Space and phase resolved optical emission in mode transitions of radio-frequency inductively coupled plasmas

Inductively coupled radio-frequency plasmas can be operated in two distinct modes. At low power and comparatively low plasma densities the plasma is sustained in capacitive mode (E-mode). As the plasma density increases a transition to inductive mode (H-mode) is observed. This transition region is of particular interest and governed by non-linear dynamics, which under certain conditions results in structure formation with strong spatial gradients in light emission. These modes show pronounced differences is various measureable quantities e.g. electron densities, electron energy distribution functions, ion energy distribution functions, dynamics of optical light emission. Here the transition from E- to H- mode in an oxygen containing inductively coupled plasma (ICP) is investigated using space and phase resolved optical emission spectroscopy (PROES). The emission, measured phase resolved, allows investigation of the electron dynamics within the rf cycle, important for understanding the power coupling and ionization mechanisms in the discharge. The temporal variation of the emission reflects the dynamics of relatively high-energy electrons. It is possible to distinguish between E- and H-mode from the intensity and temporal behaviour of the emission.

Improving the utilisation of University teaching space

There is a perception that teaching space in universities is a rather scarce resource. However, some studies have revealed that in many institutions it is actually chronically under-used. Often, rooms are occupied only half the time, and even when in use they are often only half full. This is usually measured by the “utilisation” which is basically the percentage of available ’seat-hours’ that are employed. In real institutions, this utilisation can often takes values as low as 20-40%. One consequence of such low utilisation is that space managers are under pressure to make a more efficient use of the available teaching space. However, better management is hampered because there does not appear to be a good understanding within space management (near-term planning) of why this happens. Nor, a good basis within space planning (long-term planning) of how best to accommodate the expected low utilisations. This motivates our two main goals: (i) To understand the factors that drive down utilisations, (ii) To set up methods to provide better space planning. Here, we provide quantitative evidence that constraints arising from timetabling and location requirements easily have the potential to explain the low utilisations seen in reality. Furthermore, on considering the decision question “Can this given set of courses all be allocated in the available teaching space?” we find that the answer depends on the associated utilisation in a way that exhibits threshold behaviour: There is a sharp division between regions in which the answer is “almost always yes” and those of “almost always no”. Our work suggests that progress in space management and planning will arise from an integrated approach; combining purely space issues with restrictions representing an aggregated or abstracted version of key constraints such as timetabling or location, and

Packet classification by multi-level cutting of the classification space

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs) are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

University space planning and space-type profiles

Universities planning the provision of space for their teaching requirements need to do so in a fashion that reduces capital and maintenance costs whilst still providing a high-quality level of service. Space plans should aim to provide sufficient capacity without incurring excessive costs due to over-capacity. A simple measure used to estimate over-provision is utilisation. Essentially, the utilisation is the fraction of seats that are used in practice, or the ratio of demand to supply. However, studies usually find that utilisation is low, often only 20–40%, and this is suggestive of significant over-capacity.

Our previous work has provided methods to improve such space planning. They identify a critical level of utilisation as the highest level that can be achieved whilst still reliably satisfying the demand for places to allocate teaching events. In this paper, we extend this body of work to incorporate the notions of event-types and space-types. Teaching events have multiple ‘event-types’, such as lecture, tutorial, workshop, etc., and there are generally corresponding space-types. Matching the type of an event to a room of a corresponding space-type is generally desirable. However, realistically, allocation happens in a mixed space-type environment where teaching events of a given type are allocated to rooms of another space-type; e.g., tutorials will borrow lecture theatres or workshop rooms.

We propose a model and methodology to quantify the effects of space-type mixing and establish methods to search for better space-type profiles; where the term “space-type profile” refers to the relative numbers of each type of space. We give evidence that these methods have the potential to improve utilisation levels. Hence, the contribution of this paper is twofold. Firstly, we present informative studies of the effects of space-type mixing on utilisation, and critical utilisations. Secondly, we present straightforward though novel methods to determine better space-type profiles, and give an example in which the resulting profiles are indeed significantly improved.