130,521 research outputs found
R&D ERL: Beam dynamics, parameters, and physics to be learned
No full textThe R&D ERL facility at BNL aims to demonstrate CW operation of ERL with average beam current in the range of 0.1-1 ampere, combined with very high efficiency of energy recovery. The ERL is being installed in one of the spacious bays in Bldg. 912 of the RHIC/AGS complex (Fig. 1). The bay is equipped with an overhead crane. The facility has a control room, two service rooms and a shielded ERL cave. The control room is located outside of the bay in a separate building. The single story house is used for a high voltage power supply for 1 MW klystron. The two-story unit houses a laser room, the CW 1 MW klystron with its accessories, most of the power supplies and electronics. The ERL R&D program has been started by the Collider Accelerator Department (C-AD) at BNL as an important stepping-stone for 10-fold increase of the luminosity of the Relativistic Heavy Ion Collider (RHIC) using relativistic electron cooling of gold ion beams with energy of 100 GeV per nucleon. Furthermore, the ERL R&D program extends toward a possibility of using 10-20 GeV ERL for future electron-hadron/heavy ion collider, MeRHIC/eRHIC. These projects are the driving force behind the development of ampere-class ERL technology, which will find many applications including light sources and FELs. The intensive R&D program geared towards the construction of the prototype ERL is under way: from development of high efficiency photo-cathodes to the development of new merging system compatible with emittance compensation
Estimation of 2-D ARMA model parameters by using EAR model approach
No full textBu çalışmada, çeyrek-düzlem destek bölgesine sahip doğrusal zamanla değişmeyen durağan iki-boyutlu özbağlanımlı kayan ortalamalı (2-B ARMA) modelin parametrelerinin kestirim problemi ele alınmakta ve bu problemin çözümü için, 2-B ARMA model parametreleri ile bu modele eşdeğer sonsuz mertebeden iki-boyutlu özbağlanımlı (2-B EAR) modelin parametreleri arasındaki ilişki incelenmektedir. Bu ilişkiyi esas alarak sonlu mertebeden EAR modelin katsayılarından (p1, p2, q1, q2). mertebeden 2-B ARMA modelin parametrelerini kestirmek amacıyla; doğrusal denklem takımlarının çözümüyle parametre kestirimlerini gerçekleştiren, yakınsama sorunu olmayan, hesapsal karmaşıklığı düşük yeni bir yöntem önerilmektedir. Önerilen bu yöntem, üç aşamalı olup; birinci aşamada, (p1, p2, q1, q2). mertebeden 2-B ARMA modeli yaklaşık olarak temsil eden (L1, L2).mertebeden 2-B EAR modelin parametreleri değiştirilmiş Yule-Walker denklemleri olarak adlandırılan doğrusal denklem takımlarının çözümüyle elde edilmektedir. İkinci aşamada ise, birinci aşamada elde edilen EAR model katsayılarını önerilen yöntem ile türetilen eşitliklerde kullanarak 2-B ARMA modelin kayan ortalamalı (MA) parametrelerinin kestirimi gerçekleştirilmektedir. Son olarak, birinci ve ikinci aşamalarda hesaplanan EAR ve MA parametre kestirimlerini türetilen doğrusal denklem ifadesinde yerine koyarak 2-B ARMA modelin özbağlanımlı (AR) kısmını tanımlayan katsayıların hesabı yapılmaktadır. Önerilen yöntemin başarımı, bilgisayar benzetimleri sınanmıştır. Bu amaçla, önerilen yöntemin literatürdeki yöntem ile eşzamanlı çalıştırılması sonucunda üretilen parametre kestirimleri ve bu parametrelere karşı düşen güç izge yoğunluk kestirimleri çeşitli başarım ölçütlerine göre karşılaştırılmıştır. Sonuç olarak, önerilen yöntemle oldukça iyi ve tatmin edici sonuçlara ulaşıldığı gözlenmiştir. Anahtar Kelimeler: 2-B ARMA model, 2-B EAR model, parametre kestirimi, çeyrek-düzlem destek bölgesi. This paper considers the parameter estimation problem of a quarter-plane (QP) linear time-invariant (LTI) two-dimensional autoregressive moving average (2-D ARMA) model excited by an unknown zero-mean white Gaussian noise with variance w2. Since the use of nonparametric methods such as Fast Fourier Transform (FFT) yield low-resolution results, 2-D system identification and parametric representations of 2-D stationary random fields based on parametric 2-D autoregressive (AR), moving average (MA), and ARMA models have received great attention in a wide range of image and signal processing applications. These applications include image restoration, image compression, stochastic texture analysis and synthesis, modeling, and high-resolution spectrum estimation of 2-D data, etc. Note that AR and MA models correspond to the special case of ARMA models. The most general models used in modeling the random fields are the ARMA models. In modeling of 2-D random fields, AR models have been used extensively since their parameters are estimated easily by solving the set of linear equations called as Modified Yule-Walker (MYW) equations. However, as in the one-dimensional case, the parameter estimation procedures for the MA and ARMA models are much more difficult than the AR models since these procedures require a heavy computational burden and there are convergence problems. All of these reasons and intrinsic nonlinearity of estimating the MA parameters cause restriction on making studies based upon MA and ARMA models. In spite of these difficulties, ARMA models are preferred frequently because of their relations with the linear filters having rational transfer function and their abilities on simulating the behavior similar to the noise correctly. From the parameter parsimony point of view, 2-D ARMA models usually provide the most effective linear models of the 2-D homogeneous random fields and are therefore preferable over its AR or MA counterparts: as compared to the AR and MA models, ARMA models can perform more accurate modeling with a few number of parameters. From the spectral estimation viewpoint, while the ARMA models can characterize both the peaks and the valleys, the AR and MA models can characterize only the peaks and the valleys, respectively. In spite of its advantages, there are a few methods in the literature related to the parameter and spectral estimation of 2-D ARMA models. For the aim of modeling 2-D random fields, the existing 2-D ARMA model-based estimation methods can be classified into two main groups. In the first group of methods, AR and MA parameters of the ARMA model are estimated explicitly from the given data set or its second-order statistics. Thus, the given data set is characterized by either the transfer function of the ARMA model or its power spectral density (PSD) function obtained using the estimated AR and MA parameters. In the second group of methods, the estimation processes are realized on the basis of the PSD function of the ARMA model. AR parameters are estimated explicitly from the given data record or its statistics, and then the MA spectrum parameters are calculated using the estimated AR parameters and the second-order statistics of the data set. Hence, the observation data are characterized by the ARMA model PSD function formed by the estimated AR parameters and MA spectrum parameters. Note that while the MA parameters are acquired explicitly in the first group of methods, the methods involving to the second group obtain the MA spectrum parameters rather than estimating the MA parameters explicitly. In this paper, we have introduced a simple and computationally efficient method for estimating the parameters of a LTI 2-D ARMA model having QP support region. The suggested method is based on the relation between the parameters of the 2-D ARMA model and those of the equivalent autoregressive (2-D EAR) model. On the basis of this relation, linear equations performing the ARMA model parameter estimation process from the coefficients of the EAR model are derived. The method proposed for this purpose is a three-step approach: firstly, the 2-D EAR model parameters are obtained solving the set of linear equations called as MYW equations; then, the MA parameters are estimated benefiting from the EAR model coefficients; finally, the AR parameters are calculated exploiting the estimated EAR and MA parameters in the derived formula. Performance of the proposed method is analyzed via computer simulations. We demonstrate with simulations that satisfactory results are obtained by the proposed method. Keywords: 2-D ARMA model, 2-D EAR model, parameter estimation, quarter-plane support region
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Two-dimensional ARMA parameter identification with two-channel AR lattice approach
No full textİki-boyutlu zamanla değişmeyen bir ARMA(M,N) sistemin parametrelerini tanılamak için yeni bir yöntem önerilmiştir. Burada M, AR kısmının derecesini, N ise MA kısmının derecesini temsil etmektedir. Bu yeni yöntem, önceden önerilen iki-kanallı AR kafes modelleme yaklaşımının, AR ve MA derecelerinin farklı olduğu durumları da içerecek şekilde genişletilmiş bir şeklidir. Yeni önerilen yöntem, hem iki-kanallı, hem de tek-kanallı kafes yapılarını barındırması nedeni ile bir “karma kafes yapısı” olarak da adlandırılabilir. Bu karma kafes yapısı, hem çeyrek düzlem, hem de simetrik olmayan yarı düzlem modellerine uygulanabilmektedir. AR derecesinin MA derecesine eşit olduğu durumlarda, karma kafes yapısı ortadan kalkmakta, yalnızca iki-kanallı iki-boyutlu AR kafes yapıları ile çözüme gidilmektedir. Bu çalışma kapsamında ayrıca, ARMA parametreleri hesaplamak için, b0 parametresini ve her iki kanala ilişkin ileri yönde öngörü süzgeçlerinin katsayı ağırlıklarını da içine alan ve M ³ N, M < N durumları için kullanılabilecek yeni bir formülasyon yaklaşımı önerilmiştir. Önerilen yöntemin doğrulanması amacıyla, bilgisayar benzetimleri kullanılmıştır. Bu benzetimlerin her birinde, karşılaştırmaya esas olarak LS kestirimleri alınmıştır. Ayrıca L1, L2 ve L¥ vektör normları ile Itakura-Saito uzaklığı, başarım ölçütleri olarak kabul edilmiş ve her bir bilgisayar benzetimi için hesaplanmıştır. Elde edilen parametre tanılama sonuçları, karma kafes yönteminin, oldukça küçük veri alanı boyutları için bile kabul edilebilir nitelikte olduğunu göstermektedir.Anahtar Kelimeler: ARMA sistem tanılama, iki-kanallı AR modelleme, iki-boyutlu kafes yapıları.The field of multi-dimensional digital signal processing has become increasingly important in recent years due to a number of trends in digital signal processing. Parametric representations of two-dimensional (2-D) random fields in the form of autoregressive (AR), moving average (MA) and autoregressive moving average (ARMA) models are useful in many applications such as image synthesis, classification, spectral estimation, radar imaging, etc. There are a number of advantages and disadvantages related with AR and MA modelings. The major advantage of both models is that the solution for the model parameters involves only linear equations. In the MA models the solution is unbiased in the presence of additive noise on the system output as long as the noise and system input are uncorrelated. MA models are always stable since they are non-recursive. One of the most serious disadvantages of either AR or MA modeling is the fact that to adequately represent even simple linear systems, both methods may require a large number of parameters (a high order model). This problem arises since, from a transfer function standpoint, AR and MA models attempt to model the system using only poles or only zeros, in spite of the fact that physical systems may have both zeroes and poles. The ARMA (M, N) model is a generalization of the Mth order AR and Nth order MA models and accomplishes exactly modeling the unknown system with poles and zeroes, representing the system in rational transfer function form. Therefore this has motivated a considerable interest in the more general pole-zero (ARMA) model. The primary concern of this research is the determination of discrete time models for 2-D LSI systems from sampled observations of the system input x(k1, k2) and system output y(k1, k2), using 2-D orthogonal lattice structures, assuming that the order of the ARMA(M, N) model is known. The ARMA model order is represented by the (M, N) pair, where M represents the order of the AR polynomial and N represents the order of the MA polynomial. Here we present a "hybrid lattice" structure in order to identify the ARMA(M, N) system parameters, provided that x(k1, k2) and y(k1, k2) are given. This structure can be applied to both quarter-plane (QP) and asymmetric half plane (ASHP) models and it is based on the two-channel AR lattice approach proposed by Kayran for equal AR and MA orders. The novelties brought about by this proposed structure can be listed as follows. We extend Kayran's approach to the case where M and N can take arbitrary values different from each other. We accomplish this with the help of our proposed hybrid lattice structure where both 2-D two-channel AR and 2-D single-channel AR lattice stages are incorporated. We also propose a modification in terms of the channel inputs of the two-channel lattices. We drive the first channel input by a difference signal of u(k1, k2) = y(k1, k2)-x(k1, k2) instead of y(k1, k2), which was formerly proposed. The second channel input, which was formerly proposed as x(k1, k2), is driven by a newly defined signal t(k1, k2), which is related with the orders of the AR and MA polynomials. If M > N, t(k1, k2) is equal to x(k1, k2), if (M < N, t(k1, k2) is equal to y(k1, k2). We propose modifications in the b0 parameter estimates for the cases where (M ³ N and M < N, in accordance with our newly proposed channel inputs. We derive a new formulation for the ARMA (M,N) parameter estimates, taking into account the estimated parameter b0 and the forward prediction error filters tap weights related with both channels. In order to make a verification of the proposed method, we give computer simulation examples where we compare the hybrid lattice estimates with the LS (Least Squares) estimates. As performance measures, we use the L1, L2 and L¥ vector norms and the Itakura-Saito distance measure, which indicates the similarity between the original and identified power spectrums.Keywords: ARMA system identification, two-channel AR modeling,two-dimensional lattice structures
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
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MERGER SYSTEM OPTIMIZATION IN BNL HIGH CURRENT R&D ERL
No full textA super-conducting RF R&D Energy recovery linac (ERL) is under construction at Brookhaven National Laboratory (BNL). This ERL will be used as a test facility to study issues relevant to high-current, high-brightness beams. One of the goals is to demonstrate an electron beam with high charge per bunch ({approx}5 nC) and extremely low normalized emittance ({approx}5 mm-mrad) at an energy of 20 MeV. In contrast with operational high-brightness linear electron accelerators, all presently operating ERLs have order of magnitude larger emittances for the same charge per bunch. One reason for this emittance growth is that the merger system mixes transverse and longitudinal degrees of freedom, and consequently violates emittance compensation conditions. A merger system based on zigzag scheme resolves this problem. In this paper we discuss performance of the present design of the BNL R&D ERL injector with a zigzag merger
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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