Spelling suggestions: "subject:"[een] CASE BASED REASONING"" "subject:"[enn] CASE BASED REASONING""
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Hollywood films, reflective practice, and social change in teacher education : a Bahamian illustrationButler, Faith J. January 2000 (has links)
No description available.
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Eino: An Intelligent Tutor For The University Of Central Florida Infinity Web AppletsHollister, James 01 January 2007 (has links)
This study investigated the various methods involved in creating an intelligent tutor for the University of Central Florida Infinity Web Applets (UCF Infinity Web Applets). After conducting research into various methods, two major methods emerged and they are: solving the problem for the student and helping the student when they become stymied and unable to solve the problem. A storyboard was created to show the interactions of the student and system along with a list of features that were desired to be included in the tutoring system. From the storyboard and list of features, an architecture was created to handle all of the interactions and features. After the initial architecture was designed, the development of the actual system was started. The architecture underwent a multitude of changes to conclude with a working system, EINO. The final architecture of EINO incorporated a case based reasoning system to perform pattern recognition on the student's input into the UCF Infinity Web Applets. The interface that the student interacts with was created using flash. EINO was implemented in three of the labs from the UCF Infinity Web Applets. A series of tests were performed on the EINO tutoring system to prove that the system could actually perform each and every one of the features listed initially. The final test was a simulation of how the EINO would perform under a set of given cases. Test subjects with the same educational level as the target group were chosen to spend an unlimited time using each of the three labs. Each of the test subjects filled out a survey on every lab to determine if the EINO system produced a helpful output.
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Problem Detection for Situation Assessment in Case-Based Reasoning for Diabetes ManagementMiller, Wesley A. 13 August 2009 (has links)
No description available.
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Clinical Evaluation and Enhancement of a Medical Case-Based Decision Support SystemVernier, Stanley J. January 2009 (has links)
No description available.
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CAFixD: A Case-based Reasoning Method for Fixture DesignBoyle, Iain Mackinnon 04 May 2006 (has links)
Fixtures accurately locate and secure a part during machining operations such that the part can be manufactured to design specifications. To reduce the design costs associated with fixturing, various computer-aided fixture design (CAFD) methods have been developed through the years to assist the fixture designer. Much research has been directed towards developing systems that determine an optimal fixture plan layout, but there is still a need to develop a CAFD method that can continue to assist designers at the unit level where the key task is identifying the appropriate structure that the individual units comprising a fixture should take. This research work details the development of a CAFD methodology (called CAFixD) that seeks to fill this hole in the CAFD field. The approach taken is to consider all operational requirements of a fixture problem, and use them to guide the design of a fixture at the unit level. Based upon a case-based reasoning (CBR) methodology where relevant design experience is retrieved and adapted to provide a new fixture design solution, the CAFixD methodology adopts a rigorous approach to indexing design cases in which axiomatic design functional requirement decomposition is adopted. Thus, the design requirement is decomposed in terms of functional requirements, physical solutions are retrieved and adapted for each individual requirement, and the design re-constituted to form a complete fixture design. Case adaptation knowledge is used to guide the retrieval process. Possible adaptation strategies for modifying candidate cases are identified and then evaluated. Case and adaptation strategy combinations that result in adapted designs that best satisfy the preferences of the designer are used as the final design solutions. Possible means of refining the effectiveness of the method include combining adaptation strategies and considering the order in which design decisions are taken.
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Knowledge maintenance of case-based reasoning systems : the SIAM methodology /Roth-Berghofer, Thomas R. January 2003 (has links)
Thesis (doctoral)--Universität Kaiserslautern, 2002. / Includes bibliographical references (p. 219-234) and index.
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Measuring Goal Similarity Using Concept, Context and Task FeaturesEyorokon, Vahid 24 August 2018 (has links)
No description available.
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EN SCHACK AI BASERAD PÅ CASE-BASED REASONING MED GRUNDLIG LIKHET / A CASE-BASED REASONING APPROACH TO A CHESS AI USING SHALLOW SIMILARITYQvarford, Johannes January 2015 (has links)
Schack är ett spel som ofta används för att undersöka olika tekniker inom artificiell intelligens (AI). I det här arbetet ställs frågan om det går att utveckla en AI-agent vars beslutsfattande är baserat på tekniken Case-based Reasoning (CBR) med grundlig likhet som spelar bättre med fallbaser baserade på bättre experter. En AI-agent har utvecklats som spelat ett antal partier mot sig själv med olika fallbaser baserade på olika experter. Efter att ha undersökt resultatet visade de sig att AI-agenten spelar så dåligt att den nästan aldrig lyckades vinna oavsett fallbas, vilket gjorde att det inte gick att rangordna dem efter skicklighet. I framtida arbete är det intressant att undersöka andra likheter än grundlig likhet. Det är även av intresse att undersöka om en CBR-baserad schackspelande AI-agent kan spela schack med hög skicklighet.
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Business case analysis: Learning to think like a physicianAmaya, Zeda Glass 01 January 2006 (has links)
The project introduces and subsequently proposes a novel framework, based on the medical model of diagnosis, to facilitate business students' preparation of case analysis. The project also shows students how to apply the framework in a sample case study.
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Symptombaserad felsökning av tunga fordon : En systematisk metod för att sammankoppla kundsymptom med systemreaktioner / Symptom-based troubleshooting of heavy vehicles : A systematic method for linking customer symptoms with system reactionsTörnqvist, Alexander, Jansson, Jesper January 2020 (has links)
This thesis is about symptom-based troubleshooting of heavy vehicles. The existing troubleshooting system at Scania is adapted to handle errors based on electronic fault codes. This means that some faults, such as mechanical faults when sensors are missing, are difficult to troubleshoot. In the thesis, a method is developed that will be a part of a symptom-based troubleshooting system which can handle all types of errors. The main objectives of the thesis are both to develop a method that can link customer symptoms with system reactions and also to develop formats for both customer symptoms and FMEA for the developed method. In the thesis, a literature study was first conducted in which troubleshooting methods and principles for the formalization of customer data were identified. The identified troubleshooting methods were Bayesian Network, Case-Based-Reasoning and Fault tree analysis. A case study was then conducted which was based on several documents for troubleshooting in gas engines and gas tanks. In the case study, data from the literature study and the empirically collected data were used to develop the final concept of the method. The case study included, among other things, semi-structured interviews to map out the existing troubleshooting process, and a workshop to choose the final concept. In order to meet the objectives of the thesis two research questions and one question linked to the case study were formulated: Research Questions: • RQ1: How is the troubleshooting process affected by the methods that can be used to link customer symptoms with system reactions in heavy vehicles? • RQ2: How can customer data and FMEA be formalized in order to be useful in the troubleshooting process of heavy vehicles? Case Study: • What kind of data is missing from Scania’s existing documentation to link customer symptoms with system reactions? The thesis resulted in a method based on two troubleshooting methods Bayesian network and Case-Based-Reasoning. The method links customer symptoms with system reactions by excluding human considerations and instead relying on previously documented cases and probabilities. A requirement for using this method is a cooperation between customer support, mechanics and development engineers. The formalization of customer symptoms in the developed method is based on what good data is for mechanics in troubleshooting contexts and what customers are capable of communicating; deviation – the customer’s description of the vehicle’s unexpected condition, position – where the customer considers the deviation to be present, context – what happened before, during and after the deviation was discovered. The conclusions that can be drawn is that it is not necessary to link customer symptoms with system reactions since the developed method allows the customer symptoms to be linked directly to the corrective actions needed. In addition, it was noted that the existing documentation at Scania on customer symptoms and system reactions is insufficient. However, this is not problematic as it was shown that FMEA is redundant for the method developed. In order for customer data to be useful, the formalization should include deviation, position and context. Further conclusions are that the role of the customer support becomes less critical when data driven troubleshooting methods are used, and that the accuracy of the developed method will improve over time as more data will be collected. / Detta arbete behandlar symptombaserad felsökning av tunga fordon. Scanias befintliga felsökningssystem är anpassat för att hantera fel som grundas i elektroniska felkoder. Detta innebär att vissa typer av fel, såsom mekaniska fel när sensorer saknas, är svåra att felsöka. I detta arbete utvecklas en metod som ska ingå i ett symptombaserat felsökningssystem eftersom ett sådant system kan hantera alla typer av fel. Målen med arbetet är att utveckla en metod som kan sammankoppla kundsymptom med systemreaktioner, och utveckla format för kundsymptom och FMEA för den framtagna metoden. I arbetet utfördes först en litteraturstudie där felsökningsmetoder och principer för formaliseringen av kunddata identifierades. Felsökningsmetoderna som identifierades var Bayesiska nätvkerk, Case-Based-Reasoning och Felträdsanalys. Därefter utfördes en fallstudie som grundades på underlag om felsökning inom gasmotorer och gastankar. I fallstudien användes data från litteraturstudien och den empiriskt insamlade data för att utveckla det slutgiltiga konceptet. I fallstudien utfördes bland annat semistrukturerade intervjuer för att kartlägga den befintliga felsökningsprocessen, och en workshop för att kunna välja det slutgiltiga konceptet. För att kunna uppfylla arbetets mål formulerades två forskningsfrågor och en frågeställning kopplad till fallstudien: Forskningsfrågor: • F1: Hur påverkas felsökningsprocessen utifrån de metoder som kan användas för att sammankoppla kundsymptom med systemreaktioner inom tunga fordon? • F2: Hur kan kunddata och FMEA formaliseras för att vara användbara inom felsökningsprocessen av tunga fordon? Fallstudie: • Vilken data saknas i Scanias befintliga dokumentation för att kunna sammankoppla kundsymptom med systemreaktioner? Arbetet resulterade i en metod som baseras på de två felsökningsmetoderna Bayesiska nätverk och Case-Based-Reasoning. Metoden sammankopplar kundsymptom med systemreaktioner genom att exkludera mänskligt avvägande och istället förlita sig på tidigare dokumenterade fall och sannolikhet. En förutsättning för att metoden ska kunna användas är ett samarbete mellan kundmottagare, mekaniker och utvecklingsingenjörer. Formaliseringen av kundsymptom i den framtagna metoden bygger på vad bra data är för mekaniker i felsökningssammanhang och vad kunderna är kapabla att förmedla; avvikelse – kundens beskrivning av fordonets oväntade tillstånd, position – var anser kunden att avvikelsen förekommer, kontext – vad hände innan, under och efter att avvikelsen upptäcktes. Slutsatserna som kan dras utifrån arbetet är att det inte är nödvändigt att sammankoppla kundsymptom med systemreaktioner, utan kundsymptom kan sammankopplas direkt med åtgärder med den framtagna metoden. Dessutom noterades det att den befintliga dokumentationen hos Scania angående kundsymptom och systemreaktioner är bristfällig. Detta är inte problematiskt då det påvisades att FMEA inte är nödvändig för att metoden ska fungera. För att kunddata ska vara användbart bör formaliseringen ske med avvikelse, position och kontext. Ytterligare slutsatser är att kundmottagarrollen blir mindre kritisk när datadrivna felsökningsmetoder används, och att den framtagna metodens träffsäkerhet kommer att förbättras över tid allt eftersom mer data har samlats in.
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