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 $\approx$ 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 $\epsilon$ that uses $O(k/\epsilon)$ 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 $\Omega(\sqrt{k})$ queries. - We give an algorithm for learning $k$-juntas to accuracy $\epsilon$ that uses $O(\epsilon^{-1} k\log k)$ quantum examples and $O(2^k \log(1/\epsilon))$ 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