Using a fuzzy approach to support financial analysis in the corporate acquisition process

In the global market place, many companies have had to adapt their strategies to meet significant challenges. A strategy adopted by some companies has been international expansion via acquisitions. The need for expert knowledge to determine an appropriate company to acquire has been complicated by the sheer size of the global market place. The costs associated with this in relation to time and personnel have created the need for a computerised expert system to be developed. This paper endeavours to show how a proposed fuzzy based system can assist in the identification of a company for acquisition. The authors discuss the manipulation of the magnitude of fuzzy membership functions to communicate priorities within the system. The fuzzy system is designed to assist financial experts in identifying a suitable company for acquisition in the corporate acquisition process. This includes the deliberate weighting of certain inputs and results above others in the decision-making process. The system attempts to learn and simulate the human precedence given to particular financial statistics in company analysis. The system uses the magnitude of the fuzzy membership functions to reflect the human precedence given to each financial ratio. This enables a particular company's strengths and weakness to be considered while concurrently considering their significance and relevance to the acquiring organisation. The system will enable a larger number of companies to be analysed in a more time and cost-effective manner. The development of this system is intended to illustrate that a fuzzy system can aid the financial experts of an acquiring organisation in the global acquisition process.     

Downstream performance prediction for a manufacturing system using neural networks and six-sigma improvement techniques

Intelligent techniques have been applied in a range of industrial environments [Meziane F, Vadera S, Kobbacy K, Proudlove N. Intelligent systems in manufacturing: current developments and future prospects. Integrated Manuf Syst 2000;11(4):218–38; Stephanopoulos G, Han C. Intelligent systems in process engineering: a review. Comput Chem Eng, 1996;20 (6–7):743–91; Johnston AB, Maguire LP, McGinnity TM. Using business improvement techniques to inform the optimisation of production cycle time: an industrial case study. Proceedings of the IEEE SMC UK-RI Chapter conference 2004 on intelligent cybernetic systems. September 7–8, 2004 ISSN:1744–9189; Proudlove NC, Vadera S, Kobbacy KAH. Intelligent management systems in operations: A review. J Oper Res Soc, 1998;49(7):682–99] although their implementation is not the first choice of many process engineers. In contrast process engineers in a diverse range of manufacturing environments regularly deploy business improvement techniques, such as the six-sigma methodology. Such techniques aim to control and subsequently identify the relationship between the process inputs and outputs so that a process engineer can more accurately predict how the process output shall perform based on the system inputs. Factors such as cost reduction, automatic process control or simply process prediction may be the defining factors in establishing prediction models.     

Transport-mediated release of endogenous glutamate in the vertebrate retina

In the present study we measured calcium-dependent, vesicular glutamate release, and calcium-independent, transport-mediated glutamate release patterns in the vertebrate retina to better understand the sources of elevated glutamate in neural tissue under ischemic conditions. A potassium concentration of 40 mM, which mimics the extracellular potassium concentration in the central nervous system during ischemia, was applied to the bathing medium of a retinal slice prepared from zebrafish. High external potassium evoked release of endogenous glutamate that was measured using a glutamate-specific fluorometric assay applied to the bath. The slice was visualized under 668 nm light using Normarski optics and fluorescent images were captured using a cooled charge-coupled device (CCD) camera. Following the elevation of external potassium to 40 mM several bands of glutamate fluorescence, reflecting the spatial distribution of glutamate release, were observed. A calcium-dependent cloud of glutamate was observed in the inner plexiform layer, that was antagonized by bath-applied nifedipine. A relatively dense glutamate cloud (1-10 microM) was observed over the ganglion cell layer, which was blocked by dihydrokainate, a glutamate transport antagonist. In contrast, nifedipine, an inhibitor of calcium-dependent neurotransmitter release in the retina, failed to block the cloud of released glutamate in the ganglion cell layer. These data suggest that under pathological conditions in the eye where glutamate levels are elevated surrounding retinal ganglion cells, such as observed in some forms of glaucoma, a possible source of the elevated glutamate is through a glutamate transporter operating in a reversed direction. A likely candidate for mediating this reversed transport of glutamate is the retinal Muller cell.     

Mie scattering of electromagnetic radiation by a sphere: A computer program

A computer program for calculating the Mie scattering of electromagnetic radiation by a sphere is described. The program will evaluate, amongst other parameters, the Mie scattering functions a_m and b_m, the extinction, scattering, back-scattering, absorption and radiation pressure efficiencies, the intensity functions, I₁ and I₂ and the polarisation ratios

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. The program can be made available to other users and computations can be commissioned on a repayment basis. A library of results is being established.     

Advances in Design and Application of Spiking Neural Networks

This paper presents new findings in the design and application of biologically plausible neural networks based on spiking neuron models, which represent a more plausible model of real biological neurons where time is considered as an important feature for information encoding and processing in the brain. The design approach consists of an evolutionary strategy based supervised training algorithm, newly developed by the authors, and the use of different biologically plausible neuronal models. A dynamic synapse (DS) based neuron model, a biologically more detailed model, and the spike response model (SRM) are investigated in order to demonstrate the efficacy of the proposed approach and to further our understanding of the computing capabilities of the nervous system. Unlike the conventional synapse, represented as a static entity with a fixed weight, employed in conventional and SRM-based neural networks, a DS is weightless and its strength changes upon the arrival of incoming input spikes. Therefore its efficacy depends on the temporal structure of the impinging spike trains. In the proposed approach, the training of the network free parameters is achieved using an evolutionary strategy where, instead of binary encoding, real values are used to encode the static and DS parameters which underlie the learning process. The results show that spiking neural networks based on both types of synapse are capable of learning non-linearly separable data by means of spatio-temporal encoding. Furthermore, a comparison of the obtained performance with classical neural networks (multi-layer perceptrons) is presented.     

An analysis of specialist and non-specialist user requirements for geographic climate change information

The EU EuroClim project developed a system to monitor and record climate change indicator data based on satellite observations of snow cover, sea ice and glaciers in Northern Europe and the Arctic. It also contained projection data for temperature, rainfall and average wind speed for Europe. These were all stored as data sets in a GIS database for users to download. The process of gathering requirements for a user population including scientists, researchers, policy makers, educationalists and the general public is described. Using an iterative design methodology, a user survey was administered to obtain initial feedback on the system concept followed by panel sessions where users were presented with the system concept and a demonstrator to interact with it. The requirements of both specialist and non-specialist users is summarised together with strategies for the effective communication of geographic climate change information.     

Modeling and Managing State in Distributed Systems: The Role of OGSI and WSRF

We often encounter in distributed systems the need to model, access, and manage state. This state may be, for example, data in a purchase order, service level agreements representing resource availability, or the current load on a computer. We introduce two closely related approaches to modeling and manipulating state within a Web services (WS) framework: the Open Grid Services Infrastructure (OGSI) and WS-Resource Framework (WSRF). Both approaches define conventions on the use of the Web service definition language schema that enable the modeling and management of state. OGSI introduces the idea of a stateful Web service and defines approaches for creating, naming, and managing the lifetime of instances of services; for declaring and inspecting service state data; for asynchronous notification of service state change; for representing and managing collections of service instances; and for common handling of service invocation faults. WSRF refactors and evolves OGSI to exploit new Web services standards, specifically WS-addressing, and to respond to early implementation and application experiences. WSRF retains essentially all of the functional capabilities present in OGSI, while changing some syntax (e.g., to exploit WS-addressing) and also adopting a different terminology in its presentation. In addition, WSRF partitions OGSI functionality into five distinct composable specifications. We explain the relationship between OGSI and WSRF and the related WS-notification specifications, explain the common requirements that both address, and compare and contrast the approaches taken to the realization of those requirements.