1,028 research outputs found
NON-PARAMETRIC REGRESSION ESTIMATION FOR DATA WITH EQUAL VALUES
Parametric regression analysis depends on some assumptions. One of the most important of assumption is that the type of relationship between dependent and independent variable or variables is known. Under such circumstances, in order to make better assumptions, regression methods which enable flexibility in the linearity assumption of the parametric regression are needed. These methods are nonparametric methods known as semi parametric regression methods. Estimation of parameters in a parametric regression which has independent variables of different values has been studied extensively in literature. Sometimes, one or more observation series of independent variable values can be equal while dependent variable values are different. This study offers a new method for the estimation of regression parameters under such data. Proposed method and other nonparametric methods such as Theil, Mood-Brown, Hodges- Lehmann methods and OLS method were compared with the sample data and the results were evaluated
Coordinated inventory replenishment and outsourced transportation operatoins
Cataloged from PDF version of article.We consider a one-warehouse N retailers supply chain with stochastic demand. Inventory is managed in-house whereas transportation is outsourced to a 3PL provider. We develop analytical expressions for the operating characteristics under both periodic and continuous joint replenishment policies. We identify the settings where a periodic review policy is comparable to a continuous review one. In our numerical test-bed, the periodic policy performed best in larger supply chains operating with larger trucks. We also observed that if the excess utilization charge is less than 25%, outsourcing becomes beneficial even if outsourcing cost is 25% more than the in-house fleet costs
The effects of different warm stratification periods on the seed germination of some Rosa taxa
In this study, the effects of different warm stratification periods on the seed germination of some Rosa species such as Rosa heckellana ssp. vanheurckiana, Rosa canina, Rosa pulverelanta and Rosa dumalis naturally grown in the Van region were investigated. In 2007, seeds of these species were kept at 25°C warm stratification for 10, 11 and 12 weeks, and then transferred to 5°C for cold stratification till the initiation of germination. Germination response to treatments of R. heckellana ssp. vanheurckiana seeds was different compared to the other species. The seeds of R. heckellana ssp. vanheurckiana germinated in a short time (when they kept in warm stratification followed by cold stratification between 1 - 3 weeks). The seeds of the other species required 5 months of cold stratification after warm stratification to overcome seed dormancy. The overall germination percentage were 18.80% in R. canina, 13.80% in R. pulverelanta and 13.53% in R. dumalis at 25°C of warm stratification followed by 5°C cold stratification. We determined that for these three taxa, the most appropriate method of stratification was 11 week warm stratification followed by cold stratification
Reentrant valence transition in EuO at high pressures: beyond the bond-valence model
The pressure-dependent relation between Eu valence and lattice structure in
model compound EuO is studied with synchrotron-based x-ray spectroscopic and
diffraction techniques. Contrary to expectation, a 7% volume collapse at
45 GPa is accompanied by a reentrant Eu valence transition into a
\emph{lower} valence state. In addition to highlighting the need for probing
both structure and electronic states directly when valence information is
sought in mixed-valent systems, the results also show that widely used
bond-valence methods fail to quantitatively describe the complex electronic
valence behavior of EuO under pressure.Comment: 5 pages, 4 figure
Effects of dietary probiotic and prebiotic supplementation on growth performance and serum IgG concentration of broilers
This study was conducted to investigate the effects of probiotic and/or prebiotic supplementation on growth performance and serum IgG concentrations in broilers. One thousand two hundred one-day old Ross-308 broiler chicks of mixed sex were randomly divided into four treatment groups of 300 birds each. The treatments were: Starter diets: 1) Unsupplemented control diet; 2) Probiotic (Bio-Plus 2B® 0.05%); 3) Prebiotic (Bio-Mos® 0.2%); 4) Probiotic and Prebiotic mixture (Bio-Plus 2B® 0.05% and Bio-Mos® 0.2%). The grower diets were: 1) Control with no supplements; 2) Probiotic (Bio-Plus 2B® 0.05%); 3) Prebiotic (Bio-Mos® 0.1%); 4) Probiotic and Prebiotic mixture (Bio-Plus 2B® 0.05% and Bio-Mos® 0.1%). Each treatment group was further sub-divided into five replicates of 60 birds per replicate. The chicks were fed the broiler starter diet for the first 21 d and the broiler grower diet between days 22 and 42. Dietary probiotic and/or prebiotic supplementation did not significantly affect body weight, body weight gain, feed intake, carcass weight, carcass yield or concentration of immunoglobulin (IgG) in the serum. However, feed conversion ratio was improved significantly in the supplemented treatments compared to the unsupplemented control. Probiotic and/or prebiotic supplementation did not significantly affect any of the examined parameters except for an improved feed conversion ratio. Keywords: Probiotic, prebiotic, broilers, performanceSouth African Journal of Animal Science Vol. 38 (1) 2008: pp. 21-2
A general moment NRIXS approach to the determination of equilibrium Fe isotopic fractionation factors: application to goethite and jarosite
We measured the reduced partition function ratios for iron isotopes in
goethite FeO(OH), potassium-jarosite KFe3(SO4)2(OH)6, and hydronium-jarosite
(H3O)Fe3(SO4)2(OH)6, by Nuclear Resonant Inelastic X-Ray Scattering (NRIXS,
also known as Nuclear Resonance Vibrational Spectroscopy -NRVS- or Nuclear
Inelastic Scattering -NIS) at the Advanced Photon Source. These measurements
were made on synthetic minerals enriched in 57Fe. A new method (i.e., the
general moment approach) is presented to calculate {\beta}-factors from the
moments of the NRIXS spectrum S(E). The first term in the moment expansion
controls iron isotopic fractionation at high temperature and corresponds to the
mean force constant of the iron bonds, a quantity that is readily measured and
often reported in NRIXS studies.Comment: 38 pages, 2 tables, 8 figures. In press at Geochimica et Cosmochimica
Acta. Appendix C contains new derivations relating the moments of the iron
PDOS to the moments of the excitation probability function measured in
Nuclear Resonant Inelastic X-ray Scatterin
Quantum Algorithms for Learning and Testing Juntas
In this article we develop quantum algorithms for learning and testing
juntas, i.e. Boolean functions which depend only on an unknown set of k out of
n input variables. Our aim is to develop efficient algorithms:
- whose sample complexity has no dependence on n, the dimension of the domain
the Boolean functions are defined over;
- with no access to any classical or quantum membership ("black-box")
queries. Instead, our algorithms use only classical examples generated
uniformly at random and fixed quantum superpositions of such classical
examples;
- which require only a few quantum examples but possibly many classical
random examples (which are considered quite "cheap" relative to quantum
examples).
Our quantum algorithms are based on a subroutine FS which enables sampling
according to the Fourier spectrum of f; the FS subroutine was used in earlier
work of Bshouty and Jackson on quantum learning. Our results are as follows:
- We give an algorithm for testing k-juntas to accuracy that uses
quantum examples. This improves on the number of examples used
by the best known classical algorithm.
- We establish the following lower bound: any FS-based k-junta testing
algorithm requires queries.
- We give an algorithm for learning -juntas to accuracy that
uses quantum examples and
random examples. We show that this learning algorithms is close to optimal by
giving a related lower bound.Comment: 15 pages, 1 figure. Uses synttree package. To appear in Quantum
Information Processin
Forecasting of Turkey inflation with hybrid of feed forward and recurrent artifical neural networks
Enflasyon öngörülerinin elde edilmesi önemli bir ekonomik problemdir. Öngörülerin doğru bir şekilde elde edilmesi daha doğru kararlara neden olacaktır. Enflasyon öngörüsü için literatürde çeşitli zaman serileri teknikleri kullanılmıştır. Son yıllarda zaman serisi öngörü probleminde esnek modelleme yeteneği nedeniyle, Yapay Sinir Ağları (YSA) tercih edilmektedir. Yapay sinir ağları doğrusal veya eğrisel belirli bir model kalıbı, durağanlık ve normal dağılım gibi ön koşullara ihtiyaç duymadığından herhangi bir zaman serisine kolaylıkla uygulanabilmektedir. Bu çalışmada Tüketici Fiyat Endeksi (TUFE) için ileri ve geri beslemeli yapay sinir ağları yaklaşımı kullanılarak öngörüler elde edilmiştir. Çözümlemede kullanılan YSA modellerinin öngörülerinin girdi olarak kullanıldığı, YSA’ya dayalı yeni bir melez yaklaşım önerilmiştir.Obtaining the inflation prediction is an important problem. Having this prediction accurately will lead to more accurate decisions. Various time series techniques have been used in the literature for inflation prediction. Recently, Artificial Neural Network (ANN) is being preferred in the time series prediction problem due to its flexible modeling capacity. Artificial neural network can be applied easily to any time series since it does not require prior conditions such as a linear or curved specific model pattern, stationary and normal distribution. In this study, the predictions have been obtained using the feed forward and recurrent artificial neural network for the Consumer Price Index (CPI). A new combined forecast has been proposed based on ANN in which the ANN model predictions employed in analysis were used as data
Influence of Magnetism on Phonons in CaFe2As2 Via Inelastic X-ray Scattering
In the iron pnictides, the strong sensitivity of the iron magnetic moment to
the arsenic position suggests a significant relationship between phonons and
magnetism. We measured the phonon dispersion of several branches in the high
temperature tetragonal phase of CaFe2As2 using inelastic x-ray scattering on
single-crystal samples. These measurements were compared to ab initio
calculations of the phonons. Spin polarized calculations imposing the
antiferromagnetic order present in the low temperature orthorhombic phase
dramatically improve agreement between theory and experiment. This is discussed
in terms of the strong antiferromagnetic correlations that are known to persist
in the tetragonal phase.Comment: 4 pages, 3 figures; added additional information and references about
spin fluctuation
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