Automatic expert system based on images for accuracy crop row detection in maize fields

This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.

Fault tolerant embedded systems design by multi-objective optimization

The design of fault tolerant systems is gaining importance in large domains of embedded applications where design constrains are as important as reliability. New software techniques, based on selective application of redundancy, have shown remarkable fault coverage with reduced costs and overheads. However, the large number of different solutions provided by these techniques, and the costly process to assess their reliability, make the design space exploration a very difficult and time-consuming task. This paper proposes the integration of a multi-objective optimization tool with a software hardening environment to perform an automatic design space exploration in the search for the best trade-offs between reliability, cost, and performance. The first tool is commanded by a genetic algorithm which can simultaneously fulfill many design goals thanks to the use of the NSGA-II multi-objective algorithm. The second is a compiler-based infrastructure that automatically produces selective protected (hardened) versions of the software and generates accurate overhead reports and fault coverage estimations. The advantages of our proposal are illustrated by means of a complex and detailed case study involving a typical embedded application, the AES (Advanced Encryption Standard).

Kansas nonmonetary expert system prototype /

"Contract number 99-7-4646-04-142-01."

Organisational learning - a critical systems thinking discipline

Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: j.s.edwards@aston.ac.uk 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.

Linking the witness simulation software to an expert system to represent a decision-making process

Expert systems, and artificial intelligence more generally, can provide a useful means for representing decision-making processes. By linking expert systems software to simulation software an effective means of including these decision-making processes in a simulation model can be achieved. This paper demonstrates how a commercial-off-the-shelf simulation package (Witness) can be linked to an expert systems package (XpertRule) through a Visual Basic interface. The methodology adopted could be used for models, and possibly software, other than those presented here.

An expert system for the development of a health and safety policy/risk assessment in the plastics industry

Health and safety policies may be regarded as the cornerstone for positive prevention of occupational accidents and diseases. The Health and Safety at Work, etc Act 1974 makes it a legal duty for employers to prepare and revise a written statement of a general policy with respect to the health and safety at work of employees as well as the organisation and arrangements for carrying out that policy. Despite their importance and the legal equipment to prepare them, health and safety policies have been found, in a large number of plastics processing companies (particularly small companies), to be poorly prepared, inadequately implemented and monitored. An important cause of these inadequacies is the lack of necessary health and safety knowledge and expertise to prepare, implement and monitor policies. One possible way of remedying this problem is to investigate the feasibility of using computers to develop expert system programs to simulate the health and safety (HS) experts' task of preparing the policies and assisting companies implement and monitor them. Such programs use artificial intelligence (AI) techniques to solve this sort of problems which are heuristic in nature and require symbolic reasoning. Expert systems have been used successfully in a variety of fields such as medicine and engineering. An important phase in the feasibility of development of such systems is the engineering of knowledge which consists of identifying the knowledge required, eliciting, structuring and representing it in an appropriate computer programming language.

Fish farm effluent control and the development of an expert system

In recent years, freshwater fish farmers have come under increasing pressure from the Water Authorities to control the quality of their farm effluents. This project aimed to investigate methods of treating aquacultural effluent in an efficient and cost-effective manner, and to incorporate the knowledge gained into an Expert System which could then be used in an advice service to farmers. From the results of this research it was established that sedimentation and the use of low pollution diets are the only cost effective methods of controlling the quality of fish farm effluents. Settlement has been extensively investigated and it was found that the removal of suspended solids in a settlement pond is only likely to be effective if the inlet solids concentration is in excess of 8 mg/litre. The probability of good settlement can be enhanced by keeping the ratio of length/retention time (a form of mean fluid velocity) below 4.0 metres/minute. The removal of BOD requires inlet solids concentrations in excess of 20 mg/litre to be effective, and this is seldom attained on commercial fish farms. Settlement, generally, does not remove appreciable quantities of ammonia from effluents, but algae can absorb ammonia by nutrient uptake under certain conditions. The use of low pollution, high performance diets gives pollutant yields which are low when compared with published figures obtained by many previous workers. Two Expert Systems were constructed, both of which diagnose possible causes of poor effluent quality on fish farms and suggest solutions. The first system uses knowledge gained from a literature review and the second employs the knowledge obtained from this project's experimental work. Consent details for over 100 fish farms were obtained from the public registers kept by the Water Authorities. Large variations in policy from one Authority to the next were found. These data have been compiled in a computer file for ease of comparison.

An analysis of users' reactions to an expert advisory system

Ignorance of user factors can be seen as one of the nontechnical issues contributing to expert system failure. An expert advisory system is built for nonexpert users; the users' acceptance is a very important factor for its successful implementation. If an expert advisory system satisfactorily represents the expertise in the domain, there still remains the question: "Will the end-users use the system?" This paper aims to address users' issues by analysing their reactions towards an expert advisory system called ADGAME, developed to help its users make better decisions in playing a competitive business game. Two experiments with ADGAME have been carried out. The research results show that, when the use of the expert advisory system is optional, there is considerable reluctance to use it, particularly amongst the "worst" potential users. Users also doubt the potential benefits in terms of improved learning and confidence in decisions made. Strangely, the one positive expectation that users had, that the system would save them time, proved not to be the case in practice; ADGAME appears to improve the users' effectiveness rather than their efficiency. © 1995.

Design and development of logistics workflow systems for demand management with RFID

This paper discusses demand and supply chain management and examines how artificial intelligence techniques and RFID technology can enhance the responsiveness of the logistics workflow. This proposed system is expected to have a significant impact on the performance of logistics networks by virtue of its capabilities to adapt unexpected supply and demand changes in the volatile marketplace with the unique feature of responsiveness with the advanced technology, Radio Frequency Identification (RFID). Recent studies have found that RFID and artificial intelligence techniques drive the development of total solution in logistics industry. Apart from tracking the movement of the goods, RFID is able to play an important role to reflect the inventory level of various distribution areas. In today’s globalized industrial environment, the physical logistics operations and the associated flow of information are the essential elements for companies to realize an efficient logistics workflow scenario. Basically, a flexible logistics workflow, which is characterized by its fast responsiveness in dealing with customer requirements through the integration of various value chain activities, is fundamental to leverage business performance of enterprises. The significance of this research is the demonstration of the synergy of using a combination of advanced technologies to form an integrated system that helps achieve lean and agile logistics workflow.

Self-organization of Functioning Process of Expert System with the Use of Subject Domain Ontology

Optimization of design, creation, functioning and accompaniment processes of expert system is the important problem of artificial intelligence theory and decisions making methods techniques. In this paper the approach to its solving with the use of technology, being based on methodology of systems analysis, ontology of subject domain, principles and methods of self-organisation, is offered. The aspects of such approach realization, being based on construction of accordance between the ontology hierarchical structure and sequence of questions in automated systems for examination, are expounded.

Expert System for Decision-Making Problem in Economics

An expert system (ES) is a class of computer programs developed by researchers in artificial intelligence. In essence, they are programs made up of a set of rules that analyze information about a specific class of problems, as well as provide analysis of the problems, and, depending upon their design, recommend a course of user action in order to implement corrections. ES are computerized tools designed to enhance the quality and availability of knowledge required by decision makers in a wide range of industries. Decision-making is important for the financial institutions involved due to the high level of risk associated with wrong decisions. The process of making decision is complex and unstructured. The existing models for decision-making do not capture the learned knowledge well enough. In this study, we analyze the beneficial aspects of using ES for decision- making process.

Decision–making Support Systems as Personal Intellectual Device of a Decision–maker

The problems of the cognitive development of subject “perception” are discussed in the thesis: from the object being studied and means of action till the single system “subject – modus operandi of subject – object”. Problems of increasing adequacy of models of “live” nature are analyzed. The concept of developing decisionmaking support systems as expert systems to decision-making support systems as personal device of a decisionmaker is discussed. The experience of the development of qualitative prediction on the basis of polyvalent dependences, represented by a decision tree, which realizes the concept of “plural subjective determinism”, is analyzed. The examples of applied systems prediction of ecological-economic and social processes are given. The ways of their development are discussed.

Distances between Predicates in By-Analogy Reasoning Systems

The purpose is to develop expert systems where by-analogy reasoning is used. Knowledge “closeness” problems are known to frequently emerge in such systems if knowledge is represented by different production rules. To determine a degree of closeness for production rules a distance between predicates is introduced. Different types of distances between two predicate value distribution functions are considered when predicates are “true”. Asymptotic features and interrelations of distances are studied. Predicate value distribution functions are found by empirical distribution functions, and a procedure is proposed for this purpose. An adequacy of obtained distribution functions is tested on the basis of the statistical 2 χ –criterion and a testing mechanism is discussed. A theorem, by which a simple procedure of measurement of Euclidean distances between distribution function parameters is substituted for a predicate closeness determination one, is proved for parametric distribution function families. The proposed distance measurement apparatus may be applied in expert systems when reasoning is created by analogy.

Knowledge-based management systems for the police force

Knowledge-Based Management Systems enable new ways to process and analyse knowledge to gain better insights to solve a problem and aid in decision making. In the police force such systems provide a solution for enhancing operations and improving client administration in terms of knowledge management. The main objectives of every police officer is to ensure the security of life and property, promote lawfulness, and avert and distinguish wrongdoing. The administration of knowledge and information is an essential part of policing, and the police ought to be proactive in directing both explicit and implicit knowledge, whilst adding to their abilities in knowledge sharing. In this paper the potential for a knowledge based system for the Mauritius police was analysed, and recommendations were also made, based on requirements captured from interviews with several long standing officers, and surveying of previous works in the area.