A multi-stage financial hedging approach for the procurement of manufacturing materials

This paper addresses the problem of mitigating procurement risk that arises from volatile commodity prices by proposing a hedging strategy within a multi-stage time frame. The proposed multi-stage hedging strategy requires a commodity futures position to be correctly initialised and rebalanced with adequate volumes of short/long positions, so as to reduce the volatility in the total procurement cost that would otherwise be generated by varying commodity spot prices. The novelty in the approach is the introduction of the rebalancing of commodity futures position at defined intermediate stages. To obtain an efficient or near optimal multi-stage hedging strategy, a discrete-time stochastic control model (DSCM) is developed. Numerical experiments and Monte Carlo simulation are used to show that the proposed multi-stage hedging strategy compares favourably with the minimal-variance hedge and the one-stage hedge. A close-form optimal solution is also presented for the case when procurement volume and price are independent.     

Medical image segmentation based on non-parametric mixture models with spatial information

Because of too much dependence on prior assumptions, parametric estimation methods using finite mixture models are sensitive to noise in image segmentation. In this study, we developed a new medical image segmentation method based on non-parametric mixture models with spatial information. First, we designed the non-parametric image mixture models based on the cosine orthogonal sequence and defined the spatial information functions to obtain the spatial neighborhood information. Second, we calculated the orthogonal polynomial coefficients and the mixing ratio of the models using expectation-maximization (EM) algorithm, to classify the images by Bayesian Principle. This method can effectively overcome the problem of model mismatch, restrain noise, and keep the edge property well. In comparison with other methods, our method appears to have a better performance in the segmentation of simulated brain images and computed tomography (CT) images.     

Improved λ/4 phase-shifted DFB semiconductor laser with spatial hole burning compensation using grating chirp

A λ/4 phase-shifted distributed feedback (DFB) semiconductor laser with a preformed chirped grating used to compensate the spatial hole burning (SHB) induced index change is proposed and analyzed. It shows that compared with the three phase shifted DFB laser which is known for its good performance to eliminate SHB, the proposed SHB compensated laser has better single longitudinal mode property, narrower spectral linewidth and better dynamic characteristics.     

Reactions of aldehyde with collagen: a DFT study

Structural Chemistry - The reaction mechanisms of several amino acids (Asn, Gln, Arg, His, and Lys) in the collagen with aldehyde were studied using density functional theory method. Based on the...     

Tunable multichannel drop filters based on the two-dimensional photonic crystal with oval defects

Light propagation through the channel filter based on the two-dimensional photonic crystals with oval-rod defects is studied by the finite-difference time-domain method. In addition to the traditional size tuning, shape alteration of the defects from the usual circle to the ellipse offers a powerful approach to tune the resonant frequency of channel-drop filters based on two-dimensional photonic crystals. It is found that the resonant frequency can be flexibly adjusted only by changing the orientation angle of the oval defects. The sensitivity of the resonant frequency to the alteration of the oval rods’ rotation angle is systematically studied. Because the rotation angles of the ellipse can be continuously adjusted, so the channel drop filter based on this kind of defects with different rotation angles is more suitable to the occasion where a large number of output channel filters is need.