Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to compare performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implication for generation policy in Korea as outlined in this study.

Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to assess the performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implications for generation policy in Korea as outlined in this study.

Agent-orientated auction mechanism and strategy design

Agent-based technology is playing an increasingly important role in today’s economy. Usually a multi-agent system is needed to model an economic system such as a market system, in which heterogeneous trading agents interact with each other autonomously. Two questions often need to be answered regarding such systems: 1) How to design an interacting mechanism that facilitates efficient resource allocation among usually self-interested trading agents? 2) How to design an effective strategy in some specific market mechanisms for an agent to maximise its economic returns? For automated market systems, auction is the most popular mechanism to solve resource allocation problems among their participants. However, auction comes in hundreds of different formats, in which some are better than others in terms of not only the allocative efficiency but also other properties e.g., whether it generates high revenue for the auctioneer, whether it induces stable behaviour of the bidders. In addition, different strategies result in very different performance under the same auction rules. With this background, we are inevitably intrigued to investigate auction mechanism and strategy designs for agent-based economics. The international Trading Agent Competition (TAC) Ad Auction (AA) competition provides a very useful platform to develop and test agent strategies in Generalised Second Price auction (GSP). AstonTAC, the runner-up of TAC AA 2009, is a successful advertiser agent designed for GSP-based keyword auction. In particular, AstonTAC generates adaptive bid prices according to the Market-based Value Per Click and selects a set of keyword queries with highest expected profit to bid on to maximise its expected profit under the limit of conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. The TAC CAT tournament provides an environment for investigating the optimal design of mechanisms for double auction markets. AstonCAT-Plus is the post-tournament version of the specialist developed for CAT 2010. In our experiments, AstonCAT-Plus not only outperforms most specialist agents designed by other institutions but also achieves high allocative efficiencies, transaction success rates and average trader profits. Moreover, we reveal some insights of the CAT: 1) successful markets should maintain a stable and high market share of intra-marginal traders; 2) a specialist’s performance is dependent on the distribution of trading strategies. However, typical double auction models assume trading agents have a fixed trading direction of either buy or sell. With this limitation they cannot directly reflect the fact that traders in financial markets (the most popular application of double auction) decide their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Experiments are conducted under both dynamic and static settings of the continuous BDA market. We find that the allocative efficiency of a continuous BDA market mainly comes from rational selection of trading directions. Furthermore, we introduce a high-performance Kernel trading strategy in the BDA market which uses kernel probability density estimator built on historical transaction data to decide optimal order prices. Kernel trading strategy outperforms some popular intelligent double auction trading strategies including ZIP, GD and RE in the continuous BDA market by making the highest profit in static games and obtaining the best wealth in dynamic games.

The emergence of knowledge exchange:an agent-based model of a software market

We investigate knowledge exchange among commercial organizations, the rationale behind it, and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high-level concepts like network effects, reputation, and trust. We attempt to formalize a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multiagent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behavior. The conclusions reached by this agent-based analysis are twofold: 1) a straightforward set of assumptions is enough to give rise to exchange in a software market, and 2) knowledge exchange is shown to increase the efficiency of the market.

Implementing an agent-based model with a spatial visual display in discrete-event simulation software

There has been an increasing interest in the use of agent-based simulation and some discussion of the relative merits of this approach as compared to discrete-event simulation. There are differing views on whether an agent-based simulation offers capabilities that discrete-event cannot provide or whether all agent-based applications can at least in theory be undertaken using a discrete-event approach. This paper presents a simple agent-based NetLogo model and corresponding discrete-event versions implemented in the widely used ARENA software. The two versions of the discrete-event model presented use a traditional process flow approach normally adopted in discrete-event simulation software and also an agent-based approach to the model build. In addition a real-time spatial visual display facility is provided using a spreadsheet platform controlled by VBA code embedded within the ARENA model. Initial findings from this investigation are that discrete-event simulation can indeed be used to implement agent-based models and with suitable integration elements such as VBA provide the spatial displays associated with agent-based software.

The selective protection afforded by ebselen against lipid peroxidation in an ROS-dependent model of inflammation

The effects of an experimental model of hydrogen-peroxide-induced foot pad oedema on indices of oxidative damage to biomolecules have been investigated. We have demonstrated increased levels of fluorescent protein and lipid peroxides occurring in plasma at 24 and 48 h post-injection. In addition, a decrease in the degree of galactosylation of IgG was observed which kinetically related the degree of inflammation and to the increase in protein autofluorescence (a specific index of oxidative damage). The effects of ebselen, a novel organoselenium compound which protects against oxidative tissue injury in a glutathione-peroxidase-like manner, have also been examined in this model. Pretreatment of animals with a dose of 50 mg/kg ebselen afforded significant and selective protection against lipid peroxidation only. This effect may contribute to the anti-inflammatory effect of this agent in hydroperoxide-linked tissue damage.

Solubilisation of drugs within liposomal bilayers:alternatives to cholesterol as a membrane stabilising agent

Objectives The aim of this work was to investigate the effect of cholesterol on the bilayer loading of drugs and their subsequent release and to investigate fatty alcohols as an alternative bilayer stabiliser to cholesterol. Methods The loading and release rates of four low solubility drugs (diazepam, ibuprofen, midazolam and propofol) incorporated within the bilayer of multilamellar liposomes which contained a range of cholesterol (0–33 mol/mol%) or a fatty alcohol (tetradecanol, hexadecanol and octadecanol) were investigated. The molecular packing of these various systems was also investigated in Langmuir monolayer studies. Key findings Loading and release of drugs within the liposome bilayer was shown to be influenced by their cholesterol content: increasing cholesterol content was shown to reduce drug incorporation and inclusion of cholesterol in the bilayer changed the release profile of propofol from zero-order, for phosphatidyl choline only liposomes, to a first-order model when 11 to 33 total molar % of cholesterol was present in the formulation. At higher bilayer concentrations substitution of cholesterol with tetradecanol was shown to have less of a detrimental impact on bilayer drug loading. However, the presence of cholesterol within the liposome bilayer was shown to reduce drug release compared with fatty alcohols. Monolayer studies undertaken showed that effective mean area per molecule for a 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) : cholesterol mixture deviated by 9% from the predicted area compared with 5% with a similar DSPC : tetradecanol mixture. This evidence, combined with cholesterol being a much more bulky structure, indicated that the condensing influence of tetradecanol was less compared with cholesterol, thus supporting the reduced impact of tetradecanol on drug loading and drug retention. Conclusions Liposomes can be effectively formulated using fatty alcohols as an alternative bilayer stabiliser to cholesterol. The general similarities in the characteristics of liposomes containing fatty alcohols or cholesterol suggest a common behavioural influence for both compounds within the bilayer.

Genetics and competing strategies in a threshold model for mail processing

Multi-agent algorithms inspired by the division of labour in social insects are applied to a problem of distributed mail retrieval in which agents must visit mail producing cities and choose between mail types under certain constraints.The efficiency (i.e. the average amount of mail retrieved per time step), and the flexibility (i.e. the capability of the agents to react to changes in the environment) are investigated both in static and dynamic environments. New rules for mail selection and specialisation are introduced and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a genetic algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation. From a more theoretical point of view, in order to avoid finite size effects, most results are obtained for large population sizes. However, we do analyse the influence of population size on the performance. Furthermore, we critically analyse the causes of efficiency loss, derive the exact dynamics of the model in the large system limit under certain conditions, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

Design and development of agent-based procurement system to enhance business intelligence

The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

Compatibilisation of heterogeneous polymer blends by reactive processing

Functionalisation of polystyrene, PS, and ethylene-co-propylene-co-cyclopentadiene terpolymer, EPDM, with acrylic acid, AA, in a melt reactive processing procedure, in the presence of peroxide, trigonox 101, and coagents, Divinyl benzene, DVB (for PS), and trimethylolpropane triacrylate, TRIS (for EPDM), were successfully carried out. The level of grafting of the AA, as determined by infrared analysis, was significantly enhanced by the coagents. The grafting reaction of AA takes place simultaneously with homopolymerisation of the monomers, melt degradation and crosslinking reactions of the polymers. The extent of these competing reactions were inferred from measurements of melt flow index and insoluble gel content. Through a judicious use of both the peroxide and the coagent, particularly TRIS, unwanted side reactions were minimized. Five different processing methods were investigated for both functionalisation experiments; the direct addition of the pre-mixed polymer with peroxide and reactive modifiers was found to give optimum condition for grafting. The functionalised PS, F-PS, and EPDM, F-EPD, and maleinised polypropylene carrying a potential antioxidant, N-(4-anilinophenyl maleimide), F-PP were melt blended in binary mixtures of F-PS/F-EPD and F-PP/F-EPD in the presence (or absence) of organic diamines which act as an interlinking agent, e.g, Ethylene Diamine, EDA, and Hexamethylene Diamine, HEMDA. The presence of an interlinking agent, particularly HEMDA shows significant enhancement in the mechanical properties of the blend, suggesting that the copolymer formed has acted as compatibiliser to the otherwise incompatible polymer pairs. The functionalised and amidised blends, F and A-PSIEPDM (SPOI) and F and A-PPIEPDM (SPD2) were subsequently used as compatibiliser concentrates in the corresponding PSIEPDM and PPIEPDM blends containing various weight propotion of the homopolymers. The SPD1 caused general decreased in tensile strength, albeit increased in drop impact strength particularly in blend containing high PS content (80%). The SPD2 was particularly effective in enhancing impact strength in blends containing low weight ratio of PP (<70%). The SPD2 was also a good thermal antioxidant albeit less effective than commercial antioxidant. In all blends the evidence of compatibility was examined by scanning electron microscopy.

A projected process kriging algorithm for sensor networks with heterogeneous error characteristics

Large monitoring networks are becoming increasingly common and can generate large datasets from thousands to millions of observations in size, often with high temporal resolution. Processing large datasets using traditional geostatistical methods is prohibitively slow and in real world applications different types of sensor can be found across a monitoring network. Heterogeneities in the error characteristics of different sensors, both in terms of distribution and magnitude, presents problems for generating coherent maps. An assumption in traditional geostatistics is that observations are made directly of the underlying process being studied and that the observations are contaminated with Gaussian errors. Under this assumption, sub–optimal predictions will be obtained if the error characteristics of the sensor are effectively non–Gaussian. One method, model based geostatistics, assumes that a Gaussian process prior is imposed over the (latent) process being studied and that the sensor model forms part of the likelihood term. One problem with this type of approach is that the corresponding posterior distribution will be non–Gaussian and computationally demanding as Monte Carlo methods have to be used. An extension of a sequential, approximate Bayesian inference method enables observations with arbitrary likelihoods to be treated, in a projected process kriging framework which is less computationally intensive. The approach is illustrated using a simulated dataset with a range of sensor models and error characteristics.

Azidoprofen as a soft anti-flammatory agent for the topical treatment of Psoriasis

Azidoprofen {2-(4-azidophenyl)propionic acid; AZP}, an azido-substituted arylalkanoic acid, was investigated as a model soft drug candidate for a potential topical non-steroidal anti-inflammatory agent (NSAIA). Reversed-phase high performance liquid chromatography (HPLC) methods were developed for the assay of AZP, a series of ester analogues and their· degradation products. 1H-NMR spectroscopy was also employed as an analytical method in selected cases. Reduction of the azido-group to the corresponding amine has been proposed as a potential detoxification mechanism for compounds bearing this substituent. An in vitro assay to measure the susceptibility of azides towards reduction was developed using dithiothreitol as a model reducing agent. The rate of reduction of AZP was found to be base-dependent, hence supporting the postulated mechanism of thiol-mediated reduction via nucleophilic attack by the thiolate anion. Prodrugs may enhance topical bioavailability through the manipulation of physico-chemical properties of the parent drug. A series of ester derivatives of AZP were investigated for their susceptibility to chemical and enzymatic hydrolysis, which regenerates the parent acid. Use of alcoholic cosolvents with differing alkyl functions to that of the ester resulted in transesterification reactions, which were found to be enzyme-mediated. The skin penetration of AZP was assessed using an in vitro hairless mouse skin model, and silastic membrane in some cases. The rate of permeation of AZP was found to be a similar magnitude to that of the well established NSAIA ibuprofen. Penetration rates were dependent on the vehicle pH and drug concentration when solutions were employed. In contrast, flux was independent of pH when suspension formulations were used. Pretreatment of the skin with various enhancer regimes, including oleic acid and azone in propylene glycol, promoted the penetration of AZP. An intense IR absorption due to the azide group serves as a highly diagnostic marker, enabling azido compounds to be detected in the outer layers of the· stratum corneum following their application to skin, using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). This novel application enabled a non-invasive examination of the percutaneous penetration enhancement of a model azido compound in vivo in man, in the presence of the enhancer oleic acid.

The effect of social influence and curfews on civil violence

We investigate the policies of (1) restricting social influence and (2) imposing curfews upon interacting citizens in a community. We compare and contrast their effects on the social order and the emerging levels of civil violence. Influence models have been used in the past in the context of decision making in a variety of application domains. The policy of curfews has been utilised with the aim of curbing social violence but little research has been done on its effectiveness. We develop a multi-agent-based model that is used to simulate a community of citizens and the police force that guards it. We find that restricting social influence does indeed pacify rebellious societies, but has the opposite effect on peaceful ones. On the other hand, our simple model indicates that restricting mobility through curfews has a pacifying effect across all types of society.

A probabilistic model for trust and reputation

This paper concerns the problem of agent trust in an electronic market place. We maintain that agent trust involves making decisions under uncertainty and therefore the phenomenon should be modelled probabilistically. We therefore propose a probabilistic framework that models agent interactions as a Hidden Markov Model (HMM). The observations of the HMM are the interaction outcomes and the hidden state is the underlying probability of a good outcome. The task of deciding whether to interact with another agent reduces to probabilistic inference of the current state of that agent given all previous interaction outcomes. The model is extended to include a probabilistic reputation system which involves agents gathering opinions about other agents and fusing them with their own beliefs. Our system is fully probabilistic and hence delivers the following improvements with respect to previous work: (a) the model assumptions are faithfully translated into algorithms; our system is optimal under those assumptions, (b) It can account for agents whose behaviour is not static with time (c) it can estimate the rate with which an agent's behaviour changes. The system is shown to significantly outperform previous state-of-the-art methods in several numerical experiments. Copyright © 2010, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.