Comparison of a centralised and distributed approach for a generic scheduling system

PEGS (Production and Environmental Generic Scheduler) is a generic production scheduler that produces good schedules over a wide range of problems. It is centralised, using search strategies with the Shifting Bottleneck algorithm. We have also developed an alternative distributed approach using software agents. In some cases this reduces run times by a factor of 10 or more. In most cases, the agent-based program also produces good solutions for published benchmark data, and the short run times make our program useful for a large range of problems. Test results show that the agents can produce schedules comparable to the best found so far for some benchmark datasets and actually better schedules than PEGS on our own random datasets. The flexibility that agents can provide for today's dynamic scheduling is also appealing. We suggest that in this sort of generic or commercial system, the agent-based approach is a good alternative.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.

Linear QR architecture for a single chip adaptive beamformer

This paper presents the design of a novel single chip adaptive beamformer capable of performing 50 Gflops, (Giga-floating-point operations/second). The core processor is a QR array implemented on a fully efficient linear systolic architecture, derived using a mapping that allows individual processors for boundary and internal cell operations. In addition, the paper highlights a number of rapid design techniques that have been used to realise this system. These include an architecture synthesis tool for quickly developing the circuit architecture and the utilisation of a library of parameterisable silicon intellectual property (IP) cores, to rapidly develop detailed silicon designs.

Phenotype-environment correlations in a putative whitefish adaptive radiation

1. The adaptive radiation of fishes into benthic (littoral) and pelagic (lentic) morphs in post-glaciallakes has become an important model system for speciation. Although these systems are well stud-ied, there is little evidence of the existence of morphs that have diverged to utilize resources in theremaining principal lake habitat, the profundal zone.
2. Here, we tested phenotype-environment correlations of three whitefish (Coregonus lavaretus)morphs that have radiated into littoral, pelagic and profundal niches in northern Scandinavianlakes. We hypothesized that morphs in such trimorphic systems would have a morphology adaptedto one of the principal lake habitats (littoral, pelagic or profundal niches). Most whitefish popula-tions in the study area are formed by a single (monomorphic) whitefish morph, and we furtherhypothesized that these populations should display intermediate morphotypes and niche utiliza-tion. We used a combination of traditional (stomach content, habitat use, gill raker counts) andmore recently developed (stable isotopes, geometric morphometrics) techniques to evaluate pheno-type-environment correlations in two lakes with trimorphic and two lakes with monomorphicwhitefish.
3. Distinct phenotype-environment correlations were evident for each principal niche in whitefishmorphs inhabiting trimorphic lakes. Monomorphic whitefish exploited multiple habitats, hadintermediate morphology, displayed increased variance in gillraker-counts, and relied significantlyon zooplankton, most likely due to relaxed resource competition.
4. We suggest that the ecological processes acting in the trimorphic lakes are similar to each other,and are driving the adaptive evolution of whitefish morphs, possibly leading to the formation ofnew species.

Adaptive Code Allocation for Interference Management on the Downlink of DS-CDMA Systems

A new technique based on adaptive code-to-user allocation for interference management on the downlink of BPSK based TDD DS-CDMA systems is presented. The principle of the proposed technique is to exploit the dependency of multiple access interference on the instantaneous symbol values of the active users. The objective is to adaptively allocate the available spreading sequences to users on a symbol-by-symbol basis to optimize the decision variables at the downlink receivers. The presented simulations show an overall system BER performance improvement of more than an order of a magnitude with the proposed technique while the adaptation overhead is kept less than 10% of the available bandwidth.

Intelligent demand response electric water heating to integrate wind power in Ireland

Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.

An investigation into the effect of thickness of titanium dioxide and gold-silver nanoparticle titanium dioxide composite thin-films on photocatalytic activity and photo-induced oxygen production in a sacrificial system

Thin films of titanium dioxide and titanium dioxide with incorporated gold and silver nanoparticles were deposited onto glass microscope slides, steel and titanium foil coupons by two sol-gel dip-coating methods. The film's photocatalytic activity and ability to evolve oxygen in a sacrificial solution were assessed. It was found that photocatalytic activity increased with film thickness (from 50 to 500 nm thick samples) for the photocatalytic degradation of methylene blue in solution and resazurin redox dye in an intelligent ink dye deposited on the surface. Contrastingly, an optimum film thickness of similar to 200 nm for both composite and pure films of titanium dioxide was found for water oxidation, using persulfate (S2O82-) as a sacrificial electron acceptor. The nanoparticle composite films showed significantly higher activity in oxygen evolution studies compared with plain TiO2 films.

Integrating wind power using intelligent electric water heating

Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to bene?t end-users ?nancially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system bene?ts. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.

Adaptive Dialogue Strategy Selection through Imprecise Probabilistic Query Answering

In a human-computer dialogue system, the dialogue strategy can range from very restrictive to highly flexible. Each specific dialogue style has its pros and cons and a dialogue system needs to select the most appropriate style for a given user. During the course of interaction, the dialogue style can change based on a user’s response and the system observation of the user. This allows a dialogue system to understand a user better and provide a more suitable way of communication. Since measures of the quality of the user’s interaction with the system can be incomplete and uncertain, frameworks for reasoning with uncertain and incomplete information can help the system make better decisions when it chooses a dialogue strategy. In this paper, we investigate how to select a dialogue strategy based on aggregating the factors detected during the interaction with the user. For this purpose, we use probabilistic logic programming (PLP) to model probabilistic knowledge about how these factors will affect the degree of freedom of a dialogue. When a dialogue system needs to know which strategy is more suitable, an appropriate query can be executed against the PLP and a probabilistic solution with a degree of satisfaction is returned. The degree of satisfaction reveals how much the system can trust the probability attached to the solution.