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Type II A Procollagen is Deposited in the Extracellular Matrix in Osteoarthritic Cartilage and Can be Used as Marker of Osteoarthritis
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“Are all beliefs equal?” investigating the nature and determinants of parental attitudinal beliefs towards educational inclusion
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융복합 문화로서 재조대장경과 판각지 남해의 문화콘텐츠 개발
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근대 지명 지료에 나타난 기장군 행정 지명 변천 연구
- 검색키워드
- 저자 : S. M. H. Ghotbi (검색결과 2 건)
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<i>Spitzer</i> Observations of the North Ecliptic Pole
Nayyeri, H.,Ghotbi, N.,Cooray, A.,Bock, J.,Clements, D. L.,Im, M.,Kim, M. G.,Korngut, P.,Lanz, A.,Lee, H. M.,Lee, D. H.,Malkan, M.,Matsuhara, H.,Matsumoto, T.,Matsuura, S.,Nam, U. W.,Pearson, C.,Serje American Astronomical Society 2018 The Astrophysical journal Supplement series Vol.234 No.2
<P>We present a photometric catalog for Spitzer Space Telescope warm mission observations of the North Ecliptic Pole (NEP; centered at R.A. = 18(h)00(m)00(s), decl. = 66(d)33(m)38(s).552). The observations are conducted with IRAC in the 3.6 and 4.5 mu m bands over an area of 7.04 deg(2), reaching 1 sigma depths of 1.29 mu Jy and 0.79 mu Jy in the 3.6 mu m and 4.5 mu m bands, respectively. The photometric catalog contains 380,858 sources with 3.6 and 4.5 mu m band photometry over the full-depth NEP mosaic. Point-source completeness simulations show that the catalog is 80% complete down to 19.7 AB. The accompanying catalog can be used for constraining the physical properties of extragalactic objects, studying the AGN population, measuring the infrared colors of stellar objects, and studying the extragalactic infrared background light.</P>
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Prediction of Scour in Plunge Pools below Outlet Bucket Using Artificial Intelligence
B. Lashkar-Ara,S. M. H. Ghotbi,L. Najafi 대한토목학회 2016 KSCE JOURNAL OF CIVIL ENGINEERING Vol.20 No.7
Accurate prediction of sediment scour hole dimensions downstream of hydraulic structures, e.g. the outlet bucket, is a complex and not straight forward engineering problem encountered worldwide. Dimensions of a scour hole are usually determined by empirical equations which their validation is limited by experimental conditions. As constructing physical models has its own difficulty, determining of scour hole parameters has been applied in this paper for a collection of previous experimental studies. Two artificial intelligence techniques (ANN & ANFIS) are used and the results are compared with empirical equation for maximum scour holes using nonlinear regression method. Artificial Neural Network (ANN) simply represents interconnection of neurons, each of which carries out the task of combining the input, determining its strength by comparing the combination and finding out the result. On the other hand, ANFIS is a hybrid scheme which uses the learning capability of the ANN to derive the fuzzy rules with membership functions. The results showed that maximum error caused by applying ANFIS techniques in estimating scour hole dimensions was 5.2 percent while the error in neural network model was 10.38 percent. The significance of different parameters was discussed and a simple, innovative formula was proposed. This formula is an interesting tool for the engineering community due to its preferences for estimating the parameters of complex phenomena like erosion procedures. It has been established that scour estimations could be improved if soft computation is used in place of the traditional formulae.
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