New concepts for lithium minerals processing

A new concept for the enrichment of lithium minerals is offering higher purity and higher yield by applying new processing technologies addressing the specific properties of the pegmatitic host rock. Additional value is created from high quality by-products which will improve the sustainability of mining activity and the overall cost base. Within the new concept, flotation may even be avoided where wet separation techniques are not applicable.Two innovative processing technologies have been integrated in the new concept: electrodynamic fragmentation and optical sorting. Detailed results of lab-technical tests show that the new process design can achieve highly selective liberation and separation processes. Optical and mineralogical analyses of the test products indicate a high benefit for commercial applications.     

Modelling time-varying higher moments with maximum entropy density

Since the introduction of the Autoregressive Conditional Heteroscedasticity (ARCH) model of Engle [R. Engle, Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica 50 (1982) 987–1007], the literature of modelling the conditional second moment has become increasingly popular in the last two decades. Many extensions and alternate models of the original ARCH have been proposed in the literature aiming to capture the dynamics of volatility more accurately. Interestingly, the Quasi Maximum Likelihood Estimator (QMLE) with normal density is typically used to estimate the parameters in these models. As such, the higher moments of the underlying distribution are assumed to be the same as those of the normal distribution. However, various studies reveal that the higher moments, such as skewness and kurtosis of the distribution of financial returns are not likely to be the same as the normal distribution, and in some cases, they are not even constant over time. These have significant implications in risk management, especially in the calculation of Value-at-Risk (VaR) which focuses on the negative quantile of the return distribution. Failed to accurately capture the shape of the negative quantile would produce inaccurate measure of risk, and subsequently lead to misleading decision in risk management. This paper proposes a solution to model the distribution of financial returns more accurately by introducing a general framework to model the distribution of financial returns using maximum entropy density (MED). The main advantage of MED is that it provides a general framework to estimate the distribution function directly based on a given set of data, and it provides a convenient framework to model higher order moments up to any arbitrary finite order k. However this flexibility comes with a high cost in computational time as k increases, therefore this paper proposes an alternative model that would reduce computation time substantially. Moreover, the sensitivity of the parameters in the MED with respect to the dynamic changes of moments is derived analytically. This result is important as it relates the dynamic structure of the moments to the parameters in the MED. The usefulness of this approach will be demonstrated using 5 min intra-daily returns of the Euro/USD exchange rate.     

Characterization of silica-based monoliths with bimodal pore size distribution

Band dispersion was studied and the retention thermodynamics addressed for insulin and angiotensin II on C18 silica monoliths with a bimodal pore size distribution, covering linear mobile-phase velocities up to 1 cm/s and different temperatures. These data suggest that the influence of average column pressure on retention (between 0 and 10 MPa) is not negligible. Plate height curves were interpreted with the van Deemter equation by assuming an independent contribution from mechanical and non-mechanical dispersion mechanisms. This analysis revealed diffusion-limited mass transfer in the mesoporous silica skeleton which, in turn, allowed us to calculate an equivalent dispersion particle diameter (d(disp) = 3 microm) using the C-term parameter of the van Deemter equation. The resulting superposition of reduced plate height curves for monolithic and particulate beds confirmed that this view presents an adequate analogy. The macroporous interskeleton network responsible for the hydraulic permeability of a monolith was translated to the interparticle pore space of particulate beds, and an equivalent permeability particle diameter (d(perm) = 15 microm) was obtained by scaling based on the Kozeny-Carman equation.     

Multicriterion genetic optimization for due date assigned distribution network problems

This paper focuses on the demand due date factor in multiechelon distribution network problems and its impact on the production scheduling in manufacturing plants. A reliable demand due date is critical in winning of customer orders. However, this may usually require high collaboration among entities in the network. Mismatching of one single schedule may seriously influence the reliability. In this connection, holistically optimizing the schedule of each entity among the network is essential. In addition, on time delivery may induce high operating cost. A trade-off between earliness, on time, and tardiness should also be considered. Hence, a multicriterion genetic optimization methodology is developed to holistically optimize them. It determines the optimized schedule to collaborate each entity to fulfill the demands. For enabling multicriterion decision-making, the proposed algorithm combines analytic hierarchy process with genetic algorithms (GAs). The problem is divided into two parts—(i) demand allocation and transportation problem, and (ii) production scheduling problem. The optimization approach is applied to iteratively optimize part (i), and then part (ii). Three experiments have been carried out, and the computation results show that the effect of due date is critical, and the ability of the proposed algorithms in taking trade-off between earliness and tardiness.     

Caching video objects: layers vs versions?

Because Internet access rates are highly heterogeneous, many video content providers today make available different versions of the videos, with each version encoded at a different rate. Multiple video versions, however, require more server storage and may also dramatically impact cache performance in a traditional cache or in a CDN server. An alternative to versions is layered encoding, which can also provide multiple quality levels. Layered encoding requires less server storage capacity and may be more suitable for caching; but it typically increases transmission bandwidth due to encoding overhead. In this paper we compare video streaming of multiple versions with that of multiple layers in a caching environment. We examine caching and distribution strategies that use both versions and layers. We consider two cases: the request distribution for the videos is known a priori; and adaptive caching, for which the request distribution is unknown. Our analytical and simulation results indicate that mixed distribution/caching strategies provide the best overall performance.A shorter version of this work has appeared in Proc. of IEEE International Conference on Multimedia and Expo (ICME), Vol. 2, pages 45–48, Lausanne, Switzerland, August 2002     

Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach

In general, distributed scheduling problem focuses on simultaneously solving two issues: (i) allocation of jobs to suitable factories and (ii) determination of the corresponding production scheduling in each factory. The objective of this approach is to maximize the system efficiency by finding an optimal planning for a better collaboration among various processes. This makes distributed scheduling problems more complicated than classical production scheduling ones. With the addition of alternative production routing, the problems are even more complicated. Conventionally, machines are usually assumed to be available without interruption during the production scheduling. Maintenance is not considered. However, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it influences the production scheduling. In this connection, maintenance should be considered in distributed scheduling. The objective of this paper is to propose a genetic algorithm with dominant genes (GADG) approach to deal with distributed flexible manufacturing system (FMS) scheduling problems subject to machine maintenance constraint. The optimization performance of the proposed GADG will be compared with other existing approaches, such as simple genetic algorithms to demonstrate its reliability. The significance and benefits of considering maintenance in distributed scheduling will also be demonstrated by simulation runs on a sample problem.     

Model-based control of a simulated moving bed chromatographic process for the separation of fructose and glucose

Chromatographic separations are an expanding technology for the separation of high value products, particularly in the area of pharmaceutics, food, and fine chemicals. The simulated moving bed (SMB) process as a continuous chromatographic separation process is an interesting alternative to conventional batch chromatography, and gained more and more impact recently. The SMB process is realized by connecting several single chromatographic columns in series. A countercurrent movement of the bed is approximated by a cyclic switching of the inlet and outlet ports in the direction of the fluid stream. Because of its complex dynamics, the optimal operation and automatic control of SMB processes is a challenging task. This paper presents the design of a model-based optimization and control scheme for SMB chromatographic separation processes and its application to the separation of fructose and glucose. We propose a two-layer control architecture where the optimal operating trajectory is calculated off-line by dynamic optimization based on a rigorous process model. The parameters of the model are adapted based on online measurements. The low-level control task is to keep the process on the optimal trajectory despite disturbances and plant/model mismatch. Here identification models based on simulation data of the rigorous process model along the optimal trajectory are combined with a suitable local controller. The efficiency of the trajectory control algorithm is shown in a simulation study for the separation of fructose and glucose on an 8-column SMB plant.     

Applications of specialized coils for high-resolution MRI on a whole-body scanner

To investigate the application of a mini-coil surface system for high-resolution MRI, 60 volunteers were examined in a 1.5-T whole-body scanner. Two replaceable probe heads were available: a circular 2.5-cm coil and a quadratic 5-cm coil, both of which were placed directly on the skin. The skin layers, Achilles tendon and finger joints were examined with the 2.5-cm coil and a FOV of 25 × 25 mm². A matrix of 256 × 256 pixels resulted in a pixel size of 0.098 × 0.098 mm². For imaging of the carpal tunnel, the 5-cm coil was used in transverse orientation. The FOV was 50 × 50 mm² so that a matrix of 256 × 256 pixels led to a pixel size of 0.195 × 0.195 mm². The resulting spatial resolution permitted visualization of the epidermis, dermis and subcutis, resulting in clear definition of anatomical detail of the musculoskeletal system. MRI measurement of skin-layer thickness did not correlate with histometric data (p<0.05). This discrepancy was due in part to shrinkage of the tumor specimen on histologic preparation. Other causes include the motion artifacts and the limited accuracy of determining thickness on the MRI display unit.