Estimating m-regimes STAR-GARCH model using QMLE with parameter transformation

It is well known in the literature that obtaining the parameter estimates for the Smooth Transition Autoregressive-Generalized Autoregressive Conditional Heteroskedasticity (STAR-GARCH) can be problematic due to computational difficulties. Conventional optimization algorithms do not seem to perform well in locating the global optimum of the associated likelihood function. This makes Quasi-Maximum Likelihood Estimator (QMLE) difficult to obtain for STAR-GARCH models in practice. Curiously, there has been very little research investigating the cause of the numerical difficulties in obtaining the parameter estimates for STAR-GARCH using QMLE. The aim of the paper is to investigate the nature of the numerical difficulties using Monte Carlo Simulation. By examining the surface of the log-likelihood function based on simulated data, the results provide several insights into the difficulties in obtaining QMLE for STAR-GARCH models. Based on the findings, the paper also proposes a simple transformation on the parameters to alleviate these difficulties. Monte Carlo simulation results show promising signs for the proposed transform. The asymptotic and robust variance-covariance matrices of the original parameter estimates are derived as a function of the transformed parameter estimates, which greatly facilitates inferences on the original parameters.     

Convolutional Sparse Coding for High Dynamic Range Imaging

Current HDR acquisition techniques are based on either (i) fusing multibracketed, low dynamic range (LDR) images, (ii) modifying existing hardware and capturing different exposures simultaneously with multiple sensors, or (iii) reconstructing a single image with spatially‐varying pixel exposures. In this paper, we propose a novel algorithm to recover high‐quality HDRI images from a single, coded exposure. The proposed reconstruction method builds on recently‐introduced ideas of convolutional sparse coding (CSC); this paper demonstrates how to make CSC practical for HDR imaging. We demonstrate that the proposed algorithm achieves higher‐quality reconstructions than alternative methods, we evaluate optical coding schemes, analyze algorithmic parameters, and build a prototype coded HDR camera that demonstrates the utility of convolutional sparse HDRI coding with a custom hardware platform.     

Semantic-based authorization architecture for Grid

There are a few issues that still need to be covered regarding security in the Grid area. One of them is authorization where there exist good solutions to define, manage and enforce authorization policies in Grid scenarios. However, these solutions usually do not provide Grid administrators with semantic-aware components closer to the particular Grid domain and easing different administration tasks such as conflict detection or resolution. This paper defines a proposal based on Semantic Web to define, manage and enforce security policies in a Grid scenario. These policies are defined by means of semantic-aware rules which help the administrator to create higher-level definitions with more expressiveness. These rules also permit performing added-value tasks such as conflict detection and resolution, which can be of interest in medium and large scale scenarios where different administrators define the authorization rules that should be followed before accessing a resource in the Grid. The proposed solution has been also tested providing some reasonable response times in the authorization decision process.     

Experimental study of diffusion-based extraction from a cell suspension

A recently proposed application of microfluidics is the post-thaw processing of biological cells. Numerical simulations suggest that diffusion-based extraction of the cryoprotective agent dimethyl sulfoxide (DMSO) from blood cells is viable and more efficient than centrifugation, the conventional method of DMSO removal. In order to validate the theoretical model used in these simulations, a prototype was built and the flow of two parallel streams, a suspension of Jurkat cells containing DMSO and a wash stream that contained neither cells nor DMSO, was characterized experimentally. DMSO transport in a rectangular channel (depth 500 μm, width 25 mm and overall length 125 mm) was studied as a function of three dimensionless parameters: depth ratio of the streams, cell volume fraction in the cell solution, and the Peclet number (Pe) based on channel depth, average flow rate and the diffusion coefficient for DMSO in water. In our studies, values of Pe ranged from O(10³) to O(10⁴). Laminar flow was ensured by keeping the Reynolds number between O(1) and O(10). Experimental results based on visual and quantitative data demonstrate conclusively that a microfluidic device can effectively remove DMSO from liquid and cell laden streams without compromising cell recovery. Also, flow conditions in the microfluidic device appear to have no adverse effect on cell viability at the outlet. Further, the results demonstrate that we can predict the amount of DMSO removed from a given device with the theoretical model mentioned previously.     

QuadCover - Surface Parameterization using Branched Coverings

We introduce an algorithm for the automatic computation of global parameterizations on arbitrary simplicial 2-manifolds, whose parameter lines are guided by a given frame field, for example, by principal curvature frames. The parameter lines are globally continuous and allow a remeshing of the surface into quadrilaterals. The algorithm converts a given frame field into a single vector field on a branched covering of the 2-manifold and generates an integrable vector field by a Hodge decomposition on the covering space. Except for an optional smoothing and alignment of the initial frame field, the algorithm is fully automatic and generates high quality quadrilateral meshes.     

A method to align the coordinate system of accelerometers to the axes of a human body: The depitch algorithm

One of the key problems in accelerometry based gait analyses is that it may not be possible to attach an accelerometer to the lower trunk so that its axes are perfectly aligned to the axes of the subject. In this paper we will present an algorithm that was designed to virtually align the axes of the accelerometer to the axes of the subject during walking sections. This algorithm is based on a physically reasonable approach and built for measurements in unsupervised settings, where the test persons are applying the sensors by themselves. For evaluation purposes we conducted a study with 6 healthy subjects and measured their gait with a manually aligned and a skewed accelerometer attached to the subject's lower trunk. After applying the algorithm the intra-axis correlation of both sensors was on average 0.89±0.1 with a mean absolute error of 0.05g. We concluded that the algorithm was able to adjust the skewed sensor node virtually to the coordinate system of the subject.     

Prediction of parking space availability in real time

Intelligent parking reservation (IPR) systems allow customers to select a parking facility according to their preferences, rapidly park their vehicle without searching for a free stall, and pay their reservation in advance avoiding queues. Some IPR systems interact with in-vehicle navigation systems and provide users with information in real time such as capacity, parking fee, and current parking utilization. However, few of these systems provide information on the forecast utilization at specific hours - a process that requires the study of the competition between parking alternatives for the market share. This paper proposes a methodology for predicting real-time parking space availability in IPR architectures. This methodology consists of three subroutines to allocate simulated parking requests, estimate future departures, and forecast parking availability. Parking requests are allocated iteratively using an aggregated approach as a function of simulated drivers’ preferences, and parking availability. This approach is based on a calibrated discrete choice model for selecting parking alternatives. A numerical comparison between a one-by-one simulation-based forecast and the proposed aggregated approach indicates that no significant discrepancies exists, validating and suggesting the use of the less time consuming proposed aggregated methodology. Results obtained from contrasting predictions with real data yielded small average error availabilities. The forecast improves as the system registers arrivals and departures. Thus, the forecast is adequate for potential distribution in real-time using different media such as Internet, navigation systems, cell phones or GIS.     

考虑周期特性的电力市场稳定性分析

研究了电力市场的稳定性问题。并根据电力市场的物理特性，在模型中考虑了电能供需的同时性、市场需求的周期性以及市场中非连续的投标竞价方式，将市场稳定问题转化为一个非线性、非自治的周期差分系统的稳定问题。为了研究市场的稳定条件，证明了差分系统收敛于唯一有界周期解的条件，并据此提出了系统最终收敛边界的估计公式。基于文中提出的模型和引理，给出了电力市场稳定的一个充分条件以及电价最终收敛边界的估计公式，并以算例仿真验证了其结论的正确性。     

A framework for capacity planning and machine configuration in flexible assembly systems

We consider the problem of simultaneously determining the number of machines (and/or workers), the assignment of tasks (and related tools and components) to these machines, and the number of jobs circulating in a flexible assembly system (FAS), to satisfy steady-state throughput requirements for a family of similar products at minimum cost. We focus on situations where there are precedence relations among the various tasks, as is common in assembly systems. We present a framework for solving this problem based on a heuristic decomposition approach which involves the solution of only a few types of sub-problems. We demonstrate the efficiency and effectiveness of the overall procedure using a number of example problems.     

Simulation modeling for comparative evaluation of supply chain management strategies

Supply chain management (SCM) has become one of the most important strategies for achieving competitive advantage in different industries in the last decade. Researchers have investigated various processes in the planning and development of supply chains. However, increasing attention has been placed on performance, design and analysis of supply chain models. A supply chain is a complex model that is very difficult to analyze, in particular, with respect to performance. Simulation is one of the effective tools to evaluate the control mechanism for a supply chain. In this paper, five common supply chain models have been built and tested with the aid of simulation. Various performance measures such as transportation cost, resources utilization, inventory level, and order cycle time will be calculated for comparative indications. The methodology that is presented in this paper can be extended to any real life applications in SCM.