Analysing Similarity in Exam Timetabling

In this paper we carry out an investigation of some of the major features of exam timetabling problems with a view to developing a similarity measure. This similarity measure will be used within a case-based reasoning (CBR) system to match a new problem with one from a case-based of previously solved problems. The case base will also store the heuristic for meta-heuristic techniques applied most successfully to each problem stored. The technique(s) stored with the matched case will be retrieved and applied to the new case. The CBR assumption in our system is that similar problems can be solved equally well by the same technique.

Analysing Similarity in Exam Timetabling

In this paper we carry out an investigation of some of the major features of exam timetabling problems with a view to developing a similarity measure. This similarity measure will be used within a case-based reasoning (CBR) system to match a new problem with one from a case-based of previously solved problems. The case base will also store the heuristic for meta-heuristic techniques applied most successfully to each problem stored. The technique(s) stored with the matched case will be retrieved and applied to the new case. The CBR assumption in our system is that similar problems can be solved equally well by the same technique.

Enhancing student learning with case-based teaching and audience response systems in an interdisciplinary Food Science course

A growing body of research in higher education suggests that teachers should move away from traditional lecturing towards more active and student-focus education approaches. Several classroom techniques are available to engage students and achieve more effective teaching and better learning experiences. The purpose of this paper is to share an example of how two of them – case-based teaching, and the use of response technologies – were implemented into a graduate-level food science course. The paper focuses in particular on teaching sensory science and sensometrics, including several concrete examples used during the course, and discussing in each case some of the observed outcomes. Overall, it was observed that the particular initiatives were effective in engaging student participation and promoting a more active way of learning. Case-base teaching provided students with the opportunity to apply their knowledge and their analytical skills to complex, real-life scenarios relevant to the subject matter. The use of audience response systems further facilitated class discussion, and was extremely well received by the students, providing a more enjoyable classroom experience.

A Case-Based Approach to Nosocomial Infection Detection

The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.

Healthcare Computer Reasoning Addressing Chronically Ill Societies Using IoT: Deep Learning AI to the Rescue of Home-Based Healthcare

The authors present a proposal to develop intelligent assisted living environments for home based healthcare. These environments unite the chronical patient clinical history sematic representation with the ability of monitoring the living conditions and events recurring to a fully managed Semantic Web of Things (SWoT). Several levels of acquired knowledge and the case based reasoning that is possible by knowledge representation of the health-disease history and acquisition of the scientific evidence will deliver, through various voice based natural interfaces, the adequate support systems for disease auto management but prominently by activating the less differentiated caregiver for any specific need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.

A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.

An Artificial Intelligence Approach to Individuals' Age Assessment

A link between patterns of pelvic growth and human life history is supported by the finding that, cross-culturally, variation in maturation rates of female pelvis are correlated with variation in ages of menarche and first reproduction, i.e., it is well known that the human dimensions of the pelvic bones depend on the gender and vary with the age. Indeed, one feature in which humans appear to be unique is the prolonged growth of the pelvis after the age of sexual maturity. Both the total superoinferior length and mediolateral breadth of the pelvis continues to grow markedly after puberty, and do not reach adult proportions until the late teens years. This continuation of growth is accomplished by relatively late fusion of the separate centers of ossification that form the bones of the pelvis. Hence, in this work we will focus on the development of an intelligent decision support system to predict individual’s age based on a pelvis' dimensions criteria. Some basic image processing techniques were applied in order to extract the relevant features from pelvic X-rays, being the computational framework built on top of a Logic Programming approach to Knowledge Representation and Reasoning that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

Trip to Sunshine Coast Queensland, September 2004 visit to bridge and foreshore

A trip was undertaken to look at concerns of Public Works and Main Roads Departments of Queensland. David Paterson and Wayne Ganther from CSIRO travelled to the Sunshine Coast with Alan Carse of Queensland Department of Main Roads and Michael Ball of Queensland Department of Public Works. We were also joined for part of the visits by Ed Bowers of QBuild which is a commercial unit of Public Works responsible for maintenance of Public Works. During the trip we visited a bridge on the David Low Way at Sunrise Beach near Noosa. This bridge was in a serve marine environment with high salt content in the concrete and corrosion of the galvanised guardrails and barriers. Also the foreshore at Coolum was visited and the use of stainless steel was examined. This is discussed in this report. Most problems stemmed from incorrect specification due to lack of awareness of the severity of the environment. The companion report Visit to Schools Report 2002-059-B No 7. covers the visit to four schools north of Caloundra.

Preliminary report on data mining techniques for life prediction

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source. In the initial software, no attempt was made to choose between the results offered or construct a case for retention in the casebase. In this phase of the project, alternative data mining techniques will be explored and evaluated. A process for selecting a unique service life prediction for each query will also be investigated. This report summarises the initial evaluation of several data mining techniques.

Report : holistic model modifications for selected building elements

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source.

Developing a hybrid expert system program to aid in the design of plastic injection molding process

Experts in injection molding often refer to previous solutions to find a mold design similar to the current mold and use previous successful molding process parameters with intuitive adjustment and modification as a start for the new molding application. This approach saves a substantial amount of time and cost in experimental based corrective actions which are required in order to reach optimum molding conditions. A Case-Based Reasoning (CBR) System can perform the same task by retrieving a similar case which is applied to the new case from the case library and uses the modification rules to adapt a solution to the new case. Therefore, a CBR System can simulate human e~pertise in injection molding process design. This research is aimed at developing an interactive Hybrid Expert System to reduce expert dependency needed on the production floor. The Hybrid Expert System (HES) is comprised of CBR, flow analysis, post-processor and trouble shooting systems. The HES can provide the first set of operating parameters in order to achieve moldability condition and producing moldings free of stress cracks and warpage. In this work C++ programming language is used to implement the expert system. The Case-Based Reasoning sub-system is constructed to derive the optimum magnitude of process parameters in the cavity. Toward this end the Flow Analysis sub-system is employed to calculate the pressure drop and temperature difference in the feed system to determine the required magnitude of parameters at the nozzle. The Post-Processor is implemented to convert the molding parameters to machine setting parameters. The parameters designed by HES are implemented using the injection molding machine. In the presence of any molding defect, a trouble shooting subsystem can determine which combination of process parameters must be changed iii during the process to deal with possible variations. Constraints in relation to the application of this HES are as follows. - flow length (L) constraint: 40 mm < L < I 00 mm, - flow thickness (Th) constraint: -flow type: - material types: I mm < Th < 4 mm, unidirectional flow, High Impact Polystyrene (HIPS) and Acrylic. In order to test the HES, experiments were conducted and satisfactory results were obtained.

Developing Co-operating Legal Knowledge Based Systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work supplements rule-based reasoning with case based reasoning and intelligent information retrieval. This research, specifies an approach to the case based retrieval problem which relies heavily on an extended object-oriented / rule-based system architecture that is supplemented with causal background information. Machine learning techniques and a distributed agent architecture are used to help simulate the reasoning process of lawyers. In this paper, we outline our implementation of the hybrid IKBALS II Rule Based Reasoning / Case Based Reasoning system. It makes extensive use of an automated case representation editor and background information.