Artificial keys for botanical identification using a multilayer perceptron neural network (MLP)

In this paper, practical generation of identification keys for biological taxa using a multilayer perceptron neural network is described. Unlike conventional expert systems, this method does not require an expert for key generation, but is merely based on recordings of observed character states. Like a human taxonomist, its judgement is based on experience, and it is therefore capable of generalized identification of taxa. An initial study involving identification of three species of Iris with greater than 90% confidence is presented here. In addition, the horticulturally significant genus Lithops (Aizoaceae/Mesembryanthemaceae), popular with enthusiasts of succulent plants, is used as a more practical example, because of the difficulty of generation of a conventional key to species, and the existence of a relatively recent monograph. It is demonstrated that such an Artificial Neural Network Key (ANNKEY) can identify more than half (52.9%) of the species in this genus, after training with representative data, even though data for one character is completely missing.

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.

Proof of concept of automated mapping of weeds in arable fields

The project investigated whether it would be possible to remove the main technical hindrance to precision application of herbicides to arable crops in the UK, namely creating geo-referenced weed maps for each field. The ultimate goal is an information system so that agronomists and farmers can plan precision weed control and create spraying maps. The project focussed on black-grass in wheat, but research was also carried out on barley and beans and on wild-oats, barren brome, rye-grass, cleavers and thistles which form stable patches in arable fields. Farmers may also make special efforts to control them. Using cameras mounted on farm machinery, the project explored the feasibility of automating the process of mapping black-grass in fields. Geo-referenced images were captured from June to December 2009, using sprayers, a tractor, combine harvesters and on foot. Cameras were mounted on the sprayer boom, on windows or on top of tractor and combine cabs and images were captured with a range of vibration levels and at speeds up to 20 km h-1. For acceptability to farmers, it was important that every image containing black-grass was classified as containing black-grass; false negatives are highly undesirable. The software algorithms recorded no false negatives in sample images analysed to date, although some black-grass heads were unclassified and there were also false positives. The density of black-grass heads per unit area estimated by machine vision increased as a linear function of the actual density with a mean detection rate of 47% of black-grass heads in sample images at T3 within a density range of 13 to 1230 heads m-2. A final part of the project was to create geo-referenced weed maps using software written in previous HGCA-funded projects and two examples show that geo-location by machine vision compares well with manually-mapped weed patches. The consortium therefore demonstrated for the first time the feasibility of using a GPS-linked computer-controlled camera system mounted on farm machinery (tractor, sprayer or combine) to geo-reference black-grass in winter wheat between black-grass head emergence and seed shedding.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

Exit strategies for business tenants

Many businesses in the UK occupy premises on fixed term leases, which usually run for several years. During this time property requirements can change. This research critically examines the three main mechanisms by which tenants can bring their leases to an end; breaks, assignment and subletting. We examine the legal rules governing these devices and undertake an analysis of lease data and surveys. Break clauses are providing a useful exit mechanism for many tenants, but they cannot give the more general flexibility of assignment and subletting. However, change is necessary to ensure that these latter provisions provide real flexibility for tenants.

Do small business tenants need protecting in commercial lease negotiations?

This paper sets out the findings relating to small business tenants of a major UK Government funded study into the commercial and industrial property landlord and tenant relationship. The UK Government is concerned that small business tenants do not appreciate many of the implications of signing leases, which in the UK are generally longer than in most other countries of the world. The objectives of the paper are to identify the characteristics of leases in the UK and any differences between those signed by small, medium and larger companies. It also examines the negotiation process and identifies whether small business tenant negotiations exhibit different characteristics. The findings are that small business tenants occupy on different terms to larger tenants including shorter terms and that the negotiation process is also different. Many small business tenants are unrepresented at the commercial stage of negotiations and take the first terms on offer. They are largely unaware of attempts to make them more informed by voluntary industry Codes of Practice. This can lead to small business tenants being unaware of the implications of certain terms within leases, hence the continuing Government concern over the issue.

Are property agents to blame for upward only rent reviews?

In negotiating commercial leases, many landlords and tenants employ property agents (brokers) to act on their behalf; typically these people are chartered surveyors. The aim of this paper is to explore the role that these brokers play in the shaping of commercial leases in the context of the current debate in the UK on upward only rent reviews. This role can be described using agency theory and the theories of professionalism. These provide expectations of behaviour which show inherent tensions between the role of agent and professional, particularly regarding the use of knowledge, autonomy and the obligation to the public interest. The parties to eleven recent lease transactions were interviewed to see if the brokers conformed to the expectations of agency theory or professionalism. Brokers that acted for industrial and office tenants behaved as professionals in using their expertise to determine lease structures. However, those acting for landlords and retail tenants simply followed instructions and behaved as conduits for their clients, a role more usually associated with that of an agent within the principal-agent relationship. None of the landlords’ brokers saw themselves as having responsibilities beyond their clients and so they were not promoting the discussion of alternatives to the UORR. The evidence from these case studies suggests that agents are not professionals; to behave entirely as an agent is to contradict the essential characteristics of a professional. While brokers cannot be held entirely responsible for the lack of movement on the UORR, by adopting predominantly agent roles then they must take some of the blame. However, behind this may be a much larger issue that needs to be explored; the institutional pressures that lead to professionals behaving in this way.

Influences on secured lending property valuations in the UK

A significant part of bank lending in the UK is secured on commercial property and valuations play an important part in this process. They are an integral part of risk management within the banking sector. It is therefore important that valuations are independent and objective and are used properly to ensure that secured lending is soundly based from the perspective of both lender and borrower. The purpose of this research is to examine objectivity and transparency in the valuation process for bank lending and to identify any influences which may undermine the process. A detailed analysis of 31 valuation negligence cases has been followed by two focus groups of lenders and valuers and also questionnaire surveys of commercial lenders and valuers. Many stakeholders exist, for example lenders, borrowers and brokers, who are able to influence the process in various ways. The strongest evidence of overt influence in the process comes from the method of valuer selection with borrowers and brokers seen to be heavily involved. There is some also some evidence of influence during the draft valuation process. A significant minority of valuers feel that inappropriate pressure is applied by borrowers and brokers yet there is no apparent part of the process that leads to this. The panel system employed by lenders is found to be a significant part of the system and merits further examination. The pressure felt by valuers needs more investigation along with the question of if and how the process could dispel such feelings. This is seen as particularly important in the context of bank regulation.