44 research outputs found
Effective Atomic Number Dependence of Radiological Parameters of Some Organic Compounds at 122 KeV Gamma Rays
Mass attenuation coefficient is a fundamental parameter of radiation interaction, from which the other radiological parameters like half Value Layer [HVL], tenth Value Layer [TVL], total atomic and electronic cross-sections, mass energy absorption coefficient, KERMA, CT number and effective atomic number are deduced. These parameters are extensively required in a number of fields such as diagnostic radiology, gamma ray spectroscopy, fluorescence analysis and reactor shielding. In the present work, mass attenuation coefficients are determined experimentally for some organic compounds at 122 keV incident photons using narrow-beam transmission geometry to establish a relation between effective atomic number (Zeff) and other deduced parameters. The experimental data for all these parameters are compared with the values deduced from WinXcom software package and are found to agree within experimental estimated errors. This study gives some insight about the photon interaction in some organic compounds whose effective atomic numbers match with some human body fluids
Effect of Yarn Type, Sett and Kind of Huck-a-back Weave on Some Characteristics of Towelling Fabrics
1-5<span style="font-size:11.0pt;line-height:115%;
font-family:" calibri","sans-serif";mso-ascii-theme-font:minor-latin;mso-fareast-font-family:="" "times="" new="" roman";mso-fareast-theme-font:minor-fareast;mso-hansi-theme-font:="" minor-latin;mso-bidi-font-family:"times="" roman";mso-ansi-language:en-us;="" mso-fareast-language:en-us;mso-bidi-language:ar-sa"="">The effect of type of weft
yarn, weft sett and kind of huck-a-back weave on water absorbance, abrasion
resistance in dry and wet states, and tensile and te.ar strengths of towelling
fabrics has been investigated. It has been observed that if the final count of
weft yarn is the same, the use of single yarn associated with lower sell leads
to a highly absorbent towelling fabric. Huck-a-back weave having relatively
longer warp floats than weft floats, using the same yarns and fabric
construction but higher ends then picks per inch, produces a fabric with
improved strength and absorbance.</span
One Time Mining by Multi-Core Preprocessing on Generalized Dataset
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. Many industries are interested in developing the association rules from their databases due to continuous retrieval and storage of huge amount of data. The discovery of interesting association relationship among business transaction records in many business decision making process such as catalog decision, cross-marketing, and loss-leader analysis. The enormity and high dimensionality of datasets typically available as input to problem of association rule discovery, and the time consuming operation in this discovery process is the computation of the frequency of interesting subset of items (called candidates) in the database of transactions. Hence, it is has become vital to develop a method that will make speedup the preprocessing computation. In this paper, We have proposed An Integrated approach of Parallel Computing and ARM for mining Association Rules in Generalized data set that is fundamentally different from all the previous algorithms in that multi-core preprocessing is done and by avoiding recurring scan of dataset number of passes required is reduced. The response time is calculated on space delimited text dataset
Markel Cell Carcinoma
Merkel cell carcinoma (MCC) is a rare but aggressive neuroendocrine tumour of the skin with high rate of local recurrence and distant metastatic potential leading to poor outcomes. Merkel cells are normally found as innervated clusters of cells around hair follicles in the basal layer of the epidermis and are thought to function as touch receptors. Here, we describe a case of MCC in a 71-year-old female and provide an up-to-date review of the literature pertinent to the management of MCC.
KEYWORDS: merkell cell carcinoma, diagnosis, imunohistochemistry, management