Multiple-Input Multiple-Output (MIMO) communications systems using multiantenna arrays simultaneously during transmission and reception have generated significant interest in recent years. Theoretical work in the mid 1990?s showed the potential for significant capacity increases in wireless channels via spatial multiplexing with sparse antenna arrays and rich scattering environments. However, in reality the capacity is significantly reduced when the antennas are placed close together, or the scattering environment is sparse, causing the signals received by different antennas to become correlated, corresponding to a reduction of the effective number of sub-channels between transmit and receive antennas. By introducing the previously ignored spatial aspects, namely the antenna array geometry and the scattering environment, into a novel channel model new bounds and fundamental limitations to MIMO capacity are derived for spatially constrained, or spatially selective, channels. A theoretically derived capacity saturation point is shown to exist for spatially selective MIMO channels, at which there is no capacity growth with increasing numbers of antennas. Furthermore, it is shown that this saturation point is dependent on the shape, size and orientation of the spatial volumes containing the antenna arrays along with the properties of the scattering environment. This result leads to the definition of an intrinsic capacity between separate spatial volumes in a continuous scattering environment, which is an upper limit to communication between the volumes that can not be increased with increasing numbers of antennas within. It is shown that there exists a fundamental limit to the information theoretic capacity between two continuous volumes in space, where using antenna arrays is simply one choice of implementation of a more general spatial signal processing underlying all wireless communication systems.

<p>The Swedish National Labour Market Administration wishes to acquire further knowledge about how the evaluation process of vocational rehabilitation at the employment service operates as a part of the quality assurance of this activity. The primary task for vocational rehabilitation at the employment service is to investigate the work capacity of unemployed people, to give them increased knowledge and better understanding of their own capacity concerning work or education. The aim of this study was to survey the evaluation process of vocational rehabilitation at the employment service in Sweden. Data were collected through telephone interviews with 15 occupational therapists employed at the employment service, who were working with vocational rehabilitation. The result shows that the investigation of work capacity can take place in different environments and that the space of time for an investigation can vary. During the evaluation process, different types of data collection methods are used. Nevertheless, the result shows that the evaluation process begins and ends in similar ways. Further studies to validate the result would be interesting. These could be done through quantitative studies, for example by sending questionnaires based on the result of this study.</p>

<p>The Laplace equation and the related p-Laplace equation are closely associated with Sobolev spaces. During the last 15 years people have been exploring the possibility of solving partial differential equations in general metric spaces by generalizing the concept of Sobolev spaces. One such generalization is the Newtonian space where one uses upper gradients to compensate for the lack of a derivative.</p><p>All papers on this topic are written for an audience of fellow researchers and people with graduate level mathematical skills. In this thesis we give an introduction to the Newtonian spaces accessible also for senior undergraduate students with only basic knowledge of functional analysis. We also give an introduction to the tools needed to deal with the Newtonian spaces. This includes measure theory and curves in general metric spaces.</p><p>Many of the properties of ordinary Sobolev spaces also apply in the generalized setting of the Newtonian spaces. This thesis includes proofs of the fact that the Newtonian spaces are Banach spaces and that under mild additional assumptions Lipschitz functions are dense there. To make them more accessible, the proofs have been extended with comments and details previously omitted. Examples are given to illustrate new concepts.</p><p>This thesis also includes my own result on the capacity associated with Newtonian spaces. This is the theorem that if a set has p-capacity zero, then the capacity of that set is zero for all smaller values of p.</p>

The relevance of domestic and foreign capacity utilization rates in forecasting future inflation rate has been investigated empirically, using five industrialized countries for which the comparable data are available. It has been found that capacity utilization rates, both domestic and foreign, have a long run stable relationship with domestic inflation rate and a positive shock in the capacity utilization rate results in a significant, although a little bit delayed, acceleration in the domestic inflation rate. Various econometric techniques have been used and led to consistent empirical findings. The results in the present study, therefore, dispute the claim that an increase in capacity utilization rate may not necessarily lead to an accelerated inflation down the road. / Graduation date: 1995

Decisions on capacity are often treated separately from those of production and inventory. In most situations, capacity issues are longer-term, so capacity-related decisions are considered strategic and thus not part of supply planning. This research focuses on optimal supply planning with emphasis on variable capacity to meet uncertain demand. It also defines three levels of capacity change: operating hours, labor availability and production hardware availability. The work presented here deals with the fundamental decisions to determine capacity, production, and inventory to meet customer demand while optimizing revenue and costs over a planning horizon (typically the life of the product). With the Lagrangian technique for constrained optimization, it can be shown that the optimal supply capacity has upper and lower bounds. The optimal feedback policy prescribes increasing the supply capacity when at the beginning of the planning interval it is below the lower bound. Similarly, the supply capacity should be decreased to the upper bound when it is above the upper bound. This paper will present arguments for characterizing forecast evolution and information sharing in the supply chain to obtain a predictor-corrector approach to supply chain control. / Singapore-MIT Alliance (SMA)

Thesis (M.Sc. (Nutrition))--North-West University, Potchefstroom Campus, 2007.

Thesis (M.Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2009.

Demand uncertainty has been recognized as one factor that may cause price dispersion in perfectly competitive markets with costly and perishable capacity. With the persistence of the degree of price dispersion in increasingly competitive markets, demand uncertainty has become more important for us to understand the phenomenon of fare inequality. This dissertation consists of three related studies on this topic. In the first study, Prescott (1975) model is extends by incorporating the heterogeneity of customers' reservation values. The model shows that the equilibrium price dispersion also depends on the mix of customers and their reservation values. With customer segmentation based on reservation values, the equilibrium price dispersion is more efficient than what can be achieved without segmentation. In the airline industry context, the model implies that different prices can exist simultaneously in the market and carriers would provide more seats if they can segment their travelers. This sheds light on an alternative motivation for airlines to require Saturday night stay over other than the practice of price discrimination. In the second study, a price simulation in the airline industry is conducted. The stochastic demand for coach class, nonstop, air travel service on the observed routs is calculated. Then a market price schedule based on Prescott's model is simulated by using nonparametric method. The comparison between the simulated price distribution and the actual price distribution provides evidence that on average more than 60 percent of the fare inequality on the observed routes can be accounted for by cost variation due to demand uncertainty under the condition of perfect competition. At last, an empirical model is specified to explore the relationship between route demand uncertainty and carrier price dispersion in U.S. air travel markets. The results demonstrate that the effect of route demand uncertainty on carrier price dispersion varies with the market structure. In monopoly market, the route demand uncertainty has no effect on carrier price dispersion. While in duopoly and competitive markets, the increase of route demand uncertainty is associated with the decrease of the carrier price dispersion. Furthermore, the negative relationship is magnified when the market becomes more competitive.

Thesis (M.Sc.)--Memorial University of Newfoundland, 2005. / Includes bibliographical references.

In this research, we consider production/inventory management decisions of a rmthat sells its product in two market segments during a nite planning horizon. In thebeginning of each period, the rm makes a decision on how much to produce basedon the production capacity and the current on-hand inventory available. After theproduction is made at the beginning of the period, the rm rst satises the stochasticdemand from customers in its primary market. Any primary market demand thatcannot be satised is lost. After satisfying the demand from the primary market, ifthere is still inventory on hand, all or part of the remaining products can be sold ina secondary market with ample demand at a lower price. Hence, the second decisionthat the rm makes in each period is how much to sell in the secondary market, orequivalently, how much inventory to carry to the next period.The objective is to maximize the expected net revenue during a nite planninghorizon by determining the optimal production quantity in each period, and theoptimal inventory amount to carry to the next period after the sales in primary andsecondary markets. We term the optimal inventory amount to be carried to the nextperiod as \economic retention quantity". We model this problem as a nite horizonstochastic dynamic program. Our focus is to characterize the structure of the optimalpolicy and to analyze the system under dierent parameter settings. Conditioning on given parameter set, we establish lower and upper bounds on the optimal policyparameters. Furthermore, we provide computational tools to determine the optimalpolicy parameters. Results of the numerical analysis are used to provide furtherinsights into the problem from a managerial perspective.