Model and visualise the relationship between energy consumption and temperature distribution in cold rooms

In the area of food and pharmacy cold storage, temperature distribution is considered as a key factor. Inappropriate distribution of temperature during the cooling process in cold rooms will cause the deterioration of the quality of products and therefore shorten their life-span. In practice, in order to maintain the distribution of temperature at an appropriate level, large amount of electrical energy has to be consumed to cool down the volume of space, based on the reading of a single temperature sensor placed in every cold room. However, it is not clear and visible that what is the change of energy consumption and temperature distribution over time. It lacks of effective tools to visualise such a phenomenon. In this poster, we initially present a solution which combines a visualisation tool with a Computational Fluid Dynamics (CFD) model together to enable users to explore such phenomenon.

Optimised crystal morphologies for active pharmaceutical ingredients and related studies

The majority of active pharmaceutical ingredients (APIs) are crystalline solids in their pure forms. Crystalline solids have definable morphologies, i.e. shape and size. Crystal morphology is determined by both the internal structure of the crystals and external factors during growth from solution. The morphology of a crystal batch can affect key processes during manufacturing. Companies generally accept whatever morphology the manufacturing process provides and deal with any subsequent problems by costly trouble‒shooting. Rational design of optimised morphologies for crystalline pharmaceutical solids would be a very significant technical and commercial advance. Chapter one introduces the concept of crystal nucleation and growth. The phenomenon of polymorphism alongside the causes and impact is discussed. A summary of the scope of instrumentation used in the investigation of crystal polymorphism and morphology, including crystal size distribution (CSD), is also included. Chapter two examines the research carried out during an exploration of the optimum crystallisation parameters of phenacetin. Following a morphological study, the impact this induces on particle density and flow properties is examined. The impact of impurities on the crystallisation properties of phenacetin is investigated. Significantly, the location of impurities within individual crystals is also studied. The third chapter describes an industrial collaboration looking at the resolution and polymorphic study of trometamol and lysine salts of ketoprofen and 2‒phenylpropionic acid (2‒PPA). Chapter four incorporates a solid state study on three separate compounds: 2‒chloro‒4‒nitroaniline, 4‒hydroxy‒N‒phenylbenzenesulfonamide and N‒acetyl‒D‒glucosamine‒6‒O‒sulfate. 2‒Chloro‒4‒nitroaniline and 4‒hydroxy‒N‒phenylbenzenesulfonamide both produced interesting, extreme morphologies which warranted further investigation as part of a collaborative study. Following a summarisation of results in chapter five, chapter six contains the full experimental details, incorporating spectral and other analytical data for all compounds synthesised during the course of the research.

ALD: adaptive layer distribution for scalable video

Recent years have witnessed a rapid growth in the demand for streaming video over the Internet and mobile networks, exposes challenges in coping with heterogeneous devices and varying network throughput. Adaptive schemes, such as scalable video coding, are an attractive solution but fare badly in the presence of packet losses. Techniques that use description-based streaming models, such as multiple description coding (MDC), are more suitable for lossy networks, and can mitigate the effects of packet loss by increasing the error resilience of the encoded stream, but with an increased transmission byte cost. In this paper, we present our adaptive scalable streaming technique adaptive layer distribution (ALD). ALD is a novel scalable media delivery technique that optimises the tradeoff between streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data are spread amongst all packets, thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the resiliency of the scalable video. The Subjective testing results illustrate that our techniques and models were able to provide levels of consistent high-quality viewing, with lower transmission cost, relative to MDC, irrespective of clip type. This highlights the benefits of selective packetisation in addition to intuitive encoding and transmission.

ALD: adaptive layer distribution for scalable video

Bandwidth constriction and datagram loss are prominent issues that affect the perceived quality of streaming video over lossy networks, such as wireless. The use of layered video coding seems attractive as a means to alleviate these issues, but its adoption has been held back in large part by the inherent priority assigned to the critical lower layers and the consequences for quality that result from their loss. The proposed use of forward error correction (FEC) as a solution only further burdens the bandwidth availability and can negate the perceived benefits of increased stream quality. In this paper, we propose Adaptive Layer Distribution (ALD) as a novel scalable media delivery technique that optimises the tradeoff between the streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data is spread amongst all datagrams thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the scalable video, while providing increased resilience to the highest quality layers. Our experimental results show that ALD improves the perceived quality and also reduces the bandwidth demand by up to 36% in comparison to the well-known Multiple Description Coding (MDC) technique.