried out in the rural dwellings of Ezine (Canakkale) during the summer season using Radosys-2000, a complete set suitable to radon concentration measurements with CR-39 plastic alpha track detectors. The range of radon concentration varied between 9 and 300 Bq m(-3), with an average of 67.9 (39.9 SD) Bq m(-3). Assuming an indoor occupancy factor of 0.8 and 0.4 for the equilibrium factor of radon indoors, it has been found that the 222Rn ED rate in the dwellings studied ranges from 0.4 to 5.2 mSv y(-1), with an average value of 1.7 (1.0) mSv y(-1). There is a possibility that low radon concentrations exist indoors during the summer season in the study area because of relatively high ventilation rates in the dwellings. A winter survey will be needed for future estimation of the annual ED.     

Microstructural characterization of corn starch‐based porous thermoplastic composites filled with multiwalled carbon nanotubes

Microstructural characterization of corn starch‐based porous thermoplastic (TPS) composites containing various contents (0.1, 0.5, and 1 wt %) of multiwalled carbon nanotubes (MWCNTs) was performed. Corn starch was plasticized with a proper combination of glycerol and stearic acid. TPS composites with MWCNT were prepared conducting melt extrusion followed by injection molding. TPS containing 1 wt % of MWCNTs exhibited higher tensile strength and elastic modulus values than neat TPS. Moreover, TPS electrical conductivity was determined to increase with increasing content of MWCNTs. X‐ray diffraction measurements revealed that incorporation of MWCNTs increased the degree of TPS crsystallinity to some extent. Scanning electron microscopy examination revealed that MWCNT altered TPS surface morphology and tensile failure modes, significantly. Transmission electron microscopy investigation showed that dispersion characteristics of MWCNTs within TPS were in the form of tiny clusters around micro pores of TPS, which is considered influential on electrical conductivity of the resulting composites. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Effect of ZnO type and concentration on the mophology,thermal, and mechanical properties of poly(ether ester)/ZnO composites

Poly(ether ester) (PEE) copolymers were synthesized in a two‐stage process involving transesterification and polycondensation. The synthesized copolymer and the zinc oxide (ZnO) were used in composite preparation by melt compounding. The influence of ZnO type and concentration on the morphology, thermal and mechanical properties of the composites were studied. DSC and XRD analyses indicated that crystallinity of composites was slightly reduced with ZnO content. Homogeneous dispersion of fillers in the polymer matrix was observed through morphological analyses. While in general tensile strength and elongation at break values of the composites decreased with increasing ZnO content, elastic modulus values increased with the addition of ZnO. Moreover, ZnO particles were modified with poly(N‐vinyl pyrrolidone) and a slight improvement in mechanical properties was observed, respectively over the composites containing unmodified particles. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

A comparative study of efficient initialization methods for the k-means clustering algorithm

K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. In this paper, we first present an overview of these methods with an emphasis on their computational efficiency. We then compare eight commonly used linear time complexity initialization methods on a large and diverse collection of data sets using various performance criteria. Finally, we analyze the experimental results using non-parametric statistical tests and provide recommendations for practitioners. We demonstrate that popular initialization methods often perform poorly and that there are in fact strong alternatives to these methods.     

Analysis of input-output clustering for determining centers of RBFN

The key point in design of radial basis function networks is to specify the number and the locations of the centers. Several heuristic hybrid learning methods, which apply a clustering algorithm for locating the centers and subsequently a linear least-squares method for the linear weights, have been previously suggested. These hybrid methods can be put into two groups, which will be called as input clustering (IC) and input-output clustering (IOC), depending on whether the output vector is also involved in the clustering process. The idea of concatenating the output vector to the input vector in the clustering process has independently been proposed by several papers in the literature although none of them presented a theoretical analysis on such procedures, but rather demonstrated their effectiveness in several applications. The main contribution of this paper is to present an approach for investigating the relationship between clustering process on input-output training samples and the mean squared output error in the context of a radial basis function network (RBFN). We may summarize our investigations in that matter as follows: (1) A weighted mean squared input-output quantization error, which is to be minimized by IOC, yields an upper bound to the mean squared output error. (2) This upper bound and consequently the output error can be made arbitrarily small (zero in the limit case) by decreasing the quantization error which can be accomplished through increasing the number of hidden units.     

Determination of radon concentrations of the Dikili geothermal area in western Turkey

For this study, a geothermal area around Izmir-Dikili, located in the western part of Turkey, was chosen as a measuring site and the radon concentrations of environmental samples were determined. Indoor radon monitoring was performed for 3 months in dwellings located in different part of the region using passive CR-39 nuclear track detectors. The radon concentrations of water samples drawn from wells, municipal supplies, village fountains and spas in the area were measured using a liquid scintillation detector (Packard Tri-Carb 2770 TR/SL, A-277001). Soil samples collected from each location were analysed and (226)Ra concentrations were determined using a gamma ray spectrometer connected to an HPGe detector. Annual effective doses from radon inhalation and ingestion were calculated.     

Radon measurements in the Catalagzi Thermal Power Plant, Turkey

The Catala?zi Thermal Power Plant (CTPP) (41(0)30'48.4(')N and 0.31(0)53'41.5(')E) is located at nearly 13 km North-east of Zonguldak city, which is located at the West Black Sea coast in Turkey. The middling products with high ash content of bituminous coals are used in this plant. Seasonal radon concentration measurements have been carried out by using CR-39 plastic track detectors in and around the CTPP. The annual average radon concentration has been found to vary from a minimum of 39.8 +/- 28.9 Bq m(-3) in the ash area to a maximum of approximately 75.0 +/- 15.7 Bq m(-3) in the service building of the power plant. The annual average radon concentration in the dwellings of the thermal power plant colony of the plant is 71.0 +/- 33.4 Bq m(-3). The effective dose has been found to vary from 0.38 to 0.71 mSv y(-1) with a mean value of 0.56 mSv y(-1), which is lower than the effective dose values 3-10 mSv given as the range of action levels recommended by International Commission on Radiological Protection: Protection against radon-222 at home and at work, ICRP Publication 65 (1993).