Inverse model control using recurrent networks

This paper illustrates how internal model control of nonlinear processes can be achieved by recurrent neural networks, e.g. fully connected Hopfield networks. It is shown that using results developed by Kambhampati et al. (1995), that once a recurrent network model of a nonlinear system has been produced, a controller can be produced which consists of the network comprising the inverse of the model and a filter. Thus, the network providing control for the nonlinear system does not require any training after it has been trained to model the nonlinear system. Stability and other issues of importance for nonlinear control systems are also discussed.

Self-organising neural networks for adaptive control

Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

Model-based life cycle cost and assessment tool for sustainable building design decision

There is a growing concern in reducing greenhouse gas emissions all over the world. The U.K. has set 34% target reduction of emission before 2020 and 80% before 2050 compared to 1990 recently in Post Copenhagen Report on Climate Change. In practise, Life Cycle Cost (LCC) and Life Cycle Assessment (LCA) tools have been introduced to construction industry in order to achieve this such as. However, there is clear a disconnection between costs and environmental impacts over the life cycle of a built asset when using these two tools. Besides, the changes in Information and Communication Technologies (ICTs) lead to a change in the way information is represented, in particular, information is being fed more easily and distributed more quickly to different stakeholders by the use of tool such as the Building Information Modelling (BIM), with little consideration on incorporating LCC and LCA and their maximised usage within the BIM environment. The aim of this paper is to propose the development of a model-based LCC and LCA tool in order to provide sustainable building design decisions for clients, architects and quantity surveyors, by then an optimal investment decision can be made by studying the trade-off between costs and environmental impacts. An application framework is also proposed finally as the future work that shows how the proposed model can be incorporated into the BIM environment in practise.

Selection of funding schemes by a borrowing decision model: a Hong Kong case study

In financial decision-making, a number of mathematical models have been developed for financial management in construction. However, optimizing both qualitative and quantitative factors and the semi-structured nature of construction finance optimization problems are key challenges in solving construction finance decisions. The selection of funding schemes by a modified construction loan acquisition model is solved by an adaptive genetic algorithm (AGA) approach. The basic objectives of the model are to optimize the loan and to minimize the interest payments for all projects. Multiple projects being undertaken by a medium-size construction firm in Hong Kong were used as a real case study to demonstrate the application of the model to the borrowing decision problems. A compromise monthly borrowing schedule was finally achieved. The results indicate that Small and Medium Enterprise (SME) Loan Guarantee Scheme (SGS) was first identified as the source of external financing. Selection of sources of funding can then be made to avoid the possibility of financial problems in the firm by classifying qualitative factors into external, interactive and internal types and taking additional qualitative factors including sovereignty, credit ability and networking into consideration. Thus a more accurate, objective and reliable borrowing decision can be provided for the decision-maker to analyse the financial options.

A hypoplastic model of skeletal muscle development displaying reduced foetal myoblast cell numbers, increased oxidative myofibres and improved specific tension capacity

The major component of skeletal muscle is the myofibre. Genetic intervention inducing over-enlargement of myofibres beyond a certain threshold through acellular growth causes a reduction in the specific tension generating capacity of the muscle. However the physiological parameters of a genetic model that harbours reduced skeletal muscle mass have yet to be analysed. Genetic deletion of Meox2 in mice leads to reduced limb muscle size and causes some patterning defects. The loss of Meox2 is not embryonically lethal and a small percentage of animals survive to adulthood making it an excellent model with which to investigate how skeletal muscle responds to reductions in mass. In this study we have performed a detailed analysis of both late foetal and adult muscle development in the absence of Meox2. In the adult, we show that the loss of Meox2 results in smaller limb muscles that harbour reduced numbers of myofibres. However, these fibres are enlarged. These myofibres display a molecular and metabolic fibre type switch towards a more oxidative phenotype that is induced through abnormalities in foetal fibre formation. In spite of these changes, the muscle from Meox2 mutant mice is able to generate increased levels of specific tension compared to that of the wild type.

A hybrid data assimilation scheme for model parameter estimation: application to morphodynamic modelling

We present a novel algorithm for joint state-parameter estimation using sequential three dimensional variational data assimilation (3D Var) and demonstrate its application in the context of morphodynamic modelling using an idealised two parameter 1D sediment transport model. The new scheme combines a static representation of the state background error covariances with a flow dependent approximation of the state-parameter cross-covariances. For the case presented here, this involves calculating a local finite difference approximation of the gradient of the model with respect to the parameters. The new method is easy to implement and computationally inexpensive to run. Experimental results are positive with the scheme able to recover the model parameters to a high level of accuracy. We expect that there is potential for successful application of this new methodology to larger, more realistic models with more complex parameterisations.

Acute effects of meal fatty acid composition on insulin sensitivity in healthy post-menopausal women

Postprandial plasma insulin concentrations after a single high-fat meal may be modified by the presence of specific fatty acids although the effects of sequential meal ingestion are unknown. The aim of the present study was to examine the effects of altering the fatty acid composition in a single mixed fat-carbohydrate meal on glucose metabolism and insulin sensitivity of a second meal eaten 5 h later. Insulin sensitivity was assessed using a minimal model approach. Ten healthy post-menopausal women underwent four two-meal studies in random order. A high-fat breakfast (40 g fat) where the fatty acid composition was predominantly saturated fatty acids (SFA), n-6 polyunsaturated fatty acids (PUFA), long-chain n-3 PUFA or monounsaturated fatty acids (MUFA) was followed 5 h later by a low-fat, high-carbohydrate lunch (5.7 g fat), which was identical in all four studies. The plasma insulin response was significantly higher following the SFA meal than the other meals after both breakfast and lunch (P<0.006) although there was no effect of breakfast fatty acid composition on plasma glucose concentrations. Postprandial insulin sensitivity (SI(Oral)) was assessed for 180 min after each meal. SI(Oral) was significantly lower after lunch than after breakfast for all four test meals (P=0.019) following the same rank order (SFA < n-6 PUFA < n-3 PUFA < MUFA) for each meal. The present study demonstrates that a single meal rich in SFA reduces postprandial insulin sensitivity with 'carry-over' effects for the next meal.

Second meal effect: modified sham feeding does not provoke the release of stored triacylglycerol from a previous high-fat meal

The present study was carried out to determine whether cephalic stimulation, associated with eating a meal, was sufficient stimulus to provoke the release of stored triacylglycerol (TAG) from a previous high-fat meal. Ten subjects were studied on three separate occasions. Following a 12 h overnight fast, subjects were given a standard mixed test meal which contained 56 g fat. Blood samples were taken before the meal and for 5 h after the meal when the subjects were randomly allocated to receive either water (control) or were modified sham fed a low-fat (6 g fat) or moderate-fat (38 g fat) meal. Blood samples were collected for a further 3 h. Compared with the control, modified sham feeding a low- or moderate-fat meal did not provoke an early entry of TAG, analysed in either plasma or TAG-rich lipoprotein (TRL) fraction (density ,1´006 kg/l). The TRL-retinyl ester data showed similar findings. A cephalic phase secretion of pancreatic polypeptide, without a significant increase in cholecystokinin levels, was observed on modified sham feeding. Although these data indicate that modified sham feeding was carried out successfully, analysis of the fat content of the expectorant showed that our subjects may have accidentally ingested a small amount of fat (0´7 g for the low-fat meal and 2´4 g for the moderate-fat meal). Nevertheless, an early TAG peak following modified sham feeding was not demonstrated in the present study, suggesting that significant ingestion of food, and not just orosensory stimulation, is necessary to provoke the release of any TAG stored from a previous meal.

Prolonged effects of modified sham feeding on energy substrate mobilization

Background: Vagal stimulation in response to nutrients is reported to elicit an array of digestive and endocrine responses, including an alteration in postprandial lipid metabolism. Objective: The objective of this study was to assess whether neural stimulation could alter hormone and substrate metabolism during the late postprandial phase, with implications for body fat mobilization. Design: Vagal stimulation was achieved by using the modified sham feeding (MSF) technique, in which nutrients are chewed and tasted but not swallowed. Ten healthy subjects were studied on 3 separate occasions, 4 wk apart. Five hours after a high-fat breakfast (56 g fat), the subjects were given 1 of 3 test meals allocated in random order: water, a lunch containing a modest amount of fat (38 g), or MSF (38 g fat). Blood was collected for 3 h poststimulus for hormone and metabolite analyses. Results: Plasma insulin and pancreatic polypeptide concentrations peaked at 250% and 209% of baseline concentrations within 15 min of MSF. The plasma glucose concentration increased significantly (P = 0.038) in parallel with the changes observed in the plasma insulin concentration. The nonesterified fatty acid concentration was significantly suppressed (P = 0.006); maximum suppression occurred at a mean time of 114 min after MSF. This fall in nonesterified fatty acid was accompanied by a fall in the plasma glucagon concentration from 122 to 85 pmol/L (P = 0.018) at a mean time of 113 min after MSF. Conclusions: Effects on substrate metabolism after MSF in the postprandial state differ from those usually reported in the postabsorptive state. The effects of MSF were prolonged beyond the period of the cephalic response and these may be relevant for longer-term metabolic regulation.