Case-based reasoning is one of the fastest growing areas in the field of knowledge-based systems and this book, authored by a leader in the field, is the first comprehensive text on the subject. Case-based reasoning systems are systems that store information about situations in their memory. As new problems arise, similar situations are searched out to help solve these problems. Problems are understood and inferences are made by finding the closest cases in memory, comparing and contrasting the problem with those cases, making inferences based on those comparisons, and asking questions whe
Riesbeck, Christopher K
Introducing issues in dynamic memory and case-based reasoning, this comprehensive volume presents extended descriptions of four major programming efforts conducted at Yale during the past several years. Each descriptive chapter is followed by a companion chapter containing the micro program version of the information. The authors emphasize that the only true way to learn and understand any AI program is to program it yourself. To this end, the book develops a deeper and richer understanding of the content through LISP programming instructions that allow the running, modification, and
Shaker H. El-Sappagh
Full Text Available Case Based Reasoning (CBR is an important technique in artificial intelligence, which has been applied to various kinds of problems in a wide range of domains. Selecting case representation formalism is critical for the proper operation of the overall CBR system. In this paper, we survey and evaluate all of the existing case representation methodologies. Moreover, the case retrieval and future challenges for effective CBR are explained. Case representation methods are grouped in to knowledge-intensive approaches and traditional approaches. The first group overweight the second one. The first methods depend on ontology and enhance all CBR processes including case representation, retrieval, storage, and adaptation. By using a proposed set of qualitative metrics, the existing methods based on ontology for case representation are studied and evaluated in details. All these systems have limitations. No approach exceeds 53% of the specified metrics. The results of the survey explain the current limitations of CBR systems. It shows that ontology usage in case representation needs improvements to achieve semantic representation and semantic retrieval in CBR system.
Case-based reasoning is a methodology with a long tradition in artificial intelligence that brings together reasoning and machine learning techniques to solve problems based on past experiences or cases. Given a problem to be solved, reasoning involves the use of methods to retrieve similar past cases in order to reuse their solution for the problem at hand. Once the problem has been solved, learning methods can be applied to improve the knowledge based on past experiences. In spite of being a broad methodology applied in industry and services, case-based reasoning has often been forgotten in
Full Text Available In this paper, we propose a fuzzy case-based reasoning system, using a case-based reasoning (CBR system that learns from experience to solve problems. Different from a traditional case-based reasoning system that uses crisp cases, our system works with fuzzy ones. Specifically, we change a crisp case into a fuzzy one by fuzzifying each crisp case element (feature, according to the maximum degree principle. Thus, we add the “vague” concept into a case-based reasoning system. It is these somewhat vague inputs that make the outcomes of the prediction more meaningful and accurate, which illustrates that it is not necessarily helpful when we always create accurate predictive relations through crisp cases. Finally, we prove this and apply this model to practical weather forecasting, and experiments show that using fuzzy cases can make some prediction results more accurate than using crisp cases.
Case-based reasoning paradigms offer automatic reasoning capabilities which are useful for the implementation of human like machines in a limited sense. This research book is the second volume in a series devoted to presenting Case-based reasoning (CBR) applications. The first volume, published in 2010, testified the flexibility of CBR, and its applicability in all those fields where experiential knowledge is available. This second volume further witnesses the heterogeneity of the domains in which CBR can be exploited, but also reveals some common directions that are clearly emerging in recent years. This book will prove useful to the application engineers, scientists, professors and students who wish to develop successful case-based reasoning applications.
Cordier, Amélie; Fuchs, Béatrice; Lieber, Jean; Mille, Alain
International audience In Case Based Reasoning (CBR), knowledge acquisition plays an important role as it allows to progressively improve the system's competencies. One of the approaches of knowledge acquisition consists in performing it while the system is used to solve a problem. An advantage of this strategy is that it is not to constraining for the expert: the system exploits its interactions to acquire pieces of knowledge it needs to solve the current problem and takes the opportunity...
Hinkle, David; Toomey, Christopher
CLAVIER is a case-based reasoning (CBR) system that assists in determining efficient loads of composite material parts to be cured in an autoclave. CLAVIER's central purpose is to find the most appropriate groupings and configurations of parts (or loads) to maximize autoclave throughput yet ensure that parts are properly cured. CLAVIER uses CBR to match a list of parts that need to be cured against a library of previously successful loads and suggest the most appropriate next load. clavier al...
Case-based reasoning (CBR) is a kind of analogous reasoning that is widely used in artificial intelligence. Conflicts are pervasive in Concurrent Engineering design environment. Conflict negotiation is necessary when conflicts occur. It is difficult to resolve conflicts due to several reasons. An approach to resolving conflicts by case-based reasoning is proposed in this paper. The knowledge representation of conflict negotiation cases, the judgment of case similarity, the retrieval model of cases, the management of case bases, and the process of case-based conflict negotiation are studied. The implementation structure of the Case-based Conflict Solving System (CCSS) is also given.
This article presents an example of estimating costs in the early phase of the project using fuzzy case-based reasoning. The fragment of database containing descriptions and unit cost of sports facilities was shown. The formulas used in Case Based Reasoning method were presented, too. The article presents similarity measurement using a few formulas, including fuzzy similarity. The outcome of cost calculations based on CBR method was presented as a fuzzy number of unit cost of construction work.
Martha Dunia Delgado Dapena
Full Text Available This paper presents a proposal for storage structure and retrieval mechanisms used for implementing case-based reasoning (CBR in generating functional test procedures in software projects. This proposal was based on software project t functional requirements and sets out the proposed algorithms for considering the similarity between each pair of projects as well as those leading to adapting the solution found in the case base.
Martha Dunia Delgado Dapena; Yucely López Trujillo; Indira Chávez Valiente
This paper presents a proposal for storage structure and retrieval mechanisms used for implementing case-based reasoning (CBR) in generating functional test procedures in software projects. This proposal was based on software project t functional requirements and sets out the proposed algorithms for considering the similarity between each pair of projects as well as those leading to adapting the solution found in the case base.
Jurisica, Igor; Glasgow, Janice
Case-based reasoning (CBR) is a computational reasoning paradigm that involves the storage and retrieval of past experiences to solve novel problems. It is an approach that is particularly relevant in scientific domains, where there is a wealth of data but often a lack of theories or general principles. This article describes several CBR systems that have been developed to carry out planning, analysis, and prediction in the domain of molecular biology.
Full Text Available Requirement elicitation is very difficult process in highly challenging and business based software as well as in real time software. Common problems associated with these types of software are rapidly changing the requirements and understanding the language of the layman person. In this study, a framework for requirement elicitation by using knowledge based system is proposed, which is very helpful for knowledge documentation, intelligent decision support, self-learning and more specifically it is very helpful for case based reasoning and explanation. Basically in this method requirements are gathered from Artificial Intelligence (AI expert system from various sources e.g., via interviews, scenarios or use cases. Then, these are converted into structured natural language using ontology and this new problem/case is put forward to Case Based Reasoning (CBR. CBR based on its previous information having similar requirements combines with new case and suggests a proposed solution. Based on this solution a prototype is developed and delivered to customer. The use of case-based reasoning in requirements elicitation process has greatly reduced the burden and saved time of requirement analyst and results in an effective solution for handling complex or vague requirements during the elicitation process.
ROENTGEN is a design assistant for radiation therapy planning which uses case-based reasoning, an artificial intelligence technique. It learns both from specific problem-solving experiences and from direct instruction from the user. The first sort of learning is the normal case-based method of storing problem solutions so that they can be reused. The second sort is necessary because ROENTGEN does not, initially, have an internal model of the physics of its problem domain. This dependence on e...
Taylor, Bruce; Robertson, David; Wiratunga, Nirmalie; Craw, Susan; Mitchell, Dawn; Stewart, Elaine
Community occupational therapists have long been involved in the provision of environmental control systems. Diverse electronic technologies with the potential to improve the health and quality of life of selected clients have developed rapidly in recent years. Occupational therapists employ clinical reasoning in order to determine the most appropriate technology to meet the needs of individual clients. This paper describes a number of the drivers that may increase the adoption of information and communication technologies in the occupational therapy profession. It outlines case based reasoning as understood in the domains of expert systems and knowledge management and presents the preliminary results of an ongoing investigation into the potential of a prototype computer aided case based reasoning tool to support the clinical reasoning of community occupational therapists in the process of assisting clients to choose home electronic assistive or smart house technology. PMID:17576021
夏利民; 杨宝娟; 涂宏斌
A novel method case-based reasoning was proposed for suspicious behavior recognition. The method is composed of three departs: human behavior decomposition, human behavior case representation and case-based reasoning. The new approach was proposed to decompose behavior into sub-behaviors that are easier to recognize using a saliency-based visual attention model. New representation of behavior was introduced, in which the sub-behavior and the associated time characteristic of sub-behavior were used to represent behavior case. In the process of case-based reasoning, apart from considering the similarity of basic sub-behaviors, order factor was proposed to measure the similarity of a time order among the sub-behaviors and span factor was used to measure the similarity of duration time of each sub-behavior, which makes the similarity calculations more rational and comprehensive. Experimental results show the effectiveness of the proposed method in comparison with other related works and can run in real-time for the recognition of suspicious behaviors.
Metamorphic virus employs code obfuscation techniques to mutate itself. It absconds from signaturebaseddetection system by modifying internal structure without compromising original functionality.In this paper, we propose a new method, for detecting metamorphic computer viruses, that is based on thetechnique of Case-Based Reasoning (CBR). In this method:-Can detect similar viruses with high probability.- The updating of the virus database is done automatically without connecting to the Intern...
The work in this thesis presents an approach towards the effective monitoring of business processes using Case-Based Reasoning (CBR). The rationale behind this research was that business processes constitute a fundamental concept of the modern world and there is a constantly emerging need for their efficient control. They can be efficiently represented but not necessarily monitored and diagnosed effectively via an appropriate platform. Motivated by the above observation this research purs...
Full Text Available The treatment of complex systems often requires the manipulation of vague, imprecise and uncertain information. Indeed, the human being is c ompetent in handling of such systems in a natural way. Instead of thinking in mathematical te rms, humans describes the behavior of the system by language proposals. In order to represent this type of information, Zadeh proposed to model the mechanism of human thought by approximate reasoning based on linguistic variables. He introduced the theory of fuzzy sets i n 1965, which provides an interface between language and digital worlds. In this paper, we prop ose a Boolean modeling of the fuzzy reasoning that we baptized Fuzzy-BML and uses the c haracteristics of induction graph classification. Fuzzy-BML is the process by which t he retrieval phase of a CBR is modelled not in the conventional form of mathematical equations, but in the form of a database with membership functions of fuzzy rules.
T omas Olsson
Full Text Available This paper describes a generic fram e w ork for e xplaining the prediction of probabilistic machine learning algorithms using cases. The fram e w ork consists of t w o components: a similarity metric between cases th at is defined relat i v e to a probability model and an n ov el case - based approach to justifying the probabilistic prediction by estimating the prediction error using case - based reasoning. As basis for der i ving similarity metrics, we define similarity in terms of the principle of inte r c han g eability that t w o cases are considered similar or identical if t w o probability distri b utions, der i v ed from e xcluding either one or the other case in the case base, are identical. Lastl y , we sh o w the applicability of the propo sed approach by der i ving a metric for linear r e gression, and apply the proposed approach for e xplaining predictions of the ene r gy performance of households
The typical antivirus approach consists of waiting for a number of computers to be infected, detecting the virus, designing a solution, delivering and deploying a solution. In such a situation, it is very difficult to prevent every machine from being compromised by viruses. In this paper, we propose a new method, for detecting computer viruses, that is based on the technique of Case-Based Reasoning (CBR). In this method: (1) even new viruses that do not exist in the database can be detected (...
Pulaski, Kirt; Casadaban, Cyprian
The coupling of data and knowledge has a synergistic effect when building an intelligent data base. The goal is to integrate the data and knowledge almost to the point of indistinguishability, permitting them to be used interchangeably. Examples given in this paper suggest that Case-Based Reasoning is a more integrated way to link data and knowledge than pure rule-based reasoning.
Full Text Available The typical antivirus approach consists of waiting for a number of computers to be infected, detecting the virus, designing a solution, delivering and deploying a solution. In such a situation, it is very difficult to prevent every machine from being compromised by viruses. In this paper, we propose a new method, for detecting computer viruses, that is based on the technique of Case-Based Reasoning (CBR. In this method: (1 even new viruses that do not exist in the database can be detected (2 The updating of the virus database is done automatically without connecting to the Internet. Whenever a new virus is detected, it will be automatically added to the database used by our application. This presents a major advantage
Vilhena, João; Vicente, Henrique; Martins, M Rosário; Grañeda, José M; Caldeira, Filomena; Gusmão, Rodrigo; Neves, João; Neves, José
Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states that increase the risk of venous and arterial thromboses. Indeed, venous thromboembolism is often a chronic illness, mainly in deep venous thrombosis and pulmonary embolism, requiring lifelong prevention strategies. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a logic programming approach to knowledge representation and reasoning, complemented with a case-based approach to computing. The proposed model has been quite accurate in the assessment of thrombophilia predisposition risk, since the overall accuracy is higher than 90% and sensitivity ranging in the interval [86.5%, 88.1%]. The main strength of the proposed solution is the ability to deal explicitly with incomplete, unknown, or even self-contradictory information. PMID:27404848
Full Text Available Obtaining competitive quotations from suitably qualified subcontractors at tender tim n significantly increase the chance of w1nmng a construction project. Amidst an increasingly growing trend to subcontracting in Australia, selecting appropriate subcontractors for a construction project can be a daunting task requiring the analysis of complex and dynamic criteria such as past performance, suitable experience, track record of competitive pricing, financial stability and so on. Subcontractor selection is plagued with uncertainty and vagueness and these conditions are difficul_t o represent in generalised sets of rules. DeciSIOns pertaining to the selection of subcontr:act?s tender time are usually based on the mtu1t1onand past experience of construction estimators. Case-based reasoning (CBR may be an appropriate method of addressing the chal_lenges of selecting subcontractors because CBR 1s able to harness the experiential knowledge of practitioners. This paper reviews the practicality and suitability of a CBR approach for subcontractor tender selection through the development of a prototype CBR procurement advisory system. In this system, subcontractor selection cases are represented by a set of attributes elicited from experienced construction estimators. The results indicate that CBR can enhance the appropriateness of the selection of subcontractors for construction projects.
Zhanbo LEI; Yoshiyasu YAMADA; Jihong HUANG; Youmin XI
Case-based reasoning (CBR) is an important reasoning technique of expert system. In this paper, the authors introduce CBR to intelligent early-warning support system, which could warn quantitatively for enterprise financial crisis and could warn qualitatively by expert's knowledge and experience. Furthermore, genetic algorithm is applied to case-based reasoning in CBR-IEWSS, which improves accuracy and efficiency of case retrieval. Last, the structure of CBR-IEWSS is given.
Sara Esfandiari; Behrooz Masoumi; Mohammadreza Meybodi; Abdolkarim Niazi
In this paper, a new algorithm based on case base reasoning and reinforcement learning is proposed to increase the rate convergence of the Selfish Q-Learning algorithms in multi-agent systems. In the propose method, we investigate how making improved action selection in reinforcement learning (RL) algorithm. In the proposed method, the new combined model using case base reasoning systems and a new optimized function has been proposed to select the action, which has led to an increase in algor...
LI Wen-hong; SUN Shao-wen; ZHANG Qi
A mechinery fault diagnosis expert system based on case-based reasoning (CBR) technology was established. The process of the CBR fault diagnosis is analyzed from three main aspects: expression and memory, retrieving and matching, and modification and maintenance of a case. The results indicate that the CBR method is flexible and simple to implement, and it has strong self-studying ability. Using a large enough number of case reasoning sets, it can accumulate the experience of problem solving, avoid the difficulty of knowledge acquisition, shorten the course of solving problems, improve efficiency of reasoning, and save the time of developing.
Even today, with modern medicine and technology, post-operative pain still exists as anmajor issue in modern treatment. A lot of research efforts have been made, in order toimprove pain outcome for patients that has undergone surgery.Even though physician's and doctors are well educated, the success rate is aboutapproximately 70 %, still there are patients that experience severe pain, after they haveundergone surgery. There could be several reasons to this, for example, lack of method...
López de Mántaras, Ramon; Spanish National Research Council (CSIC)
This paper surveys significant research on the problem of rendering expressive music by means of AI techniques with an emphasis on Case-Based Reasoning. Following a brief overview discussing why we prefer listening to expressive music instead of lifeless synthesized music, we examine a representative selection of well-known approaches to expressive computer music performance with an emphasis on AI-related approaches. In the main part of the paper we focus on the existing CBR approaches to the...
Full Text Available This study proposes a retinopathy prediction system based on data mining,particularly association rules using Apriori algorithm, and case-based reasoning. The association rules are used to analyse patterns in the data set and to calculate retinopathy probability whereas case-based reasoning is used to retrieve similar cases. This paper discusses the proposed system. It is believed that great improvements can be provided to medical practitioners and also to diabetics with the implementation of this system.
In this thesis, novel Case-Based Reasoning (CBR) methods were developed to be included in CBRDP (Case-Based Reasoning Dose Planner) -an adaptive decision support system for radiotherapy dose planning. CBR is an artificial intelligence methodology which solves new problems by retrieving solutions to previously solved similar problems stored in a case base. The focus of this research is on dose planning for prostate cancer patients. The records of patients successfully treated in the Nottingham...
Collaborative commerce (c-commerce) has become an innovative business paradigm that helps companies achieve high operational performance through inter-organizational collaboration. This paper presents an effective case-based reasoning (CBR) capability model for solution selection in c-commerce applications, as CBR is widely used in knowledge management and electronic commerce.Based on the case-based competence model suggested by Smyth and McKenna, a directed graph was used to represent the collaborative reasoning history of CBR systems, where information of reasoning process ability was extracted. Experiment was carried out on a travel dataset. By integrating case-based competence and reasoning process ability, the capability is more suitable to reflect the real ability of CBR systems. The result shows that the proposed method can effectively evaluate the capability of CBR systems and enhance the performance of collaborative case-based reasoning in c-commerce environment.
Full Text Available In this paper, a new algorithm based on case base reasoning and reinforcement learning is proposed to increase the rate convergence of the Selfish Q-Learning algorithms in multi-agent systems. In the propose method, we investigate how making improved action selection in reinforcement learning (RL algorithm. In the proposed method, the new combined model using case base reasoning systems and a new optimized function has been proposed to select the action, which has led to an increase in algorithms based on Selfish Q-learning. The algorithm mentioned has been used for solving the problem of cooperative Markovs games as one of the models of Markov based multi-agent systems. The results of experiments on two ground have shown that the proposed algorithm perform better than the existing algorithms in terms of speed and accuracy of reaching the optimal policy.
De Loor, Pierre; Pierre, Chevaillier; 10.1016/j.eswa.2010.10.048
The aim of this paper is to present the principles and results about case-based reasoning adapted to real- time interactive simulations, more precisely concerning retrieval mechanisms. The article begins by introducing the constraints involved in interactive multiagent-based simulations. The second section pre- sents a framework stemming from case-based reasoning by autonomous agents. Each agent uses a case base of local situations and, from this base, it can choose an action in order to interact with other auton- omous agents or users' avatars. We illustrate this framework with an example dedicated to the study of dynamic situations in football. We then go on to address the difficulties of conducting such simulations in real-time and propose a model for case and for case base. Using generic agents and adequate case base structure associated with a dedicated recall algorithm, we improve retrieval performance under time pressure compared to classic CBR techniques. We present some results relating to the perfor...
Speicher, Timothy E.; Bell, Alexandra; Kehrhahn, Marijke; Casa, Douglas J.
Context: One of the most common instructional methods utilized to promote learning transfer in health profession education is examination of a single patient case. However, in non-healthcare settings this practice has shown to be less effective in promoting learning than the examination of multiple cases with cueing. Objective(s): The primary…
Marryam Murtaza; Jamal Hussain Shah; Aisha Azeem; Wasif Nisar; Maria Masood
Requirement elicitation is very difficult process in highly challenging and business based software as well as in real time software. Common problems associated with these types of software are rapidly changing the requirements and understanding the language of the layman person. In this study, a framework for requirement elicitation by using knowledge based system is proposed, which is very helpful for knowledge documentation, intelligent decision support, self-learning and more specifically...
Full Text Available In the Security Department Computing ETECSA through diagnostic matrices or checklists, the audit process is performed to Database Management Systems. After completing the monitoring of DBMS, experts determine the risk level of information security in terms of High, Medium and Low. The use of artificial intelligence technique Reasoning Case-Based, for use in the analysis phase of evaluation of the risk of security of the information to take advantage of the experience gained in previous audits of this type is proposed. He leaned on ETECSA specialists in determining the features that make the vector cases. The incorporation of Reasoning Case-Based technique to support the analysis of information security audits managers’ database, streamlines the process and helps in the analysis of risks to information security auditors.
Talib, Amir Mohamed; Elshaiekh, Nour Eldin Mohamed
Cloud Computing is a new technology which use the Internet and central remote servers in order to maintain data and applications. The aim of this paper is to describe about Case Based Reasoning (CBR) which is based on Multi Agent System (MAS) and the implementation in Cloud Computing Environment to assist the Cloud Service Provider (CSP) to deliver a number of services to the cloud users according to their needs. The Introduction Section gives an introduction about Cloud Computing, MAS and CB...
Ben Mustapha, Nesrine; Baazaoui, Hajer; Aufaure, Marie-Aude; Ben Ghezala, Henda
International audience In this paper, we present a semantic search approach based on Case-based reasoning and modular Ontology learning. A case is defined by a set of similar queries associated with its relevant results. The case base is used for ontology learning and for contextualizing the search process. Modular ontologies are designed to be used for case representation and indexing. Our work aims at improving ontology-based information retrieval by the integration of the traditional in...
The purpose of this study was to determine if a case-based reasoning tool would improve a student's understanding of the complex concepts in a Java programming course. Subjects for the study were randomly assigned from two sections of an introductory Java programming course. Posttests were used to measure the effects of the case-based reasoning…
LI Hong-bo; TAN Shu-kui; ZHONG Hai-feng
To establish the institutional mechanism for land conflict coordination in China, a case-based reasoning system is developed as an intelligent support and effective manner to resolve such issues. The establishment of the case library is discussed, previous land conflict cases are archived in a structural representation format for retrieval, and the similarity algorithm is adopted to compare the case features. Group tests show a good classification performance, which reveals that the system is feasible.
Human beings solve problems according to their experiences. Case-based reasoning (CBR) is a problem solving method which simulates the process of problem solving of human beings. CBR is applied various problems in engineering field. However, CBR has not been applied to the LP optimization problem so far. In this study, CBR is applied to LP optimizations and its performance is compared with Simulated Annealing (SA) and Tabu search (TS). From the results, it is demonstrated that CBR optimizes a LP faster than SA and TS. The performance of a LP that is obtained by CBR is slightly worse than that of SA and TS, but the difference of performance of LP among CBR, SA and TS is small. This indicates that CBR is a very effective method for fast and reasonable LP optimization. (author)
Full Text Available Accurate software cost estimation is a vital task that affects the firm's software investment decisions before committing required resources to that project or bidding for a contract. This study proposes an improved Case-Based Reasoning (CBR approach integrated with multi-agent technology to retrieve similar projects from multi-organizational distributed datasets. The study explores the possibility of building a software cost estimation model by collecting software cost data from distributed predefined project cost databases. The model applying CBR method to find similar projects in historical data derived from measured software projects developed by different organizations.
Pinkus, Rosa Lynn; Gloeckner, Claire; Fortunato, Angela
The use of case-based reasoning in teaching professional ethics has come of age. The fields of medicine, engineering, and business all have incorporated ethics case studies into leading textbooks and journal articles, as well as undergraduate and graduate professional ethics courses. The most recent guidelines from the National Institutes of Health recognize case studies and face-to-face discussion as best practices to be included in training programs for the Responsible Conduct of Research. While there is a general consensus that case studies play a central role in the teaching of professional ethics, there is still much to be learned regarding how professionals learn ethics using case-based reasoning. Cases take many forms, and there are a variety of ways to write them and use them in teaching. This paper reports the results of a study designed to investigate one of the issues in teaching case-based ethics: the role of one's professional knowledge in learning methods of moral reasoning. Using a novel assessment instrument, we compared case studies written and analyzed by three groups of students whom we classified as: (1) Experts in a research domain in bioengineering. (2) Novices in a research domain in bioengineering. (3) The non-research group--students using an engineering domain in which they were interested but had no in-depth knowledge. This study demonstrates that a student's level of understanding of a professional knowledge domain plays a significant role in learning moral reasoning skills. PMID:25820218
Full Text Available Early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through appropriate treatment; thus classifying cardiac signals will be helped to immediate diagnosing of heart beat type in cardiac patients. The present paper utilizes the case base reasoning (CBR for classification of ECG signals. Four types of ECG beats (normal beat, congestive heart failure beat, ventricular tachyarrhythmia beat and atrial fibrillation beat obtained from the PhysioBank database was classified by the proposed CBR model. The main purpose of this article is classifying heart signals and diagnosing the type of heart beat in cardiac patients that in proposed CBR (Case Base Reasoning system, Training and testing data for diagnosing and classifying types of heart beat have been used. The evaluation results from the model are shown that the proposed model has high accuracy in classifying heart signals and helps to clinical decisions for diagnosing the type of heart beat in cardiac patients which indeed has high impact on diagnosing the type of heart beat aided computer.
Mehdi Neshat; Mehdi Sargolzaei; Adel Nadjaran Toosi; Azra Masoumi
Correct diagnosis of a disease is one of the most important problems in medicine. Hepatitis disease is one of the most dangerous diseases that affect millions of people every year and take man’s life. In this paper, the combination of two methods of PSO and CBR (case-based reasoning) has been used to diagnose hepatitis disease. First, a case-based reasoning method is workable to preprocess the data set therefore a weight vector for every one feature is extracted. A particle swarm optimization...
ZHAO Chunhua; WU Zhengjia; ZHOU Chengjun; ZHU Dalin; LI Haoping
Computer aided process planning system played a key role for integrating design and manufacturing or assembly systems properly considering available resources and design constraints. To take advantage of the enterprise resource, the web CAPP framework was established. Case based reasoning and multi agent system were integrated in the system. The multi agent mechanism was discussed in the paper. And an instance of case base was introduced. They made the system run independently and continuously in the network environment of process planning problems.
Tan, Verily; Kou, Xiaojing
This study proposes the use of case-based reasoning to help educators design with Web 2.0. Principles for designing a web-enhanced case-based activity (CBA) were used to design an online professional development course for a group of 16 in-service educators. The Learning in Context model was used as a scaffold to help participants in their design…
Slope is a non-linear and uncertain kinetic system affected by many factors. In view of the incompleteness and uncertainty of the information of slope stability evaluation, a new method of slope stability evaluation by using case-based reasoning is presented. Considering the sensitivity of attribute weights to the environment, the algorithm of attribute weights is set up on the basis of the concept of changeable weights. Calculating the similarity between target case of the slope and base case, the stability of target case is evaluated. It is shown from examples that the method is simple, visual, practical, and convenient for use.
S. Dutta (Shantanu); B. Wierenga (Berend); A. Dalebout
textabstractOver the past decade, case-based reasoning (CBR) has emerged as a major research area within the artificial intelligence research field due to both its widespread usage by humans and its appeal as a methodology for building intelligent systems. Conventional CBR systems have been largely
Research and practice in human performance technology (HPT) has recently accelerated the search for innovative approaches to supplement or replace traditional training interventions for improving organizational performance. This article examines a knowledge management framework built upon the theories and techniques of case-based reasoning (CBR)…
Moura, Elionai; Cunha, José António; Analide, Cesar
This paper introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, s...
Fidjeland, Mikael Kirkeby
The Semantic Web is an emerging framework for data reuse and sharing. By giving data clear semantics it allows for machine processing of this information. The Semantic Web technologies range from simple meta data to domain models using the Web Ontology Languge (OWL). Much of the semantics of OWL stems from the Knowledge Representation field of Description Logics. Case-Based Reasoning (CBR) uses specific knowledge in the form of cases to solve problems. The Creek system is a Knowledge-Intens...
Full Text Available A knowledge-based society determines organizations to focus their activities on improving management quality by using knowledge. Huge data stores become important once the real significance of data is discovered. Data mining techniques are involved in different knowledge processes, as one can notice in various public applications of the researchers. Managers can use these techniques in order to extract patterns, relations, associations from data initially considered of little value. Over the past decade, case-based reasoning (CBR has emerged as a major research area within the artificial intelligence research field due to both its widespread usage by humans and its appeal as a methodology for building intelligent systems. More recently, there has been a search for new paradigms and directions for increasing the utility of CBR systems for decision support. This paper focuses on the synergism between the research areas of Data Mining, CBR System, Multi-agent System and decision support systems (DSSs. A conceptual framework for DSSs based on MAS using DM and CBRS is presented. Nowadays, intelligent agents represent an important opportunity to optimize knowledge management. The research implications of the evolution in the design of DSS based on MAS using DM and CBR systems from automation toward decision-aiding is also explored.
Liane Mahlmann Kipper
Full Text Available This paper introduces the development process of a knowledge management system built to support decision making processes. This study takes into account different topics as knowledge, intellectual capital, strategies used by companies and a system using case based reasoning techniques. Artificial Intelligence was applied in order to meet the challenges of making knowledge part of the company's culture through Case Based Reasoning (CBR. The proposal developed in this study was applied in the business sector of a company. This action offered the organization detailed analysis of the results, helping the managers to make strategic decisions. Three tools were created and adapted in order to make this application possible and distinguished, they are: linear range of interest for each attribute, drawing of a symmetric matrix of similarity and definition table with values compiled per attributes. This allowed them to have a significant improvement in the accuracy of real-time information, helping to make decisions and generating effective results.
Dong, Ruihai; Schaal, Markus; O'Mahony, Michael P.; Smyth, Barry
Today, online reviews for products and services have become an important class of user-generated content and they play a valuable role for countless online businesses by helping to convert casual browsers into informed and satisfied buyers. As users gravitate towards sites that offer insightful and objective reviews, the ability to source helpful reviews from a community of users is increasingly important. In this extended abstract we describe the Reviewer’s Assistant, a case-based reasoning ...
Applying high-speed machining technology in shop floor has many benefits, such as manufacturing more accurate parts with better surface finishes. The selection of the appropriate machining parameters plays a very important role in the implementation of high-speed machining technology. The case-based reasoning is used in the developing of high-speed machining database to overcome the shortage of available high-speed cutting parameters in machining data handbooks and shop floors. The high-speed machining data...
This research study focused on learning lessons from the experience of designing a comprehensive case-based reasoning (CBR) tool for support of complex thinking skills. Theorists have historically identified, analyzed, and classified different thinking processes and skills. Thinking skills have been increasingly emphasized in national standards, state testing, curricula, teaching and learning resources, and research agendas. Complex thinking is the core of higher-order thinking. Complex think...
Smyth, Barry; Cunningham, Padraig; Keane, Mark T.
Case-based reasoning (CBR) is an AI technique that emphasises the role of past experience during future problem solving. New problems are solved by retrieving and adapting the solutions to similar problems, solutions that have been stored and indexed for future reuse as cases in a case-base. The power of CBR is severely curtailed if problem solving is limited to the retrieval and adaptation of a single case, and for this reason the strategy of reusing multiple cases is immediately...
Many approaches used for diagnostics today are based on a precise model. This excludes diagnostics of many complex types of machinery that cannot be modelled and simulated easily or without great effort. Our aim is to show that by including human experience it is possible to diagnose complex machinery when there is no or limited models or simulations available. This also enables diagnostics in a dynamic application where conditions change and new cases are often added. In fact every new solved case increases the diagnostic power of the system. We present a number of successful projects where we have used feature extraction together with case-based reasoning to diagnose faults in industrial robots, welding, cutting machinery and we also present our latest project for diagnosing transmissions by combining Case-Based Reasoning (CBR) with statistics. We view the fault diagnosis process as three consecutive steps. In the first step, sensor fault signals from machines and/or input from human operators are collected. Then, the second step consists of extracting relevant fault features. In the final diagnosis/prognosis step, status and faults are identified and classified. We view prognosis as a special case of diagnosis where the prognosis module predicts a stream of future features.
Cobb, Corie L.; Zhang, Ying; Agogino, Alice M.
A case-based reasoning (CBR) knowledge base has been incorporated into a Micro-Electro-Mechanical Systems (MEMS) design tool that uses a multi-objective genetic algorithm (MOGA) to synthesize and optimize conceptual designs. CBR utilizes previously successful MEMS designs and sub-assemblies as building blocks stored in an indexed case library, which serves as the knowledge base for the synthesis process. Designs in the case library are represented in a parameterized object-oriented format, incorporating MEMS domain knowledge into the design synthesis loop as well as restrictions for the genetic operations of mutation and crossover for MOGA optimization. Reasoning tools locate cases in the design library with solved problems similar to the current design problem and suggest promising conceptual designs which have the potential to be starting design populations for a MOGA evolutionary optimization process, to further generate more MEMS designs concepts. Surface micro-machined resonators are used as an example to introduce this integrated MEMS design synthesis process. The results of testing on resonator case studies demonstrate how the combination of CBR and MOGA synthesis tools can help increase the number of optimal design concepts presented to MEMS designers.
Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa
Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.
Musa Bala Shuaibu
Full Text Available Fraud cases are significantly causing huge revenue losses in telecommunication companies around the world. Although previous cases are very important data in dealing with fraud patterns, there are variations in the dataset of different fraud case scenarios which in turns need specific detection system without necessarily involving the domain expert directly. This paper investigates the appropriate weight values for attributes using fraud Call Rate Data that is based on Artificial Intelligence technique (Case Based Reasoning with a meaningful confidence in telecommunication data. The experimental result on the fraud data reports that the weight for all attribute used in this study needs to be set at 0.9 in order to get the best performance of 98.33%.
Makoto, Takahashi [Tohoku University, Miyagi (Japan); Akio, Gofuku [Okayama University, Okayamaa (Japan)
Case-based diagnostic technique has been developed based on the multi-attribute similarity. Specific feature of the developed system is to use multiple attributes of process signals for similarity evaluation to retrieve a similar case stored in a case base. The present technique has been applied to the measurement data from Monju with some simulated anomalies. The results of numerical experiments showed that the present technique can be utilizes as one of the methods for a hybrid-type diagnosis system.
HOU Jun-ming; SU Chong; LIANG Shuang; WANG Wan-shan
Collaborative design is a new style for modern mechanical design to meet the requirement of increasing competition. Designers of different places complete the same work, but the conflict appears in the process of design which may interface the design. Case-based reasoning (CBR) method is applied to the problem of conflict resolution, which is in the artificial intelligence field. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures of CBR, it is very difficult to find the similar cases from case database. A fuzzy CBR method was proposed to solve the problem of conflict resolution in collaborative design. The process of fuzzy CBR was introduced. Based on the feature attributes and their relative weights determined by a fuzzy technique, a fuzzy CBR retrieving mechanism was developed to retrieve conflict resolution cases that tend to enhance the functions of the database. By indexing, calculating the weight and defuzzicating of the cases, the case similarity can be obtained. Then the case consistency was measured to keep the right result. Finally, the fuzzy CBR method for conflict resolution was demonstrated by means of a case study. The prototype system based on web is developed to illustrate the methodology.
The automotive engine performance tune-up is greatly affected by the calibration of its electronic control unit (ECU). The ECU calibration is traditionally done by trial-and-error method. This traditional method consumes a large amount of time and money because of a large number of dynamometer tests. To resolve this problem, case based reasoning (CBR) is employed, so that an existing and effective ECU setup can be adapted to fit another similar class of engines. The adaptation procedure is done through a more sophisticated step called case-based adaptation (CBA)[1, 2]. CBA is an effective knowledge management tool, which can interactively learn the expert adaptation knowledge. The paper briefly reviews the methodologies of CBR and CBA. Then the application to ECU calibration is described via a case study. With CBR and CBA, the efficiency of calibrating an ECU can be enhanced. A prototype system has also been developed to verify the usefulness of CBR in ECU calibration.
Directly calculating the topological and geometric complexity from the STEP (standard for the exchange of product model data, ISO 10303) file is a huge task. So, a case-based reasoning approach is presented, which is based on the similarity between the new component and the old one, to calculate the topological and geometric complexity of new components. In order to index, retrieve in historical component database, a new way of component representation is brought forth. And then an algorithm is given to extract topological graph from its STEP files. A mathematical model, which describes how to compare the similarity, is discussed. Finally, an example is given to show the result.
Gauthier, Geneviève; Lajoie, Susanne P.
To explore the assessment challenge related to case based learning we study how experienced clinical teachers--i.e., those who regularly teach and assess case-based learning--conceptualize the notion of competent reasoning performance for specific teaching cases. Through an in-depth qualitative case study of five expert teachers, we investigate…
Full Text Available Bayesian network has the abilities of probability expression, uncertainty management and multi-information fusion.It can support emergency decision-making, which can improve the efficiency of decision-making.Emergency decision-making is highly time sensitive, which requires shortening the Bayesian Network modeling time as far as possible.Traditional Bayesian network modeling methods are clearly unable to meet that requirement.Thus, a Bayesian network modeling method based on case reasoning for emergency decision-making is proposed.The method can obtain optional cases through case matching by the functions of similarity degree and deviation degree.Then,new Bayesian network can be built through case adjustment by case merging and pruning.An example is presented to illustrate and test the proposed method.The result shows that the method does not have a huge search space or need sample data.The only requirement is the collection of expert knowledge and historical case models.Compared with traditional methods, the proposed method can reuse historical case models, which can reduce the modeling time and improve the efficiency.
Full Text Available Conventional face-to-face classrooms are still the main learning system applied in Indonesia. In assisting such conventional learning towards an optimal learning, formative evaluations are needed to monitor the progress of the class. This task can be very hard when the size of the class is large. Hence, this research attempted to create a classroom monitoring system based on student’s data of Department of Electrical Engineering and Information Technology UGM. In order to achieve the goal, a student modeling using Case-Based Reasoning (CBR was proposed. A generic student model based on jCOLIBRI 2.3 framework was developed. The model represented student’s knowledge of a subject. The result showed that the system was able to store and retrieve student’s data for suggestion of the current situation and formative evaluation for one of the subject in the Department.
The aim of this thesis is the design of a faults diagnosis-aiding system in a nuclear facility of the Cea. Actually the existing system allows the optimization of the production processes in regular operating conditions. Meanwhile during accidental events, the alarms, managed by threshold, are bringing no relevant information. To increase the reliability and the safety, the human operator needs a faults diagnosis-aiding system. The developed system, SECAPI, combines problem solving techniques and automatic learning techniques, that allow the diagnosis and the the simulation of various faults happening on nuclear facilities. Its reasoning principle uses case-based and rules-based techniques. SECAPI owns a learning module which reads out knowledge connected with faults. It can then simulate various faults, using the inductive logical computing. SECAPI has been applied on a radioactive tritium treatment operating channel, at the Cea with good results. (A.L.B.)
The authors reports the development of the EquiVox platform, the aim of which is to allow a radioprotection expert (physician, biologist or other) to work with a phantom which will be the closest possible to the examined person in order to make an as precise as possible dosimetric assessment. The objective is to help to select the best phantom among those the expert knows depending on the assessment type he wants to make. First, they present the general principles of the case-based reasoning, and then the EquiVox platform which proposes all the steps: formalization, elaboration, comparison, and so on. Based on typical numerical values associated with different morphological characteristics, they present and discuss graphical results obtained by the platform. They also discuss their validity and reliability
Cabrera, Mariana Maceiras
This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the implementation of the adaptation stage, from the integration of Case Based Reasoning and Rule Based Expert Systems. In this adaptation stage we use a higher level RBC that stores and allows reutilizing change experiences, combined with a classic rule-based inference engine. In order to take into account the most evident clinical situation, a pre-diagnosis stage is implemented using a rule engine that, given an evident situation, emits the corresponding diagnosis and avoids the complete process.
Full Text Available Across Latin America 420 indigenous languages are spoken. Spanish is considered a second language in indigenous communities and is progressively introduced in education. However, most of the tools to support teaching processes of a second language have been developed for the most common languages such as English, French, German, Italian, etc. As a result, only a small amount of learning objects and authoring tools have been developed for indigenous people considering the specific needs of their population. This paper introduces Multilingual–Tiny as a web authoring tool to support the virtual experience of indigenous students and teachers when they are creating learning objects in indigenous languages or in Spanish language, in particular, when they have to deal with the grammatical structures of Spanish. Multilingual–Tiny has a module based on the Case-based Reasoning technique to provide recommendations in real time when teachers and students write texts in Spanish. An experiment was performed in order to compare some local similarity functions to retrieve cases from the case library taking into account the grammatical structures. As a result we found the similarity function with the best performance
Yan Liu; Ting-Hua Yi; Zhen-Jun Xu
As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The ...
Mohamed M. Marzouk
Full Text Available The effective estimation of costs is crucial to the success of construction projects. Cost estimates are used to evaluate, approve and/or fund projects. Organizations use some form of classification system to identify the various types of estimates that may be prepared during the lifecycle of a project. This research presents a parametric-cost model for pump station projects. Fourteen factors have been identified as important to the influence of the cost of pump station projects. A data set that consists of forty-four pump station projects (fifteen water and twenty-nine waste water are collected to build a Case-Based Reasoning (CBR library and to test its performance. The results obtained from the CBR tool are processed and adopted to improve the accuracy of the results. A numerical example is presented to demonstrate the development of the effectiveness of the tool.
The paper presents a Case-Based Reasoning Tool for Breast Cancer Knowledge Management to improve breast cancer screening. To develop this tool, we combine both concepts and techniques of Case-Based Reasoning (CBR) and Data Mining (DM). Physicians and radiologists ground their diagnosis on their expertise (past experience) based on clinical cases. Case-Based Reasoning is the process of solving new problems based on the solutions of similar past problems and structured as cases. CBR is suitable for medical use. On the other hand, existing traditional hospital information systems (HIS), Radiological Information Systems (RIS) and Picture Archiving Information Systems (PACS) don't allow managing efficiently medical information because of its complexity and heterogeneity. Data Mining is the process of mining information from a data set and transform it into an understandable structure for further use. Combining CBR to Data Mining techniques will facilitate diagnosis and decision-making of medical experts.
HU Xiao,WANG Zhaodong,; WANG Guodong
New generation thermo-mechanical control process(TMCP) based on ultra-fast cooling is being widely adopted in plate mill to product high-performance steel material at low cost. Ultra-fast cooling system is complex because of optimizing the temperature control error generated by heat transfer mathematical model and process parameters. In order to simplify the system and improve the temperature control precision in ultra-fast cooling process, several existing models of case-based reasoning(CBR) model are reviewed. Combining with ultra-fast cooling process, a developed R5 CBR model is proposed, which mainly improves the case representation, similarity relation and retrieval module. Certainty factor is defined in semantics memory unit of plate case which provides not only internal data reliability but also product performance reliability. Similarity relation is improved by defined power index similarity membership function. Retrieval process is simplified and retrieval efficiency is improved apparently by windmill retrieval algorithm. The proposed CBR model is used for predicting the case of cooling strategy and its capability is superior to traditional process model. In order to perform comprehensive investigations on ultra-fast cooling process, different steel plates are considered for the experiment. The validation experiment and industrial production of proposed CBR model are carried out, which demonstrated that finish cooling temperature(FCT) error is controlled within±25℃ and quality rate of product is more than 97%. The proposed CBR model can simplify ultra-fast cooling system and give quality performance for steel product.
The likelihood ratio (LR) is an optimal approach for deciding which of two alternate hypotheses best describes a given situation. We adopted this formalism for predicting whether biopsy results of mammographic masses will be benign or malignant, aiming to reduce the number of biopsies performed on benign lesions. We compared the performance of this LR-based algorithm (LRb) to a case-based reasoning (CBR) classifier, which provides a solution to a new problem using past similar cases. Each classifier used mammographers' BI-RADSTM descriptions of mammographic masses as input. The database consisted of 646 biopsy-proven mammography cases. Performance was evaluated using Receiver Operating Characteristic (ROC) analysis, Round Robin sampling, and bootstrap. The ROC areas (AUC) for the LRb and CBR were 0.91±0.01 and 0.92±0.01, respectively. The partial ROC area index (0.90AUC) was the same for both classifiers, 0.59±0.05. At a sensitivity of 98%, the CBR would spare 204 (49%) of benign lesions from biopsy; the LRb would spare 209 (51%) benign lesions. The performance of the two classifiers was very similar, with no statistical differences in AUC or 0.90AUC. Although the CBR and LRb originate from different fields of study, their implementations differ only in the estimation of the probability density functions (PDFs) of the feature distributions. The CBR performs this estimation implicitly, while using various similarity metrics. On the other hand, the estimation of the PDFs is specified explicitly in the LRb implementation. This difference in the estimation of the PDFs results in the very small difference in performance, and at 98% sensitivity, both classifiers would spare about half of the benign mammographic masses from biopsy. The CBR and LRb are equivalent methods in implementation and performance
Zarea Gavgani Vahideh; Hazrati Hakime; Ghojazadeh Mortaza
Introduction: In medical and clinical education, creating critical thinking and promoting clinical reasoning abilities are the highest aims and results of education. The main aim of this study was to assess the efficacy of digital case scenarios versus print/paper case scenarios on clinical reasoning in problem-based learning (PBL). If a study used the multimedia scenario case interventions, video case scenarios and online-guided scenarios as digital case PBL, we would cons...
Full Text Available As it is well known, the characterization of knowledge in termsof “Justified True Belief” (JTB has been deemed unsuccessful since the popularization of Gettier-type counterexamples. This paper revisits Gettier’s seminal work and examines his arguments carefully. It holds that Gettier counterexamples are based on unwarranted substitution moves; that one of his arguments seems persuasive because it conflates syntactic validity with semantic truth; that for such reasons his case is weaker than it appears; and that there is, in fact, an avenue for escape open to the supporter of JTB. In short,I shall contend that Gettier’s cases are not genuine counterexamples to thestandard characterization of knowledge in terms of JTB and that, consequently,such characterization is not seriously affected.
Petrovic, Sanja; Qu, Rong
This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and the case base. Experimental results are analysed and related research issues for future work are dis...
Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai
This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. PMID:26133480
De la Torre Vega, H. Octavio; Garcia Tevillo, Arturo; Campuzano Martinez, Roberto [Instituto de Investigaciones Electricas, Temixco, Morelos (Mexico); Lopez Azamar, Ernesto [Comision Federal de Electricidad (Mexico)
The development of a system for the diagnosis of electrical generators that apply techniques of artificial intelligence, is presented, as it is the reasoning based on cases, to support the work of the diagnosis engineer. This system is part of a system called CADIS, dedicated to the diagnosis of electrical generators out of line and reason of previous articles. In this occasion the characteristics of the reasoning module based on experiences (SirBE) are emphasized, indicating how to make a diagnosis using similar cases and how to edit the system base of experience, using the interactive editor of cases. It is included, in addition, a summarized example which represents a case for SirBE and how the system helps to make a diagnosis. [Spanish] Se presenta el desarrollo de un sistema de diagnostico de generadores electricos que aplica tecnicas de inteligencia artificial, como es el razonamiento basado en casos, para apoyar la labor del ingeniero de diagnostico. Este sistema es parte de un sistema denominado CADIS, dedicado al diagnostico de generadores electricos fuera de linea y motivo de articulos anteriores. En esta ocasion se resaltan las caracteristicas del modulo de razonamiento basado en experiencias (SirBE), indicando como realizar un diagnostico utilizando casos similares y como editar la base de experiencia del sistema utilizando el editor interactivo de casos. Se incluye, ademas, un ejemplo resumido de lo que representa un caso para SiRBE y como el sistema ayuda a realizar un diagnostico.
Full Text Available Emotional cellular (EC, proposed in our previous works, is a kind of semantic cell that contains kernel and shell and the kernel is formalized by a triple- L = , where P denotes a typical set of positive examples relative to word-L, d is a pseudodistance measure on emotional two-dimensional space: valence-arousal, and δ is a probability density function on positive real number field. The basic idea of EC model is to assume that the neighborhood radius of each semantic concept is uncertain, and this uncertainty will be measured by one-dimensional density function δ. In this paper, product form features were evaluated by using ECs and to establish the product style database, fuzzy case based reasoning (FCBR model under a defined similarity measurement based on fuzzy nearest neighbors (FNN incorporating EC was applied to extract product styles. A mathematical formalized inference system for product style was also proposed, and it also includes uncertainty measurement tool emotional cellular. A case study of style acquisition of mobile phones illustrated the effectiveness of the proposed methodology.
Stranieri, Andrew; Yearwood, John; Pham, Binh
The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.
Healy, Matt, (Thesis); Delany, Sarah Jane; Zamolotskikh, Anton
Message classification is a text classification task that has provoked much interest in machine learning. One aspect of message classification that presents a particular challenge is the classification of short text messages. This paper presents an assessment of applying a case based approach that was developed for long text messages (specifically spam filtering) to short text messages. The evaluation involves determining the most appropriate feature types and feature representation for short...
Santana, Gustavo A.; Velazquez C, David [Mexican Oil Institute, Mexico DF (Mexico)
A system that applies a method of knowledge-intensive case-based reasoning, for repair and prevention of unwanted events in the domain of offshore oil well drilling, has been developed in cooperation with an oil company. From several reoccurring problems during oil well drilling the problem of 'lost circulation', i.e. loss of circulating drilling fluid into the geological formation, was picked out as a pilot problem. An extensive general knowledge model was developed for the domain of oil well drilling. Different cases were created on the basis of information from one Mexican Gulf operator. When the completed CBR-system was tested against a new case, cases with descending similarity were selected by the tool. In an informal evaluation, the two best fitting cases proved to give the operator valuable advise on how to go about solving the new case (author)
Recently, plant construction industries are enjoying a favorable business climate centering around developing countries and oil producing countries rich in oil money. This paper proposes a methodology of implementing corporation-wide case-based reasoning (CBR) system for effectively managing lessons learned knowledge like experiences and know-how obtained in performing power plant construction projects. Our methodology is consisted of 10 steps: user requirement analysis, information modeling, case modeling, case base design, similarity function design, user interface design, case base building, CBR module development, user interface development, integration test. Also, to illustrate the usability of proposed methodology, the practical CBR system is implemented for the plant construction business division of ’H’ company which has international competitiveness in the field of plant construction industry. At present, our CBR system is successfully utilizing as storing, sharing, and reusing the knowledge which is accumulated in performing power plant construction projects in the target enterprise.
Ifenthaler, Dirk; Seel, Norbert M.
In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper…
Full Text Available As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR, this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods’ effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.
Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun
As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established. PMID:24191134
Ruiz, Magda; Sin, Gürkan; Berjaga, Xavier;
, MPCA is used to reduce the multi-dimensional nature of online process data, which summarises most of the variance of the process data in a few (new) variables. Next, the outputs of MPCA (t-scores, Q-statistic) are provided as inputs (descriptors) to the CBR method, which is employed to identify......The main idea of this paper is to develop a methodology for process monitoring, fault detection and predictive diagnosis of a WasteWater Treatment Plant (WWTP). To achieve this goal, a combination of Multiway Principal Component Analysis (MPCA) and Case-Based Reasoning (CBR) is proposed. First...
Gomez, Fernando; Segami, Carlos
A representation formalism for N-ary relations, quantification, and definition of concepts is described. Three types of conditions are associated with the concepts: (1) necessary and sufficient properties, (2) contingent properties, and (3) necessary properties. Also explained is how complex chains of inferences can be accomplished by representing existentially quantified sentences, and concepts denoted by restrictive relative clauses as classification hierarchies. The representation structures that make possible the inferences are explained first, followed by the reasoning algorithms that draw the inferences from the knowledge structures. All the ideas explained have been implemented and are part of the information retrieval component of a program called Snowy. An appendix contains a brief session with the program.
Addressing socioscientific issues (SSI) has been one of the main focuses in science education since the Science, Technology, and Society (STS) movement in the 1970s (Levinson, 2006); however, teaching controversial socioscientific issues has always been challenging for teachers (Dillon, 1994; Osborne, Duschl, & Fairbrother, 2002). Although teachers exhibit positive attitudes for using controversial socioscientific issues in their science classrooms, only a small percentage of them actually incorporate SSI content into their science curricula on a regular basis (Sadler, Amirshokoohi, Kazempour, & Allspaw, 2006; Lee & Witz, 2009). The literature in science education has highlighted the signi?cant relationships among teacher beliefs, teaching practices, and student learning (Bryan & Atwater, 2002; King, Shumow, & Lietz, 2001; Lederman, 1992). Despite the fact that the case studies present a relatively detailed picture of teachers' values and motivations for teaching SSI (e.g. Lee, 2006; Lee & Witz, 2009; Reis & Galvao, 2004), these studies still miss the practices of these teachers and potential outcomes for their students. Therefore, there is a great need for in-depth case studies that would focus on teachers' practices of designing and teaching SSI-based learning environments, their deeper beliefs and motivations for teaching SSI, and their students' response to these practices (Lee, 2006). This dissertation is structured as three separate, but related, studies about secondary school teachers' experiences of designing and teaching SSI-based classes and their students' understanding of science and SSI reasoning. The case studies in this dissertation seek answers for (1) teachers' practices of designing and teaching SSI-based instruction, as well as its relation to their deeper personal beliefs and motivations to teach SSI, and (2) how their students respond to their approaches of teaching SSI in terms of their science understanding and SSI reasoning. The first paper
The study is from a base of accident scenarii in rail transport (feedback) in order to develop a tool to share build and sustain knowledge and safety and secondly to exploit the knowledge stored to prevent the reproduction of accidents / incidents. This tool should ultimately lead to the proposal of prevention and protection measures to minimize the risk level of a new transport system and thus to improve safety. The approach to achieving this goal largely depends on the use of artificial intelligence techniques and rarely the use of a method of automatic learning in order to develop a feasibility model of a software tool based on case based reasoning (CBR) to exploit stored knowledge in order to create know-how that can help stimulate domain experts in the task of analysis, evaluation and certification of a new system.
Vilstrup Pedersen, Klaus
Intelligence, Knowledge Management Systems and Business Intelligence to make context sensitive, patient case specific analysis and knowledge management. The knowledge base consists of patient health records, reasoning process information and clinical guidelines. Patient specific information and knowledge is...... paper a framework for a Clinical Reasoning Knowledge Warehouse (CRKW) is presented, intended to support the reasoning process, by providing the decision participants with an analysis platform that captures and enhances information and knowledge. The CRKW mixes theories and models from Artificial...... continually enhanced by adding results of analysis. Context sensitive analysis is done by retrieving similar patient cases and guidelines from the knowledge base in a case based fashion....
Janthong, Nattawut; BRISSAUD Daniel; Butdee, Suthep
Current market environments are volatile and unpredictable. The ability for design products to meet customer's requirements has become critical to success. The key element to develop such products is identifying functional requirements and knowledge utilization based on a scientific approach to provide both designers of new products and redesigners of existing products with a suitable solution that meets to customer's needs. This paper presents a method to (re)design mechatronic products by c...
Shahina Begum; Shaibal Barua; Mobyen Uddin Ahmed
Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classificati...
Ruiz, Magda; Sin, Gürkan; Berjaga, Xavier; Colprim, Jesús; Puig, Sebastià; Colomer, Joan
The main idea of this paper is to develop a methodology for process monitoring, fault detection and predictive diagnosis of a WasteWater Treatment Plant (WWTP). To achieve this goal, a combination of Multiway Principal Component Analysis (MPCA) and Case-Based Reasoning (CBR) is proposed. First, MPCA is used to reduce the multi-dimensional nature of online process data, which summarises most of the variance of the process data in a few (new) variables. Next, the outputs of MPCA (t-scores, Q-statistic) are provided as inputs (descriptors) to the CBR method, which is employed to identify problems and propose appropriate solutions (hence diagnosis) based on previously stored cases. The methodology is evaluated on a pilot-scale SBR performing nitrogen, phosphorus and COD removal and to help to diagnose abnormal situations in the process operation. Finally, it is believed that the methodology is a promising tool for automatic diagnosis and real-time warning, which can be used for daily management of plant operation. PMID:22335109
Koo, Choongwan; Hong, Taehoon; Lee, Minhyun; Park, Hyo Seon
The photovoltaic (PV) system is considered an unlimited source of clean energy, whose amount of electricity generation changes according to the monthly average daily solar radiation (MADSR). It is revealed that the MADSR distribution in South Korea has very diverse patterns due to the country's climatic and geographical characteristics. This study aimed to develop a MADSR estimation model for the location without the measured MADSR data, using an advanced case based reasoning (CBR) model, which is a hybrid methodology combining CBR with artificial neural network, multiregression analysis, and genetic algorithm. The average prediction accuracy of the advanced CBR model was very high at 95.69%, and the standard deviation of the prediction accuracy was 3.67%, showing a significant improvement in prediction accuracy and consistency. A case study was conducted to verify the proposed model. The proposed model could be useful for owner or construction manager in charge of determining whether or not to introduce the PV system and where to install it. Also, it would benefit contractors in a competitive bidding process to accurately estimate the electricity generation of the PV system in advance and to conduct an economic and environmental feasibility study from the life cycle perspective. PMID:23548030
Full Text Available This paper proposes an automatic method for detecting landslides by using an integrated approach comprising object-oriented image analysis (OOIA, a genetic algorithm (GA, and a case-based reasoning (CBR technique. It consists of three main phases: (1 image processing and multi-image segmentation; (2 feature optimization; and (3 detecting landslides. The proposed approach was employed in a fast-growing urban region, the Pearl River Delta in South China. The results of detection were validated with the help of field surveys. The experimental results indicated that the proposed OOIA-GA-CBR (0.87 demonstrates higher classification performance than the stand-alone OOIA (0.75 method for detecting landslides. The area under curve (AUC value was also higher than that of the simple OOIA, indicating the high efficiency of the proposed landslide detection approach. The case library created using the integrated model can be reused for time-independent analysis, thus rendering our approach superior in comparison to other traditional methods, such as the maximum likelihood classifier. The results of this study thus facilitate fast generation of accurate landslide inventory maps, which will eventually extend our understanding of the evolution of landscapes shaped by landslide processes.
Full Text Available Purpose: This paper presents the research on the development of the Aluminum Thermal Analysis Technology Platform (AlTAP utilizing a Case Based Reasoning (CBR Caspian shell for interpretation of industrial cooling curves and predicting alloy and cast component characteristics.Design/methodology/approach: CBR being a branch of Artificial Intelligence (AI that solves problems based on understanding and adaptation of previous experiences is suitable for interpretation of the AlTAP results since this is a knowledge intensive activity which requires a fair amount of experience.Findings: The integrated AlTAP and CBR system was found to be useful for the prediction of melt thermal characteristics, cast component mechanical and structural properties.Practical implications: Industrial trials confirmed the technical capabilities of the AlTAP/CBR Platform for the on-line quality control and prediction of 319 melt characteristics and the aluminum engine block’s (Cosworth casting process engineering specifications.Originality/value: An automated AlTAP Platform integrated with a CBR system is a new Quality Control concept in the area of the aluminum automotive casting.
Nowadays the research and exploitation of the case-based system are getting more and more attention.Case-Based Reasoning (CBR) is a strategy for solving the object cases based on the source cases that are prompted bythe object ones. CBR is not only a psychological theory for human knowledge, but will be a new cornerstone of theintelligent computer system technology. The case-based system is adopted in more and more application fields in orderto obtain better results, especially in the fields with ill-defined and no expert knowledge. But there is a lot of knowl-edge required in CBR, and we are also faced with the same knowledge acquisition bottleneck as in the expert systems.Data Mining (DM) and Knowledge Discovery in Database (KDD) are just the most useful means to solve this kind ofproblem in order to make the knowledge acquisition more automated . In this paper, we discuss the data mining tech-nology in CBR, especially we raise knowledge discovery in case base (KDC) and discuss this concept in detail. Final-ly, the structure of CBR based on DM is put forward.
Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie
Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the
Currently, a work breakdown structure (WBS) approach is used as the most common cost estimation approach for online course production projects. To improve the practice of cost estimation, this paper proposes a novel framework to estimate the cost for online course production projects using a case-based reasoning (CBR) technique and a WBS. A…
O'Flaherty, Joanne; McGarr, Oliver
The important role of the teacher in developing morally sensitive individuals is widely acknowledged. This paper examines the integration of context-specific moral development interventions within a four-year undergraduate teacher education programme in Ireland. The intervention strategy employed a case-based pedagogical approach where…
Radomski, Natalie; Russell, John
Learning how to "think like doctors" can be difficult for undergraduate medical students in their early clinical years. Our model of collaborative Integrated Case Learning (ICL) and simulated clinical reasoning aims to address these issues. Taking a socio-cultural perspective, this study investigates the reflective learning interactions and…
Burd, W. [Sandia National Labs., Albuquerque, NM (United States); Culler, D.; Eskridge, T.; Cox, L.; Slater, T. [New Mexico State Univ., Las Cruces, NM (United States)
The Milling Assistant (MA) programming system demonstrates the automated development of tool paths for Numerical Control (NC) machine tools. By integrating a Case-Based Reasoning decision processor with a commercial CAD/CAM software, intelligent tool path files for milled and point-to-point features can be created. The operational system is capable of reducing the time required to program a variety of parts and improving product quality by collecting and utilizing ``best of practice`` machining strategies.
Visser, W.M.; Hindriks, K.V.; Jonker, C.M.
In the context of practical reasoning, such as decision making and negotiation, it is necessary to model preferences over possible outcomes. Such preferences usually depend on multiple criteria. We argue that the criteria by which outcomes are evaluated should be the satisfaction of a person’s under
Nowadays, people can easily use a smartphone to get wanted information and requested services. Hence, this study designs and proposes a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oritened clustering case-based reasoning mechanism, which is called GoSIDE, based on Arduino and Open Service Gateway initative (OSGi). GoSIDE is a three-tier architecture, which is composed of Mobile Users, Application Servers and a Cloud-based Digital Convergence Server. A mobile user is with a smartphone and Kinect sensors to detect the user's Golf swing actions and to interact with iDTV. An application server is with Intelligent Golf Swing Posture Analysis Model (iGoSPAM) to check a user's Golf swing actions and to alter this user when he is with error actions. Cloud-based Digital Convergence Server is with Ontology-oriented Clustering Case-based Reasoning (CBR) for Quality of Experiences (OCC4QoE), which is designed to provide QoE services by QoE-based Ontology strategies, rules and events for this user. Furthermore, GoSIDE will automatically trigger OCC4QoE and deliver popular rules for a new user. Experiment results illustrate that GoSIDE can provide appropriate detections for Golfers. Finally, GoSIDE can be a reference model for researchers and engineers. PMID:26444809
Rex project involves: A method for analyzing needs and identifying sources of experience; Procedures for constructing elementary pieces of experience from documents, data bases, or interviews; Procedures for building up a computer representation of the knowledge domain at stake; A software package which includes a multimedia interface, and a retrieval engine that produces information files on the basis of questions in natural language. An extension to a Case Based Reasoning system oriented toward operation diagnostic is presented. Rex is an experience management method that was initiated and developed by the CEA in order to preserve and make use of the experience gathered during nuclear reactors design and start-up phases. The objective of the initial application was to preserve the knowledge feedback on the start-up of the European fast reactor Super-Phenix. Recent studies point out that an increasing number of companies consider the management of their experience as a strategic concern. Capitalizing experience concerning NPP's operation becomes a key-factor in companies' competitiveness and in NPP's safety. After raising the problem of experience management, we describe the principle of an Experience Feed-back Cycle. Then the Rex approach is introduced as an organic answer to the functional requirements of the cycle. Finally, an extension to a Case Based Reasoning system oriented toward operation diagnostic is presented. 6 refs, 9 figs
Highlights: • This study estimates the dynamic operational rating of a new residential building. • The advanced case-based reasoning (A-CBR) and stochastic approaches were used. • The prediction accuracy of the A-CBR model was determined at 96.8% for electricity. • The prediction accuracy of the A-CBR model was determined at 86.6% for gas energy. • The letter rating of cluster No.6 was estimated to be “B” with 83.46% probability. - Abstract: To ensure the high energy performance of a new building, its operational rating should be accurately estimated in the early design phase. Toward this end, this study developed an estimation methodology for the dynamic operational rating (DOR) of a new residential building using the advanced case-based reasoning (A-CBR) and stochastic approaches. This study was conducted in three steps: (i) establishment of a case database; (ii) retrieval of similar cases using the A-CBR approach; and (iii) estimation of the dynamic operational rating using the stochastic approach. The residential buildings located in Pusan, South Korea, were selected to validate the applicability of the developed methodology. Also, this study used the mean absolute percentage error (MAPE) to evaluate the prediction accuracy of the developed methodology (which means the difference between the predicted and measured energy performance). As a result, it was determined that the MAPE of the A-CBR model (i.e., 96.8% for electricity and 86.6% for gas energy) is superior to those of the other models (i.e., the basic CBR, multiple regression analysis, and artificial neural network models). In addition, based on the stochastic approach, it was estimated that cluster No.6, as a case study, would have the letter rating of ‘B’ grade (i.e., 25 < DOR ⩽ 50) with 83.46% of probability; and the letter rating of ‘C’ grade (i.e., 50 < DOR ⩽ 75) with 16.54%. The developed methodology can be used to easily and accurately estimate the dynamic operational
Lee, Minhyun; Koo, Choongwan; Hong, Taehoon; Park, Hyo Seon
For the effective photovoltaic (PV) system, it is necessary to accurately determine the monthly average daily solar radiation (MADSR) and to develop an accurate MADSR map, which can simplify the decision-making process for selecting the suitable location of the PV system installation. Therefore, this study aimed to develop a framework for the mapping of the MADSR using an advanced case-based reasoning (CBR) and a geostatistical technique. The proposed framework consists of the following procedures: (i) the geographic scope for the mapping of the MADSR is set, and the measured MADSR and meteorological data in the geographic scope are collected; (ii) using the collected data, the advanced CBR model is developed; (iii) using the advanced CBR model, the MADSR at unmeasured locations is estimated; and (iv) by applying the measured and estimated MADSR data to the geographic information system, the MADSR map is developed. A practical validation was conducted by applying the proposed framework to South Korea. It was determined that the MADSR map developed through the proposed framework has been improved in terms of accuracy. The developed MADSR map can be used for estimating the MADSR at unmeasured locations and for determining the optimal location for the PV system installation. PMID:24635702
Haouchine, Mohamed-Karim; Chebel-Morello, Brigitte; Zerhouni, Noureddine
Case base Maintenance is an active Case Based Reasoning research area. The main stream focuses on the method for reducing the size of the case-base while maintaining case-base competence. This paper gives an overview of these works, and proposes a case deletion strategy based on competence criteria using a novel approach. The proposed method, even if inspired from existing literature, combines an algorithm with a Competence Metric (CM). A series of tests are conducted using two standards data...
Based on the Internet technology and artificial int el ligence (AI) technology, this paper presents a dispersed press process knowledge bases based multi-reasoning press process decision system (DKB-MRPPD). The di spersed press process knowledge bases have been organized into case bases and ru le bases, which may be located at different enterprises, and employed to plan pr ess process by a multi-reasoning engine made up of the ART1, case reasoning and rule-based reasoning net. The architecture model of DK...
Based on an analysis of the connotation of knowledge system and knowledge management,this paper clarifies that historical experience is an important content of the study of the organization.It also describes the concept and characteristics of Case-Based Reasoning Technology,and the process framework of empirical knowledge management of an enterprise.
El Mokhtar En-Naimi
Full Text Available The major problem of e-learning is often stopped during training. Due to the fact that it is necessary to ensure an individualized and continuous learners follow-up during the learning process. Our work in this field develops the design and implementation of a Multi-Agents System Based on Dynamic Case Based Reasoning which can initiate learning and provide an individualized follow-up of a learner. When interacting with the platform, every learner leaves his/her traces in the machine. These traces are stored in the memory bank, this operation enriches collective past experiences. Via monitoring, comparing and analyzing these traces, the system keeps a constant intelligent watch on the platform, and therefore it detects the difficulties hindering progress, and/or it avoids possible dropping out. The system can support any learning subject. The success of a case-based reasoning system depends critically on the performance of the retrieval step used and, more particularly, on similarity measure used to retrieve source cases that are similar to the learners' traces (traces in progress. We propose a dynamic retrieving method based on a complementary similarity measure, named Inverse Longest Common Sub-Sequence (ILCSS. To guide and help the learner, the system is equipped with combination of human and virtual tutors.
Full Text Available Context-aware computing is an emerging computing paradigm that provides intelligent context-aware application. Context reasoning is an important aspect in context awareness, by which high level context can be derived from low-level context data. In this paper, we focus on the situation in mobile workspace, where a worker performs a set of activities to archive defined goals. The main part of being aware is to be able to answer the question of “what is going on”. Therefore high level context we need to derive is current activity and its state. The approach we propose is knowledge-driven technique. Temporal relations as well as semantic relations are integrated into the context model of activity, and the recognition is performed based on the model. We first define the context model of activity, and then we analyze the characteristics of context change and propose a method of context reasoning.
Full Text Available Urban fringe is the transition zone fine grained with urban and non-urban land cover types. The complex landscape mosaic in this area challenges the land cover classification based on the remote-sensing data. Spectral signatures are not efficient to discriminate all pixels into classes. To improve the recognition and handle the uncertainty, this paper provides a novel integrated approach, based on a fuzzy rough set and evidential reasoning (FRSER, for land cover classification in an urban fringe area. The approach is implemented on Landsat Operation Land Imager data covering the urban fringe area of Wuhan city, China. A fuzzy rough set is first used to define a decision table from multispectral imagery and ground reference data. Then the fuzzy rough information system is interpreted using the Dempster–Shafer theory, based on an evidential reasoning system. A final land cover classification with uncertainty is achieved by evidential reasoning. The results are compared with the traditional maximum likelihood classifier (MLC and some rough set-based classifiers including classical rough set classifier (RS, fuzzy rough set classifier (FRS, and variable precision fuzzy rough set classifier (VPFRS. The better overall accuracy, user’s and producer’s accuracies, and the kappa coefficient, in comparison with the other classifiers, suggest that the proposed approach can effectively discriminate land cover types in urban fringe areas with high inter-class similarities and intra-class heterogeneity. It is also capable of handling the uncertainty in data processing, and the final land cover map comes with a degree of uncertainty. The proposed approach that can efficiently integrate the merits of both the fuzzy rough set and DS theory provides an efficient method for urban fringe land cover classification.
蔡良才; 董豪昊; 王海服; 刘洲; 邵斌; 戴圣睿
A support vector machine prediction method based on the surveillance of case-based reasoning was presented,aiming at solving the problems of small sample,small range and data distortion during the military aircraft noise-power-distance (NPD)data integration.In the method,support vector machine was adopted as a regression and prediction model,and similar case was searched via case-based reasoning to supervise the process of regression and prediction.In the process,a method of comparability searching,checkout and revising based on gradient was put forward successfully to combine the case-based reasoning and prediction model,which reduces the sensitivity and dependence of the model on the data sample.An example indicates that the mothed is economical and effective,and will greatly improve the precision of regression and prediction.%针对当前军用飞机 NPD（Noise-Power-Distance）数据集成过程中面临小样本、小范围及数据失真问题，给出基于范例推理监督的支持向量机预测方法。用支持向量机作为数据回归与预测模型，通过范例推理检索出与目标范例相似的 NPD 数据，用相似范例来指导 NPD 数据的回归与预测。提出基于坡度的相似性检索、检验及修正方法，成功将范例推理的监督作用与预测模型有机结合，降低预测模型对数据样本的敏感性及依赖性。实例表明，该方法经济可行，能提高回归及预测精度。
Chen, Deyun; Pei, Shujun; Quan, Zhiying
Knowledge base system is one of the most future branches for artificial intelligence facing with practical application. But the reasoning process of system is invisible, not visual and users cannot intervene the reasoning process, therefore for users the system is only a black box. This condition causes many users to take a suspicious attitude to the conclusions analyzing and drawing from the system, that means even though the system has the explanation function, but it is still not far enough. If we adopt graph or image technique to display this reasoning procedure interactively and dynamically which can make this procedure be visual, users can intervene the reasoning procedure which can greatly reduce users" gain giving, and at the same time it can provide a given method for integrity check to knowledge of the knowledge base. Therefore, we can say that reasoning visualization of knowledge base system has a further meaning than general visualization. In this paper the visual problem of reasoning process for knowledge base system on the basis of the formalized analysis for ICON system, Icon operation, syntax and semanteme of the statement is presented, a reasoning model of knowledge base system that has a visual characteristics is established, the model is used to do an integrity check in practical expert system and knowledge base, better effect is got.
This paper offers an approach to extensible knowledge representation and reasoning for a family of formalisms known as Description Logics. The approach is based on the notion of adding new concept constructors, and includes a heuristic methodology for specifying the desired extensions, as well as a modularized software architecture that supports implementing extensions. The architecture detailed here falls in the normalize-compared paradigm, and supports both intentional reasoning (subsumption) involving concepts, and extensional reasoning involving individuals after incremental updates to the knowledge base. The resulting approach can be used to extend the reasoner with specialized notions that are motivated by specific problems or application areas, such as reasoning about dates, plans, etc. In addition, it provides an opportunity to implement constructors that are not currently yet sufficiently well understood theoretically, but are needed in practice. Also, for constructors that are provably hard to reaso...
Kononowicz, Andrzej A; Zary, Nabil; Davies, David; Heid, Jörn; Woodham, Luke; Hege, Inga
Patient consents for distribution of multimedia constitute a significant element of medical case-based repositories in medicine. A technical challenge is posed by the right of patients to withdraw permission to disseminate their images or videos. A technical mechanism for spreading information about changes in multimedia usage licenses is sought. The authors gained their experience by developing and managing a large (>340 cases) repository of virtual patients within the European project eViP. The solution for dissemination of license status should reuse and extend existing metadata standards in medical education. Two methods: PUSH and PULL are described differing in the moment of update and the division of responsibilities between parties in the learning object exchange process. The authors recommend usage of the PUSH scenario because it is better adapted to legal requirements in many countries. It needs to be stressed that the solution is based on mutual trust of the exchange partners and therefore is most appropriate for use in educational alliances and consortia. It is hoped that the proposed models for exchanging consents and licensing information will become a crucial part of the technical frameworks for building case-based repositories. PMID:21893742
徐丽华; 谢德体; 魏朝富; 李兵
The 111 soil samples were collected in Wangjiagou watershed of Three Gorges Reservoir Area with complex geographical environment.Total nitrogen content in the soil was measured,and the land use data and elevation,slope,plan curvature,profile curvature,topographic position index and topographic wetness index were collected.The soil total nitrogen was mapped by using the soil land inference model (SoLIM) that is based on case reasoning.The results showed that,land use type data can be used to improve the accuracy of prediction.The spatial distribution of soil nutrients produced by the SoLIM contained more information,and presented more details of spatial variability of soil nutrients.Therefore,the SoLIM based on case reasoning was validated a good method for soil nutrient mapping in the small study area with complex geographical environment.
Hackling, Mark; Sherriff, Barbara
Language is critical in the mediation of scientific reasoning, higher-order thinking and the development of scientific literacy. This study investigated how an exemplary primary science teacher scaffolds and supports students' reasoning during a Year 4 materials unit. Lessons captured on video, teacher and student interviews and micro-ethnographic…
在基于模型重用的敏捷虚拟企业(Agile Virtual Enterprise,AVE)建模过程研究中,提出基于模型重用的AVE建模过程框架,并在该框架下对两个特殊的AVE建模过程实例即G-EM和V-EM进行研究.同时,为了支持AVE建模过程中的模型重用,提出面向AVE建模的基于实例推理(Case Based Reasoning,CBR)的模型重用方法,使AVE建模过程的效率更高,AVE模型的语义一致性更强.
This book consists of various contributions in conjunction with the keywords "reasoning" and "intelligent systems", which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally.
Wessels, B; Seger, W
The process of "clinical reasoning" is exemplified as supportive to the complaint management of the Statutory Medical Health Advisory Board in Lower Saxony, Germany, within the operational division for long-term care insurance. A model case from real life illustrates in detail the hypothetical-deductive approach by Beusheusen and Klemme/Siegmann. Because of the potential area of conflicts between human concern in the case of a long-term care burden and legal requirements, the process was analysed in terms of a pragmatic reasoning. Human resources of the claimant and persons in charge at customer's service were demonstrated as well as political, statutory and institutional determining factors. Concluding self-perception validates the process in the context of evidence-based practice. PMID:25397910
罗晨; 王欣; 苏春; 吴泽
夹具具有夹持工件并精确定位的重要作用。由于夹具设计关联因素诸多，过程复杂，设计方案很大程度依赖于设计者经验，最近发展的基于案例推理的夹具设计方法可一定程度上缓解对个人经验的依赖性，但此类设计方法大多仅以工件的几何形状为案例表示和检索依据，影响推理系统的检索效率及准确度，其有效性和实用性也因此减弱。鉴于此，建立了一种夹具设计案例特征表示的新型检索机制，该模型不仅包含工件几何形状，还包含工件材料、加工工艺和其他功能要求等因素，采用统一建模语言(Unified modeling language, UML)面向对象的表示方式实现特征信息存储的结构化和模块化，采用几何形状和位置拓扑关系并行检索的算法，该算法主要通过搜索节点对应约束的最大相似连通子图以确定零件的几何特征相似度，并给出其他影响因素相关的相似度公式。具体实例说明该新型检索模型的有效性和实用性。%Fixtures play a key role in accurately locating and clamping workpiece. Fixture design is a complex process involving many factors and traditionally the designer’s experience plays a big role. Recently case-based reasoning(CBR) based fixture design method becomes popular and it can ease personal experience dependence. However existing methods mainly use simple manufacturing parts’ geometric feature in case representation and retrieval and this leads to inaccuracy and inefficiency in their real application. In view of that, a new comprehensive retrieval model for fixture design case representation is proposed and it incorporates geometry, material, processing and functional features. The new model uses object-oriented unified modeling language(UML) case representation to enable information to be processed in a structural and modular way. A parallel retrieval algorithm, combining geometrical shape and its
Tao Lu; Xiaoling Liu; Xiaogang Liu; Shaokun Zhang
Context-aware computing is an emerging computing paradigm that provides intelligent context-aware application. Context reasoning is an important aspect in context awareness, by which high level context can be derived from low-level context data. In this paper, we focus on the situation in mobile workspace, where a worker performs a set of activities to archive defined goals. The main part of being aware is to be able to answer the question of “what is going on”. Therefore high level context w...
Li, Jianwen; Zhu, Shufang; Pu, Geguang; Vardi, Moshe
We present here a new explicit reasoning framework for linear temporal logic (LTL), which is built on top of propositional satisfiability (SAT) solving. As a proof-of-concept of this framework, we describe a new LTL satisfiability tool, Aalta\\_v2.0, which is built on top of the MiniSAT SAT solver. We test the effectiveness of this approach by demonnstrating that Aalta\\_v2.0 significantly outperforms all existing LTL satisfiability solvers. Furthermore, we show that the framework can be extend...
Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.
The purpose of this thesis is to analyze why IKEA, biggest Swedish furniture brand, should enter to Vietnam. Based on research and interviews, the study provides an overview of Vietnamese economy, reasons for the company to open its first branch in Vietnam and suggest how IKEA adapt their strategies to expand and become profitable in Vietnam. The idea of this literature started after the author's first visited IKEA store in Finland, in 2013. By realized the promising development of IKEA i...
金保华; 林青; 付中举; 李红婵
The quantities of emergency information make it hard to provide quick support for decision-making system. Nowadays it has become a heat issue in public security field. The knowledge representation and reasoning of emergency cases repository based on SWRL is lucubrated. Firstly, the concepts in emergency cases repository were defined and the 0WL( Web Ontology Language) was used as the basis of establishment of emergency cases repository in semantically representation. And then, SWRL (Semantic WebRule Language) was introduced to further established rules mechanics. At the same time, the disadvantage of reasoning capacity of OWL was greatly improved. Finally, further integration and reasoning are realized by SWRL reasoning rules and Jena inference engine. The validity of SWRL reasoning rules is verified in the experiment results.%针对当下在公共社会领域中突发应急事件的信息量庞大,难以为应急决策系统提供快速支持的热点问题,深入研究了基于SWRL的应急案例库的知识表示以及推理方法.首先定义了应急案例库中的相关概念,并采用语义上具有较强能力的OWL( Web Ontology Language)作为应急案例库Ontology构建的基础.然后引入SWRL( Semantic WebRule Language)来进一步构建应急案例库的规则机制并改善OWL在推理能力方面的不足.最后运用SWRL推理规则与Jena推理机对应急案例库中的规则进行了进一步的整合与推理现实.仿真结果验证了SWRL推理规则的有效性与正确性.
This paper gives a semantic fuzzy retrieval method of multimedia object,discusses the principle of fuzzy semantic retrieval technique,presents a fuzzy reasoning mechanism based on the knowledge base,and designs the relevant reasoning algorithms.Researchful results have innovative significance.
Tatsuzawa, Yasutaka; Yoshino, Aihide; Nomura, Soichiro
We describe a case of reflex seizures induced by abstract reasoning but not other cognitive processes. The patient, a 46-year-old man, experienced myoclonic seizures whenever he played shogi (Japanese chess). To identify the critical thought processes responsible for inducing his seizures, we monitored his clinical seizures and epileptiform discharges while he performed comprehensive neuropsychological tests, including the Wechsler Adult Intelligence Scale-Revised (WAIS-R), spatial working memory, mental rotation, and Wisconsin Card Sorting Test (WCST) tasks. A myoclonic seizure occurred only during the WCST. Generalized 3- to 5-Hz spike-and-slow-wave bursts occurred repeatedly during the Block Design subtest of the WAIS-R and the WCST, whereas no discharges occurred during other subtests of the WAIS-R including the calculation, spatial working memory, and mental rotation tasks. These results indicate that abstract reasoning, independent of other cognitive processes, could induce the patient's epileptiform discharges, suggesting that his reflex seizures might be a distinct subtype of nonverbal thinking-induced seizures. PMID:20171146
Chávez Valiente Indira
Full Text Available En este trabajo se presenta una propuesta de estructura de almacenamiento y los mecanismos de recuperación utilizados para aplicar el razonamiento basado en casos (RBC en la generación de procedimientos de prueba funcionales en proyectos de software. Esta propuesta parte de los requisitos funcionales del proyecto de software y en ella se enuncian los algoritmos propuestos para considerar la semejanza entre cada par de proyectos, así como los que permiten adaptar la solución encontrada en la base de casos a las características de los nuevos proyectos.This paper presents a proposal for storage structure and retrieval mechanisms used for implementing case-based reasoning (CBR in generating functional test procedures in software projects. This proposal was based on software project t functional requirements and sets out the proposed algorithms for considering the similarity between each pair of projects as well as those leading to adapting the solution found in the case base.
In such engineering fields as nuclear power plant engineering, technical information expressed in the form of schematics is frequently used. A new paradigm for model-based reasoning (MBR) and an AI tool called PLEXSYS (plant expert system) using this paradigm has been developed. PLEXSYS and the underlying paradigm are specifically designed to handle schematic drawings, by expressing drawings as models and supporting various sophisticated searches on these models. Two application systems have been constructed with PLEXSYS: one generates PLEXSYS models from existing CAD data files, and the other provides functions for nuclear power plant design support. Since the models can be generated from existing data resources, the design support system automatically has full access to a large-scale model or knowledge base representing actual nuclear power plants. (author)
A new type of intelligent CAI system for chemistry is developed in this paper based on automated reasoning with chemistry knowledge.The system has shown its ability to solve chemistry problems,to assist students and teachers in studies and instruction with the automated reasoning functions.Its open mode of the knowledge base and its unique style of the interface between the system and human provide more opportunities for the users to acquire living knowledge through active participation.The automated reasoning based on basic chemistry knowledge also opened a new approach to the information storage and management of the ICAI system for sciences.
National Aeronautics and Space Administration — The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and...
Hansen, Claus Thorp; Zavbi, R.
In this paper we propose a model of how to carry out functional reasoning. The model is based on the domain theory, and it links the stepwise determination of the artefact´s characteristics during the design process to different ways of carrying out functional reasoning found in the literature. The...... model proposes of a set of the mental objects and a number of ways to carry out functional reasoning available to the engineering designer. The result of the research presented in this paper is the building of a hypothesis "in the form of a model" with explanatory power....
张茉莉; 袁鹏; 宋永会; 张慧良; 姜诗慧
In recent years, abrupt environmental pollution accidents occurred frequently in China, having resulted in huge hazards on socio-economic development.Through structured hierarchical storage and searching technology based on case reasoning, the emergency management application case library can be established, with which historical matching cases can be found by quick search, and then relatively optimal solution tools can be provided for the policy makers. The realization approaches of information database based on case-reasoning retrieval technology were explored.The contents of the case library were researched, the structure was designed and the system developed.Finally the case retrieval system of abrupt environmental pollution accidents based on Web technology was established, which included more than 500 cases.The system takes the nearest neighbor decoding to search similar fitting cases, possessing retrieving, correcting, studying and statistical analysis functions and so on.It can provide references for the emergency response to the newly happened abrupt environmental accidents.%近年来，我国突发环境污染事件事故频发，给经济社会发展造成巨大危害。通过基于案例推理的结构化层次存储和搜索技术，构建应用管理案例库，通过快速搜索查找匹配历史案例，可为决策者提供相对优化的解决方案工具。探讨了基于案例推理检索技术的信息数据库的实现途径，研究了案例库内容，进行了结构设计和系统开发，建立了基于Web技术的环境污染事故案例检索查询系统，收集整理500余件事故案例系统采用最近相邻法在案例库中检索相似案例，具有检索、修正和学习，以及统计分析等功能，可为新的突发事件应急响应提供参考。
Moldability evaluation for molded parts, which is the basis of concurrent design, is a key design stage in injection molding design. By moldability evaluation the design problems can be found timely and an optimum plastic part design achieved. In this paper, a systematic methodology for moldability evaluation based on fuzzy logic is proposed. Firstly, fuzzy set modeling for six key design attributes of molded parts is carried out respectively. Secondly, on the basis of this, the relationship between fuzzy sets for design attributes and fuzzy sets for moldability is established by fuzzy rules that are based on domain experts' experience and knowledge. At last the integral moldability for molded parts is obtained through fuzzy reasoning. The neural network based fuzzy reasoning approach presented in this paper can improve fuzzy reasoning efficiency greatly, especially for system having a large number of rules and complicated membership functions. An example for moldability evaluation is given to show the feasibility of this proposed methodology.
In this thesis two models of syllogistic reasoning for dealing with arguments that involve fuzzy quantified statements and approximate chaining are proposed. The modeling of quantified statements is based on the Theory of Generalized Quantifiers, which allows us to manage different kind of quantifiers simultaneously, and the inference process is interpreted in terms of a mathematical optimization problem, which allows us to deal with more arguments that standard deductive ones. For the case o...
Jiang Ruisong; Zhang Dinghua; Wang Wenhu; Bu Kun
A hybrid reasoning model was proposed in which CBR (case-based reasoning) was applied to the conceptual design and RBR (rule-based reasoning) was applied to the detailed design after research of the design process and domain knowledge of the acre-engine turbine blade investment casting mold design field. In the conceptual design stage, the representation and retrieval technologies were researched which improve the retrieval efficiency. Meanwhile, RBR was used to modify the retrieval result. The experimentation shows that the approach in this study can be used to obtain a more satisfactory design result.
Hoelldobler, Steffen; Stoerr, Hans-Peter
The paper reports on first preliminary results and insights gained in a project aiming at implementing the fluent calculus using methods and techniques based on binary decision diagrams. After reporting on an initial experiment showing promising results we discuss our findings concerning various techniques and heuristics used to speed up the reasoning process.
In addition to feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control like for example automatic control sequences, interlocks, etc. A lot of complex routine reasoning is involved in the design and verification and validation (VandV) of such automatics. Similar reasoning tasks are encountered during plant operation in action planning and fault diagnosis. The low-level part of the required problem solving is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised reasoning. Such plant models and corresponding inference algorithms are the main subject of this report. Deep knowledge and qualitative modelling play an essential role in this work. Deep knowledge refers to mechanised reasoning based on the first principles of the phenomena in the problem domain. Qualitative modelling refers to knowledge representation formalism and related reasoning methods which allow solving problems on an abstraction level higher than for example traditional simulation and optimisation. Prolog is a commonly used platform for artificial intelligence (Al) applications. Constraint logic languages like CLP(R) and Prolog-III extend the scope of logic programming to numeric problem solving. In addition they allow a programming style which often reduces the computational complexity significantly. An approach to model-based reasoning implemented in constraint logic programming language CLP(R) is presented. The approach is based on some of the principles of QSIM, an algorithm for qualitative simulation. It is discussed how model-based reasoning can be applied in the design and VandV of plant automatics and in action planning during plant operation. A prototype tool called ISIR is discussed and some initial results obtained during the development of the tool are presented. The results presented originate from preliminary test results of the prototype obtained
Full Text Available An automatic multilevel image segmentation method based on sup-star fuzzy reasoning (SSFR is presented. Using the well-known sup-star fuzzy reasoning technique, the proposed algorithm combines the global statistical information implied in the histogram with the local information represented by the fuzzy sets of gray-levels, and aggregates all the gray-levels into several classes characterized by the local maximum values of the histogram. The presented method has the merits of determining the number of the segmentation classes automatically, and avoiding to calculating thresholds of segmentation. Emulating and real image segmentation experiments demonstrate that the SSFR is effective.
Shellenbarger, Teresa; Robb, Meigan
Faculty face the demand of preparing nursing students for the constantly changing health care environment. Effective use of online, classroom, and clinical conferencing opportunities helps to enhance nursing students' clinical reasoning capabilities needed for practice. The growth of technology creates an avenue for faculty to develop engaging learning opportunities. This article presents technology-based strategies such as electronic concept mapping, electronic case histories, and digital storytelling that can be used to facilitate clinical reasoning skills. PMID:25402714
Babai, Reuven; Levit-Dori, Tamar
This study addressed one aspect of scientific reasoning, the control of variables reasoning scheme. We explored whether a short intervention aimed at accelerating this reasoning scheme by CASE lessons would improve students' ability to apply this scheme in problems related to the biology curriculum. About 120 students from grade nine were assessed…
Dinesh, KP; Radhakrishna, C; Reddy, Manjunatha AH; Gururaja, KV
A recent issue of Current Science carried a correspondence entitled ‘Taxonomic vandalism: The case of the giant wrinkled frog’ by Ranjit Daniels1. The author is critical of a communication authored by us.
Point pattern matching (PPM) is an important topic in computer vision and pattern recognition. It can be widely used in many areas such as image registration, object recognition, motion detection, target tracking, autonomous navigation, and pose estimation. This paper discusses the incomplete matching problem of two point sets under Euclidean transformation. According to geometric reasoning, some definitions for matching clique, support point pair, support index set, and support index matrix, etc. are given. Based on the properties and theorems of them, a novel reasoning algorithm is presented, which searches for the optimal sOlLtion from top to bottom and could find out as many consistent corresponding point pairs as possible. Theoretical analysis and experimental results show that the new algorithm is very effective, and could be, under some conditions, applied to the PPM problem under other kind of transformations.
Christiansen, Henning; Have, Christian Theil; Tveitane, Knut
We consider automated transition from Use Cases in a restricted natural language syntax into UML models, by trying to capture the semantics of the natural language and map it into building blocks of the object oriented programming paradigm. Syntax and semantic analysis is done in a framework of...... Definite Clause Grammars extended with Constraint Handling Rules, which generalizes previous approaches with a direct way to express domain knowledge utilized in the interpretation process as well as stating explicit rules for pronoun resolution....
The purpose of this extensive thesis was to study the essence of communication in companies and gain a better understanding of how a company’s strategy is applied into the communication culture. Furthermore, due to the rapid growth of popularity of social media utilization amongst people and companies, this thesis discusses social media in general, from the perspective of B2B oriented companies, its usage and opportunities. The case company for this thesis was a Finnish B2B oriented compa...
Tutac, Adina E.; Racoceanu, Daniel; Leow, Wee-Keng; Müller, Henning; Putti, Thomas; Cretu, Vladimir
One of the fundamental issues in bridging the gap between the proliferation of Content-Based Image Retrieval (CBIR) systems in the scientific literature and the deficiency of their usage in medical community is based on the characteristic of CBIR to access information by images or/and text only. Yet, the way physicians are reasoning about patients leads intuitively to a case representation. Hence, a proper solution to overcome this gap is to consider a CBIR approach inspired by Case-Based Reasoning (CBR), which naturally introduces medical knowledge structured by cases. Moreover, in a CBR system, the knowledge is incrementally added and learned. The purpose of this study is to initiate a translational solution from CBIR algorithms to clinical practice, using a CBIR/CBR hybrid approach. Therefore, we advance the idea of a translational incremental similarity-based reasoning (TISBR), using combined CBIR and CBR characteristics: incremental learning of medical knowledge, medical case-based structure of the knowledge (CBR), image usage to retrieve similar cases (CBIR), similarity concept (central for both paradigms). For this purpose, three major axes are explored: the indexing, the cases retrieval and the search refinement, applied to Breast Cancer Grading (BCG), a powerful breast cancer prognosis exam. The effectiveness of this strategy is currently evaluated over cases provided by the Pathology Department of Singapore National University Hospital, for the indexing. With its current accuracy, TISBR launches interesting perspectives for complex reasoning in future medical research, opening the way to a better knowledge traceability and a better acceptance rate of computer-aided diagnosis assistance among practitioners.
Assembly-based modeling is a promising approach to broadening the accessibility of 3D modeling. In assembly-based modeling, new models are assembled from shape components extracted from a database. A key challenge in assembly-based modeling is the identification of relevant components to be presented to the user. In this paper, we introduce a probabilistic reasoning approach to this problem. Given a repository of shapes, our approach learns a probabilistic graphical model that encodes semantic and geometric relationships among shape components. The probabilistic model is used to present components that are semantically and stylistically compatible with the 3D model that is being assembled. Our experiments indicate that the probabilistic model increases the relevance of presented components. © 2011 ACM.
To use reasoning knowledge accurately and efficiently,many reasoning methods have been proposed.However,the differences in form among the methods may obstruct the systematical analysis and harmonious integration of them.In this paper,a common reasoning model JUM(Judgement Model)is introduced.According to JUM,a common knowledge representation form is abstracted from different reasoning methods and its limitation is reduced.We also propose an algorithm for transforming one type of JUMs into another.In some cases,the algorithm can be used to resolve the key problem of integrating different types of JUM in one system.It is possible that a new architecture of knowledge-based system can be realized under JUM.
Arocha José F
Full Text Available Abstract Background The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. Discussion We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences
Golbreich, Christine; Dameron, Olivier; Bierlaire, Olivier; Gibaud, Bernard
This paper presents a medical case study, which requires reasoning with an OWL ontology extended by rules. The application aims at assisting the labeling of some brain cortex structures identified in MRI images. A simplified example is provided to illustrate the need for supplementing OWL with rules, for reasoning over such hybrid knowledge, and showing potential issues with doing that. Then, we describe some of the available techniques and implementations for reasoning over hybrid systems an...
Csapó, Beno; Molnár, Gyöngyvér; Nagy, József
This study explores the potential of using online tests for the assessment of school readiness and for monitoring early reasoning. Four tests of a face-to-face-administered school readiness test battery (speech sound discrimination, relational reasoning, counting and basic numeracy, and deductive reasoning) and a paper-and-pencil inductive…
Durham, Catherine O; Fowler, Terri; Kennedy, Sally
Accelerating the development of diagnostic reasoning skills for nurse practitioner students is high on the wish list of many faculty. The purpose of this article is to describe how the teaching strategy of problem-based learning (PBL) that drills the hypothetico-deductive or analytic reasoning process when combined with an assignment that fosters pattern recognition (a nonanalytic process) teaches and reinforces the dual process of diagnostic reasoning. In an online Doctor of Nursing Practice program, four PBL cases that start with the same symptom unfold over 2 weeks. These four cases follow different paths as they unfold leading to different diagnoses. Culminating each PBL case, a unique assignment called an illness script was developed to foster the development of pattern recognition. When combined with hypothetico-deductive reasoning drilled during the PBL case, students experience the dual process approach to diagnostic reasoning used by clinicians. PMID:25350904
A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.
Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás
Some modern Electronic Healthcare Record (EHR) architectures and standards are based on the dual model-based architecture, which defines two conceptual levels: reference model and archetype model. Such architectures represent EHR domain knowledge by means of archetypes, which are considered by many researchers to play a fundamental role for the achievement of semantic interoperability in healthcare. Consequently, formal methods for validating archetypes are necessary. In recent years, there has been an increasing interest in exploring how semantic web technologies in general, and ontologies in particular, can facilitate the representation and management of archetypes, including binding to terminologies, but no solution based on such technologies has been provided to date to validate archetypes. Our approach represents archetypes by means of OWL ontologies. This permits to combine the two levels of the dual model-based architecture in one modeling framework which can also integrate terminologies available in OWL format. The validation method consists of reasoning on those ontologies to find modeling errors in archetypes: incorrect restrictions over the reference model, non-conformant archetype specializations and inconsistent terminological bindings. The archetypes available in the repositories supported by the openEHR Foundation and the NHS Connecting for Health Program, which are the two largest publicly available ones, have been analyzed with our validation method. For such purpose, we have implemented a software tool called Archeck. Our results show that around 1/5 of archetype specializations contain modeling errors, the most common mistakes being related to coded terms and terminological bindings. The analysis of each repository reveals that different patterns of errors are found in both repositories. This result reinforces the need for making serious efforts in improving archetype design processes. PMID:23246613
D'Aquin, Mathieu; Badra, Fadi; Lafrogne, Sandrine; Lieber, Jean; Napoli, Amedeo; Szathmary, Laszlo
International audience In case-based reasoning, the adaptation of a source case in order to solve the target problem is at the same time crucial and difficult to implement. The reason for this difficulty is that, in general, adaptation strongly depends on domain-dependent knowledge. This fact motivates research on adaptation knowledge acquisition (AKA). This paper presents an approach to AKA based on the principles and techniques of knowledge discovery from databases and data-mining. It is...
... quantitative analysis of the probability of occurrence of each scenario and combination of events will be...-SAFETY AND ENVIRONMENTAL MANAGEMENT Accident and Fire Prevention Reasonable Worst Case Fire Scenario § 102-80.150 What is meant by “reasonable worst case fire scenario”? Reasonable worst case fire...
Meléndez i Frigola, Joaquim; Colomer Llinàs, Joan; Rosa, Josep Lluís de la
The paper focuses on taking advantage of large amounts of data that are systematically stored in plants (by means of SCADA systems), but not exploited enough in order to achieve supervisory goals (fault detection, diagnosis and reconfiguration). The methodology of case base reasoning (CBR) is proposed to perform supervisory tasks in industrial processes by re-using the stored data. The goal is to take advantage of experiences, registered in a suitable structure as cam, avoiding the tedious ta...
Arman Avadikyan; Patrick Llerena
Using a real option reasoning perspective we study the uncertainties and irreversibilities that impact the investment decisions of firms during the different phases of technological transitions. The analysis of transition dynamics via real options reasoning allows the provision of an alternative and more qualified explanation of investment decisions according to the sequentiality of pathways considered. In our framework, flexibility management through option investments concerns both the incu...
Atmani Baghdad; Benbelkacem Sofia; Benamina Mohamed
The treatment of complex systems often requires the manipulation of vague, imprecise and uncertain information. Indeed, the human being is c ompetent in handling of such systems in a natural way. Instead of thinking in mathematical te rms, humans describes the behavior of the system by language proposals. In order to represent this type of information, Zadeh proposed to model the mechanism of human thought by a...
Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standar
The textile process planning is a knowledge reuse process in nature, which depends on the expert's knowledge and experience. It seems to be very difficult to build up an integral mathematical model to optimize hundreds of the processing parameters. In fact, the existing process cases which were recorded to ensure the ability to trace production steps can also be used to optimize the process itself. This paper presents a novel knowledge-reuse based hybrid intelligent reasoning model (HIRM) for worsted process optimization. The model architecture and reasoning mechanism are respectively described. An applied case with HIRM is given to demonstrate that the best process decision can be made, and important processing parameters such as for raw material optimized.
Irish, Tobias E. L.
This multiple case study explores issues of equity in science education through an examination of how teachers' reasoning patterns compare with students' reasoning patterns during inquiry-based lessons. It also examines the ways in which teachers utilize students' cultural and linguistic resources, or funds of knowledge, during inquiry-based lessons and the ways in which students utilize their funds of knowledge, during inquiry-based lessons. Three middle school teachers and a total of 57 middle school students participated in this study. The data collection involved classroom observations and multiple interviews with each of the teachers individually and with small groups of students. The findings indicate that the students are capable of far more complex reasoning than what was elicited by the lessons observed or what was modeled and expected by the teachers, but that during the inquiry-based lessons they conformed to the more simplistic reasoning patterns they perceived as the expected norm of classroom dialogue. The findings also indicate that the students possess funds of knowledge that are relevant to science topics, but very seldom use these funds in the context of their inquiry-based lessons. In addition, the teachers in this study very seldom worked to elicit students' use of their funds in these contexts. The few attempts they did make involved the use of analogies, examples, or questions. The findings from this study have implications for both teachers and teacher educators in that they highlight similarities and differences in reasoning that can help teachers establish instructional congruence and facilitate more equitable science instruction. They also provide insight into how students' cultural and linguistic resources are utilized during inquiry-based science lessons.
D'Aquin, Mathieu; Badra, Fadi; Lafrogne, Sandrine; Lieber, Jean; Napoli, Amedeo; Szathmary, Laszlo
In case-based reasoning, the adaptation step depends in general on domain-dependent knowledge, which motivates studies on adaptation knowledge acquisition (AKA). CABAMAKA is an AKA system based on principles of knowledge discovery from databases. This system explores the variations within the case base to elicit adaptation knowledge. It has been successfully tested in an application of case-based decision support to breast cancer treatment.
Thoron, Andrew C.; Myers, Brian E.
The purpose of this study was to determine the effect of inquiry-based agriscience instruction on student scientific reasoning. Scientific reasoning is defined as the use of the scientific method, inductive, and deductive reasoning to develop and test hypothesis. Developing scientific reasoning skills can provide learners with a connection to the…
Maria J. Santofimia
Full Text Available Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.
Fixture is an important manufacturing activity. A fixture design system based on case-based reasoning (CBR) is proposed in this paper. A new method of case representation on the basis of fixture function is presented, where the case representation is constituted of workpiece knowledge, processing feature knowledge, and fixture feature knowledge. Running the prototype system shows that the knowledge representation method, using cases, is a better way to transform and explain the design knowledge.
Kim, Hyeonjin; Hannafin, Michael J.
Cases have been used in education through a variety of methods, such as case written analysis, case discussion, and case development. Recent case definitions and uses have extended their traditional uses. In case-based reasoning, cases are considered to represent knowledge, and the use of cases is integral to an individual's problem-solving…
This book is a sequel to the classic work, Fallacies Selected Papers 1972 - 1982 (1989), coauthored with Douglas Walton, and is a further major contribution to the Woods-Walton Approach to the logic of fallacious reasoning No one disputes the formitable accomplishments of modern mathematical logic; but equally no one seriously believes that classical logic is much good for the analysis of real-life argument and reasoning, or that it is the best place in which to transact the business of fallacy theory One of the principal innovations of the book is its adaptation of systems of logic to the particular requirements of fallacy theory The book develops logical analyses which take into account such features of real-life cognitive agency as resource- availability and computational complexity The book is also an invitation to interdisciplinary cooperation, linking the relevant branches of logic with computer science, cognitive psychology, neurobiology, forensic science, linguistics, (including conversational analysi...
D'Aquin, Mathieu; Lafrogne, Sandrine; Lieber, Jean; Napoli, Amedeo; Szathmary, Laszlo
In case-based reasoning, the adaptation of a source case in order to solve the target problem is at the same time crucial and difficult to implement. The reason for this difficulty is that, in general, adaptation strongly depends on domain-dependent knowledge. This fact motivates research on adaptation knowledge acquisition (AKA). This paper presents an approach to AKA based on the principles and techniques of knowledge discovery from databases and data-mining. It is implemented in CABAMAKA, a system that explores the variations within the case base to elicit adaptation knowledge. This system has been successfully tested in an application of case-based reasoning to decision support in the domain of breast cancer treatment.
王伟; 徐扬; 王学芳
This paper is focused on automated reasoning based on classical propositional logic and lattice-valued propositional logic LP(X). A new method of automated reasoning is given, and the soundness and completeness theorems of this method are proved.
Lim, Jeongyeon; Kim, Munjo; Lee, Bumshik; Kim, Munchurl; Lee, Heekyung; Lee, Han-Kyu
With the rapidly growing Internet, the Internet broadcasting and web casting service have been one of the well-known services. Specially, it is expected that the IPTV service will be one of the principal services in the broadband network . However, the current broadcasting environment is served for the general public and requires the passive attitude to consume the TV programs. For the advanced broadcasting environments, various research of the personalized broadcasting is needed. For example, the current unidirectional advertisement provides to the TV viewers the advertisement contents, depending on the popularity of TV programs, the viewing rates, the age groups of TV viewers, and the time bands of the TV programs being broadcast. It is not an efficient way to provide the useful information to the TV viewers from customization perspective. If a TV viewer does not need particular advertisement contents, then information may be wasteful to the TV viewer. Therefore, it is expected that the target advertisement service will be one of the important services in the personalized broadcasting environments. The current research in the area of the target advertisement classifies the TV viewers into clustered groups who have similar preference. The digital TV collaborative filtering estimates the user's favourite advertisement contents by using the usage history [1, 4, 5]. In these studies, the TV viewers are required to provide their profile information such as the gender, job, and ages to the service providers via a PC or Set-Top Box (STB) which is connected to digital TV. Based on explicit information, the advertisement contents are provided to the TV viewers in a customized way with tailored advertisement contents. However, the TV viewers may dislike exposing to the service providers their private information because of the misuse of it. In this case, it is difficult to provide appropriate target advertisement service.
Dealing with child sexual abuse cases, is an integral part of the social workers job. Due to the nature of the abuse and the provisions made by the Children’s Act, 38 of 2005, as amended, to safeguard the child victim, many social workers remove children of child sexual abuse cases and place them in alternative care. The aim of this study is to explore the perceptions of social workers on the reasons why child sexual abuse cases in alternative care is not finalized. Some of the factors tha...
Full Text Available Objective: Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods: Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results: A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions: The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge
Neller, Daniel J; Petris, Giovanni
The sexual recidivism rate of sex offenders is a controversial issue. Perhaps as controversial is the sexual recidivism rate of the select group of sex offenders who are examined pursuant to sexually violent predator (SVP) statutes. At present, reliable estimates of SVP recidivism are unavailable. We propose that reasonable estimates of SVP recidivism can be reached by considering three available pieces of data: (i) a likely recidivism rate of the general population of sex offenders; (ii) procedures typically followed by jurisdictions that civilly commit sex offenders; and (iii) classification accuracy of procedures. Although sexual recidivism rates vary across jurisdictions, the results of our analyses suggest sex offenders referred for examination pursuant to SVP statutes recidivate at substantially higher rates than typical sex offenders. Our results further suggest that sex offenders recommended for commitment as SVPs recidivate at even greater rates than SVP respondents who are not recommended for commitment. We discuss practice and policy implications of these findings. PMID:23620130
This paper aims to describe the priority-setting procedure for new original pharmaceuticals practiced by the Swedish Pharmaceutical Benefits Board (LFN), to analyse the outcome of the procedure in terms of decisions and the relative importance of ethical principles, and to examine the reactions of stakeholders. All the 'principally important' decisions made by the LFN during its first 33 months of operation were analysed. The study is theoretically anchored in the theory of fair and legitimate priority-setting procedures by Daniels and Sabin, and is based on public documents, media articles, and semi-structured interviews. Only nine cases resulted in a rejection of a subsidy by the LFN and 15 in a limited or conditional subsidy. Total rejections rather than limitations gave rise to actions by stakeholders. Primarily, the principle of cost-effectiveness was used when limiting/conditioning or totally rejecting a subsidy. This study suggests that implementing a priority-setting process that fulfils the conditions of accountability for reasonableness can result in a priority-setting process which is generally perceived as fair and legitimate by the major stakeholders and may increase social learning in terms of accepting the necessity of priority setting in health care. The principle of cost-effectiveness increased in importance when the demand for openness and transparency increased. PMID:18634660
Miles, Anna; Friary, Philippa; Jackson, Bianca; Sekula, Julia; Braakhuis, Andrea
This study evaluated hospital readiness and interprofessional clinical reasoning in speech-language pathology and dietetics students following a simulation-based teaching package. Thirty-one students participated in two half-day simulation workshops. The training included orientation to the hospital setting, part-task skill learning and immersive simulated cases. Students completed workshop evaluation forms. They filled in a 10-question survey regarding confidence, knowledge and preparedness for working in a hospital environment before and immediately after the workshops. Students completed written 15-min clinical vignettes at 1 month prior to training, immediately prior to training and immediately after training. A marking rubric was devised to evaluate the responses to the clinical vignettes within a framework of interprofessional education. The simulation workshops were well received by all students. There was a significant increase in students' self-ratings of confidence, preparedness and knowledge following the study day (p < .001). There was a significant increase in student overall scores in clinical vignettes after training with the greatest increase in clinical reasoning (p < .001). Interprofessional simulation-based training has benefits in developing hospital readiness and clinical reasoning in allied health students. PMID:26803776
Holder, L. N.; Herbert, B. E.
Understanding how students use their conceptual models to reason about societal challenges involving societal issues such as natural hazard risk assessment, environmental policy and management, and energy resources can improve instructional activity design that directly impacts student motivation and literacy. To address this question, we created four laboratory exercises for an introductory physical geology course at Texas A&M University that engages students in authentic scientific practices by using real world problems and issues that affect societies based on the theory of situated cognition. Our case-study design allows us to investigate the various ways that students utilize model based reasoning to identify and propose solutions to societally relevant issues. In each of the four interventions, approximately 60 students in three sections of introductory physical geology were expected to represent and evaluate scientific data, make evidence-based claims about the data trends, use those claims to express conceptual models, and use their models to analyze societal challenges. Throughout each step of the laboratory exercise students were asked to justify their claims, models, and data representations using evidence and through the use of argumentation with peers. Cognitive apprenticeship was the foundation for instruction used to scaffold students so that in the first exercise they are given a partially completed model and in the last exercise students are asked to generate a conceptual model on their own. Student artifacts, including representation of earth systems, representation of scientific data, verbal and written explanations of models and scientific arguments, and written solutions to specific societal issues or environmental problems surrounding earth systems, were analyzed through the use of a rubric that modeled authentic expertise and students were sorted into three categories. Written artifacts were examined to identify student argumentation and
Reverberi, Carlo; Shallice, Tim; D'Agostini, Serena; Skrap, Miran; Bonatti, Luca L.
Elementary deduction is the ability of unreflectively drawing conclusions from explicit or implicit premises, on the basis of their logical forms. This ability is involved in many aspects of human cognition and interactions. To date, limited evidence exists on its cortical bases. We propose a model of elementary deduction in which logical…
Full Text Available Cost estimation is one of the most critical tasks for building construction project management. The existing building construction cost estimation methods of many countries, including China, require information from several sources, including material, labor, and equipment, and tend to be manual, time-consuming, and error-prone. To solve these problems, a building construction cost estimation model based on ontology representation and reasoning is established, which includes three major components, i.e., concept model ontology, work item ontology, and construction condition ontology. Using this model, the cost estimation information is modeled into OWL axioms and SWRL rules that leverage the semantically rich ontology representation to reason about cost estimation. Based on OWL axioms and SWRL rules, the cost estimation information can be translated into a set of concept models, work items, and construction conditions associated with the specific construction conditions. The proposed method is demonstrated in Protégé 3.4.8 through case studies based on the Measurement Specifications of Building Construction and Decoration Engineering taken from GB 50500-2013 (the Chinese national mandatory specifications. Finally, this research discusses the limitations of the proposed method and future research directions. The proposed method can help a building construction cost estimator extract information more easily and quickly.
姜洋; 冯志勇; 王鑫马晓宁
A new concept of rare axis based on statistical facts is proposed, and an evaluation algorithm is designed thereafter. For the nested regular expressions containing rare axes, the proposed algorithm can reduce its evaluation complexity from polynomial time to nearly linear time. The distributed technique is also employed to construct the navigation axis indexes for resource description framework (RDF) graph data. Experiment results in DrugBank and BioGRID show that this method can improve the query efficiency significantly while ensuring the accuracy and meet the query requirements on Web-scale RDF graph data.
SERGIO ALEJANDRO GÓMEZ; CARLOS IVÁN CHESÑEVAR; GUILLERMO RICARDO SIMARI
The notion of forms as a way of organizing and presenting data has been used since the beginning of the World Wide Web. Web-based forms have evolved together with the development of new markup languages, in which it is possible to provide validation scripts as part of the form code to test whether the intended meaning of the form is correct. However, for the form designer, part of this intended meaning frequently involves other features which are not constraints by themselves, but rather attr...
This paper introduces context algebras and demonstrates their application to combining logical and vector-based representations of meaning. Other approaches to this problem attempt to reproduce aspects of logical semantics within new frameworks. The approach we present here is different: We show how logical semantics can be embedded within a vector space framework, and use this to combine distributional semantics, in which the meanings of words are represented as vectors, with logical semantics, in which the meaning of a sentence is represented as a logical form.
曾珠; 吕书玉; 李冰
Ontology theories are applied to after-sale service of motor car in this paper.In modeling the problem,three ontology models are constructed,they are:ontology of driving behavior,ontology of driving environment,and ontology of automobile domain.With these models and their association,an ontology model for automotive after-sale service is built.Thus,the intrinsic factors affecting automotive after-sales service are clarified.Then,based on the model,a similarity calculation method for automotive after-sale service is put forward based on case-oriented reasoning.%将本体论理论方法应用于汽车售后服务领域,利用本体论构造客户驾驶行为本体、驾驶环境本体和汽车领域本体,并结合这三个本体之间的关联,构建汽车售后服务本体模型,从而厘清了影响汽车售后服务诸因素的内在关联.根据汽车售后服务本体模型提出驾驶行为相似度和驾驶环境相似度的度量方法,基于驾驶行为相似度、道路环境相似度和气候环境相似度,提出了案例相似度的计算方法.
Kristensen, Hanne Kaae; Borg, Tove; Hounsgaard, Lise
within stroke rehabilitation. METHODS: The study was based on a phenomenological hermeneutical and an action research approach in collaboration with three occupational therapy settings including 25 occupational therapists. Data collection consisted of 41 field observations, 14 individual interviews, and......BACKGROUND: When implementing evidence-based practice in occupational therapy the investigation of clinical reasoning provides important information on research utilization. AIM: This study investigates aspects affecting occupational therapists' reasoning when implementing research-based evidence...... research-based clinical guidelines....
Johnson, Mike; Rilee, M.; Truszkowski, W.; Powers, Edward I. (Technical Monitor)
of environmental hazards, frame the problem of constructing autonomous science instruments. we are developing a model of the Low Energy Neutral Atom instrument (LENA) that is currently flying on board the Imager for Magnetosphere-to-Aurora Global Exploration (IMAGE) spacecraft. LENA is a particle detector that uses high voltage electrostatic optics and time-of-flight mass spectrometry to image neutral atom emissions from the denser regions of the Earth's magnetosphere. As with most spacecraft borne science instruments, phenomena in addition to neutral atoms are detected by LENA. Solar radiation and energetic particles from Earth's radiation belts are of particular concern because they may help generate currents that may compromise LENA's long term performance. An explicit model of the instrument response has been constructed and is currently in use on board IMAGE to dynamically adapt LENA to the presence or absence of energetic background radiations. The components of LENA are common in space science instrumentation, and lessons learned by modelling this system may be applied to other instruments. This work demonstrates that a model-based approach can be used to enhance science instrument effectiveness. Our future work involves the extension of these methods to cover more aspects of LENA operation and the generalization to other space science instrumentation.
Full Text Available In this study, we proposed a modular approach for description logic reasoning to meet the on-demand and scalability requirement semantic-based systems. One typical use of description logic knowledge-base is to support reasoning in semantic-based systems. However, including large description logic knowledge-bases in their complete form in applications would imply unnecessarily huge storage and computational requirement. Therefore, we go beyond the use of static description logic knowledge-base by reusing knowledge dynamically. In particular, we refer to the context-specific contents from large-scale description logic knowledge-bases as description logic modules. A tableau algorithm based on the description logic module representation is given to support modular description logic reasoning. In order to solve the semi-deterministic problem of modular reasoning, we propose an expansion reasoning algorithm for preserving consistency. We also analyzed the time complexity of the modular reasoning algorithm under different conditions. The proposed algorithm improved the performance of description logic reasoning by modulization, especially when the scale of the knowledge-base is very large.
Full Text Available Abstract Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871 that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED based on experimental variables and their interdependencies. The software has three parts: (a the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger
Full Text Available Abstract Introduction Computed tomography colonography, or virtual colonoscopy, is a good alternative to optical colonoscopy. However, suboptimal patient preparation or colon distension may reduce the diagnostic accuracy of this imaging technique. Case presentation We report the case of an 83-year-old Caucasian woman who presented with a five-month history of pneumaturia and fecaluria and an acute episode of macrohematuria, leading to a high clinical suspicion of a colovesical fistula. The fistula was confirmed by standard contrast-enhanced computed tomography. Optical colonoscopy was performed to exclude the presence of an underlying colonic neoplasm. Since optical colonoscopy was incomplete, computed tomography colonography was performed, but also failed due to inadequate colon distension. The insufflated air directly accumulated within the bladder via the large fistula. Conclusions Clinicians should consider colovesical fistula as a potential reason for computed tomography colonography failure.
Kapil Khandelwal; Durga Prasad Sharma
In this paper, we briefly outlined popular case-based reasoning combinations. More specifically, we focus on combinations of case-based reasoning with rule based reasoning, and model based reasoning. Further we examined the strengths and weaknesses of various reasoning models, case-based reasoning, rule-based reasoning and model-based reasoning, and discuss how they can be combined to form a more robust and better-performing hybrid. In a decision support system to address the variety of tasks...
This paper focused on the integration of case base and relational database management system (RDBMS). The organizational and commercial impact will be far greater if the case-based reasoning (CBR) system is integrated with main stream information system, which is exemplified by RDBMS. The scalability, security and robustness provided by a commercial RDBMS facilitate the CBR system to manage the case base.The virtual table in relational database (RDB) is important for CBR systems to implement the flexibility of case template. It was discussed how to implement a flexible and succinct case template, and a mapping model between case template and RDB was proposed. The key idea is to build the case as the virtual view of underlying data.
Lu Qiang; Shen Guanting; and Liu Xiaoping
Aiming at the deficiencies of analysis capacity from different levels and fuzzy treating method in product function modeling of conceptual design, the theory of quotient space and universal triple I fuzzy reasoning method are introduced, and then the function modeling algorithm based on the universal triple I fuzzy reasoning method is proposed. Firstly, the product function granular model based on the quotient space theory is built, with its function granular representation and computing rules defined at the same time. Secondly, in order to quickly achieve function granular model from function requirement, the function modeling method based on universal triple I fuzzy reasoning is put forward. Within the fuzzy reasoning of universal triple I method, the small-distance-activating method is proposed as the kernel of fuzzy reasoning; how to change function requirements to fuzzy ones, fuzzy computing methods, and strategy of fuzzy reasoning are respectively investigated as well; the function modeling algorithm based on the universal triple I fuzzy reasoning method is achieved. Lastly, the validity of the function granular model and function modeling algorithm is validated. Through our method, the reasonable function granular model can be quickly achieved from function requirements, and the fuzzy character of conceptual design can be well handled, which greatly improves conceptual design.
Full Text Available In this paper, one conflict context reasoning method based on Dempster-Shafer theory is proposed. Firstly the context conflict problems are illustrated and partitioned based on theory of evidence. Then the context model combined with Dempster-Shafer theory is presented and applied to the reasoning method based on Dempster rule of combination. The effectiveness of this method is verified with a RFID application example.
In this paper, one conflict context reasoning method based on Dempster-Shafer theory is proposed. Firstly the context conflict problems are illustrated and partitioned based on theory of evidence. Then the context model combined with Dempster-Shafer theory is presented and applied to the reasoning method based on Dempster rule of combination. The effectiveness of this method is verified with a RFID application example.
Kristin Prehn; Marc Korczykowski; Hengyi Rao; Zhuo Fang; Detre, John A.; Diana C Robertson
Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema) or based on adherence to laws and rules (maintaining norms schema), whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which mora...
Kapetanakis, Stelios; Filippoupolitis, Avgoustinos; Loukas, George; Al Murayziq, Tariq Saad
Computer security would arguably benefit from more information on the characteristics of the particular human attacker behind a security incident. Nevertheless, technical security mechanisms have always focused on the at- tack's characteristics rather than the attacker's. The latter is a challenging prob- lem, as relevant data cannot easily be found. We argue that the cyber traces left by a human attacker during an intrusion attempt can help towards building a profile of the particular person...
Alves, Victor; Novais, Paulo; Nelas, Luís; Maia, Moreira; Ribeiro, Victor
Embedding Machine Learning technology into Intelligent Diagnosis Systems adds a new potential to such systems and in particular to the imagiology ones. In our work, this is achieved using the data acquired from MEDsys, a computational environment that supports medical diagnosis systems that use an amalgam of knowledge discovery and data mining techniques, which use the potential of an extension to the language of Logic Programming, with the functionalities of a connectionist approach to probl...
The thesis consists of three journal articles (one published in Journal of Industrial Management and Data Systems, nine pages, and two accepted for publication in International Journal of Learning and Intellectual Capital, and Journal of Production Planning & Control, 10 and 22 pages respectively...
Delany, Sarah Jane
pam is a universal problem with which everyone is familiar. Figures published in 2005 state that about 75% of all email sent today is spam. In spite of significant new legal and technical approaches to combat it, spam remains a big problem that is costing companies meaningful amounts of money in lost productivity, clogged email systems, bandwidth and technical support. A number of approaches are used to combat spam including legislative measures, authentication approaches and email filtering....
Healy, Matt, (Thesis)
Text classification is the categorization of text into a predefined set of categories. Text classification is becoming increasingly important given the large volume of text stored electronically e.g. email, digital libraries and the World Wide Web (WWW). These documents represent a massive amount of information that can be accessed easily. To gain benefit from using this information requires organisation. One way of organising it automatically is to use text classification. A number of well k...
Vivek Jaglan,; Surjeet Dalal,; Dr. S. Srinivasan
The managers should be skilled to make better decisions in the business organization. They also need a supportive environment where they won’t be unfairly criticised for making wrong decisions. Decisionmaking increasingly happens at all levels of a business. Business Intelligence delivers the appropriate data at the proper time and in the precise arrangement. It offers user-friendly information openly to users where they can work, team up, and make resolutions. Although the business intellige...
Chen, Shyi-Ming; Hsin, Wen-Chyuan
In this paper, we propose a new weighted fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on the slopes of fuzzy sets. We also propose a particle swarm optimization (PSO)-based weights-learning algorithm to automatically learn the optimal weights of the antecedent variables of fuzzy rules for weighted fuzzy interpolative reasoning. We apply the proposed weighted fuzzy interpolative reasoning method using the proposed PSO-based weights-learning algorithm to deal with the computer activity prediction problem, the multivariate regression problems, and the time series prediction problems. The experimental results show that the proposed weighted fuzzy interpolative reasoning method using the proposed PSO-based weights-learning algorithm outperforms the existing methods for dealing with the computer activity prediction problem, the multivariate regression problems, and the time series prediction problems. PMID:25204003
Taís Quevedo Marcolino
The Clinical Reasoning Study supported by the American Occupational Therapy Association/AOTA and the American Occupational Therapy Foundation/AOTF in the United States in the late 1980s, had inaugurated the scientific production in the field and offered an initial framework on clinical reasoning for understanding and conducting clinical cases in Occupational Therapy. Most of the researches in this field have focused on reasoning processes, and point out the need to understand the contents of ...
Nievelstein, Fleurie; van Gog, Tamara; Van Dijck, Gijs; Boshuizen, Els
Nievelstein, F., Van Gog, T., Van Dijck, G., & Boshuizen, H. P. A. (2013). The worked example and expertise reversal effect in less structured tasks: Learning to reason about legal cases. Contemporary Educational Psychology, 38, 118–125.
Full Text Available Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema or based on adherence to laws and rules (maintaining norms schema, whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA students. Subjects completed the Defining Issues Test (DIT-2 which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago.
Prehn, Kristin; Korczykowski, Marc; Rao, Hengyi; Fang, Zhuo; Detre, John A; Robertson, Diana C
Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema) or based on adherence to laws and rules (maintaining norms schema), whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA) students. Subjects completed the Defining Issues Test (DIT-2) which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago. PMID:26039547
J. L. Schellenberg argues in the book Divine Hiddenness and Human Reason that the apparent hiddenness of God is—in itself—an atheistic argument. His argument takes as the starting premise: If a perfectly loving God exists, reasonable nonbelief does not occur. Then he tries to show that reasonable nonbelief does occur. Thus, the conclusion is that he has an argument of considerable force from the reasonableness of nonbelief to the nonexistence of God. I find that the argument of Schellenbe...
J Michael Pearson; Emad A. Abu Shanab; Khalil Md Nor
ABSTRACT The theory of reasoned action originally introduced in the field of Social Psychology has been widely used to explain individuals’ behaviour. The theory postulates that individuals’ behaviour is influenced by their attitude and subjective norm. The purpose of this study was to determine factors that influence an individual’s intention to use a technology based on the theory of reasoned action. We used Internet banking as the target technology and Malaysian subjects as the sampling fr...
Møller, Signe Juhl; Tenenbaum, Harriet R.
perpetrator of the exclusion and the social identity of the target. Children assessed exclusion based on ethnicity as less acceptable than exclusion based on gender and used more moral reasoning for the former than the latter. Children judged it less acceptable for a teacher than a child to exclude a child...
Forsberg, Elenita; Ziegert, Kristina; Hult, Håkan; Fors, Uno
In health-care education, it is important to assess the competencies that are essential for the professional role. To develop clinical reasoning skills is crucial for nursing practice and therefore an important learning outcome in nursing education programmes. Virtual patients (VPs) are interactive computer simulations of real-life clinical scenarios and have been suggested for use not only for learning, but also for assessment of clinical reasoning. The aim of this study was to investigate how experienced paediatric nurses reason regarding complex VP cases and how they make clinical decisions. The study was also aimed to give information about possible issues that should be assessed in clinical reasoning exams for post-graduate students in diploma specialist paediatric nursing education. The information from this study is believed to be of high value when developing scoring and grading models for a VP-based examination for the specialist diploma in paediatric nursing education. Using the think-aloud method, data were collected from 30 RNs working in Swedish paediatric departments, and child or school health-care centres. Content analysis was used to analyse the data. The results indicate that experienced nurses try to consolidate their hypotheses by seeing a pattern and judging the value of signs, symptoms, physical examinations, laboratory tests and radiology. They show high specific competence but earlier experience of similar cases was also of importance for the decision making. The nurses thought it was an innovative assessment focusing on clinical reasoning and clinical decision making. They thought it was an enjoyable way to be assessed and that all three main issues could be assessed using VPs. In conclusion, VPs seem to be a possible model for assessing the clinical reasoning process and clinical decision making, but how to score and grade such exams needs further research. PMID:23938093
Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang
In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.
Kerruish, Nicola; McMillan, John R
In 2006 a case report was published about a 6-year-old girl, Ashley, who has profound developmental disabilities and was treated with oestrogen patches to limit her final height, along with a hysterectomy and the removal of her breast buds. Ashley's parents claimed that attenuating her growth would make it possible for them to lift and move her more easily, facilitating greater involvement in family activities and making routine care more straightforward. The 'Ashley treatment' provoked public comment and academic debate and remains ethically controversial. As more children are being referred for such treatment, there is an urgent need to clarify how clinicians and ethics committees should respond to such requests. The controversy surrounding the Ashley treatment exists, at least in part, because of gaps in the literature, including a lack of empirical data about the outcomes for children who do and do not receive such treatment. However, we suggest in this paper that there is also merit in examining the parental decision-making process itself, and provide empirical data about the reasoning of one set of parents who ultimately chose part of this treatment for their child. Using the interview data, we illuminate some important points regarding how these parents characterise benefits and harms and their responsibilities as surrogate decision-makers. This analysis could inform decision-making about future requests for growth attenuation and might also have wider relevance to healthcare decision-making for children with profound cognitive impairment. PMID:25858291
Pigini, L; Andrich, R; Liverani, G; Bucciarelli, P; Occhipinti, E
If working tasks are carried out in inadequate conditions, workers with functional limitations may, over time, risk developing further disabilities. While several validated risk assessment methods exist for able-bodied workers, few studies have been carried out for workers with disabilities. This article, which reports the findings of a Study funded by the Italian Ministry of Labour, proposes a general methodology for the technical and organisational re-design of a worksite, based on risk assessment and irrespective of any worker disability. To this end, a sample of 16 disabled workers, composed of people with either mild or severe motor disabilities, was recruited. Their jobs include business administration (5), computer programmer (1), housewife (1), mechanical worker (2), textile worker (1), bus driver (1), nurse (2), electrical worker (1), teacher (1), warehouseman (1). By using a mix of risk assessment methods and the International Classification of Functioning (ICF) taxonomy, their worksites were re-designed in view of a reasonable accommodation, and prospective evaluation was carried out to check whether the new design would eliminate the risks. In one case - a man with congenital malformations who works as a help-desk operator for technical assistance in the Information and Communication Technology (ICT) department of a big organisation - the accommodation was actually carried out within the time span of the study, thus making it possible to confirm the hypotheses raised in the prospective assessment. PMID:20131973
J. Christopher Moore*
Full Text Available We have found that non-STEM (science, technology, engineering, and mathematics majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower preinstruction on the Lawson’s Classroom Test of Scientific Reasoning (LCTSR in comparison to national average STEM majors. Based on LCTSR score, the majority of non-STEM students can be classified as either concrete operational or transitional reasoners in Piaget’s theory of cognitive development, whereas in the STEM population formal operational reasoners are far more prevalent. In particular, non-STEM students demonstrate significant difficulty with proportional and hypothetico-deductive reasoning. Prescores on the LCTSR are correlated with normalized learning gains on various concept inventories. The correlation is strongest for content that can be categorized as mostly theoretical, meaning a lack of directly observable exemplars, and weakest for content categorized as mostly descriptive, where directly observable exemplars are abundant. Although the implementation of research-verified, interactive engagement pedagogy can lead to gains in content knowledge, significant gains in theoretical content (such as force and energy are more difficult with non-STEM students. We also observe no significant gains on the LCTSR without explicit instruction in scientific reasoning patterns. These results further demonstrate that differences in student populations are important when comparing normalized gains on concept inventories, and the achievement of significant gains in scientific reasoning requires a reevaluation of the traditional approach to physics for non-STEM students.
Moore, J. Christopher; Rubbo, Louis J.
We have found that non-STEM (science, technology, engineering, and mathematics) majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower preinstruction on the Lawson’s Classroom Test of Scientific Reasoning (LCTSR) in comparison to national average STEM majors. Based on LCTSR score, the majority of non-STEM students can be classified as either concrete operational or transitional reasoners in Piaget’s theory of cognitive development, whereas in the STEM population formal operational reasoners are far more prevalent. In particular, non-STEM students demonstrate significant difficulty with proportional and hypothetico-deductive reasoning. Prescores on the LCTSR are correlated with normalized learning gains on various concept inventories. The correlation is strongest for content that can be categorized as mostly theoretical, meaning a lack of directly observable exemplars, and weakest for content categorized as mostly descriptive, where directly observable exemplars are abundant. Although the implementation of research-verified, interactive engagement pedagogy can lead to gains in content knowledge, significant gains in theoretical content (such as force and energy) are more difficult with non-STEM students. We also observe no significant gains on the LCTSR without explicit instruction in scientific reasoning patterns. These results further demonstrate that differences in student populations are important when comparing normalized gains on concept inventories, and the achievement of significant gains in scientific reasoning requires a reevaluation of the traditional approach to physics for non-STEM students.
J Michael Pearson
Full Text Available ABSTRACT The theory of reasoned action originally introduced in the field of Social Psychology has been widely used to explain individuals’ behaviour. The theory postulates that individuals’ behaviour is influenced by their attitude and subjective norm. The purpose of this study was to determine factors that influence an individual’s intention to use a technology based on the theory of reasoned action. We used Internet banking as the target technology and Malaysian subjects as the sampling frame. A principal component analysis was used to validate the constructs and multiple regressions were used to analyze the data. As expected, the results supported the theory’s proposition as that an individuals’ behavioural intention to use Internet banking is influenced by their attitude and subjective norm. Based on the findings, theoretical and practical implications were offered. Keywords: theory of reasoned action, Internet banking, technology acceptance
Full Text Available In the ubiquitous computing environment, context reasoning is an important issue of context-awareness. It is used to deduce desired or higher-level context and then to provide suitable services automatically. The previous context-reasoning approaches are mainly non-temporal. The reasoning is according to the real-time contexts without time information. However, temporal contexts are very important information for context-awareness. Therefore, a model, called TempCRM (Temporal Context Reasoning Model, based on Resource Description Framework (RDF and Web Ontology Language (OWL is proposed in this paper. TempCRM is used for inferring the dangerous level of a smart home. In a home environment, a potential dangerous situation is caused by a series of temporal events. A temporal event is represented as a RDF-based temporal context. A smart home ontology is defined for the terms and relationships used in the temporal context. Then, a set of reasoning rules can be defined for inferring and computing the dangerous level. In the simulation study, a script with dangerous situations is designed to evaluate the dangerous level generated by TempCRM. The result illustrates that TempCRM is useful to alarm the inhabitant and thus prevent the occurrence of an incident from the temporal contexts.
Full Text Available In this paper, the perturbation of fuzzy connectives and the robustness of fuzzy reasoning are investigated. This perturbation of Schweizer-Sklar parameterized t-norms and its residuated implication operators are given. We show that full implication triple I algorithms based on Schweizer-sklar operators are robust for normalized Minkowski distance.
Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.
We review and extend existing frameworks on modeling to develop a new framework that describes model-based reasoning in introductory and upper-division physics laboratories. Constructing and using models are core scientific practices that have gained significant attention within K-12 and higher education. Although modeling is a broadly applicable…
Arici, Sevil; Aslan-Tutak, Fatma
This research study examined the effect of origami-based geometry instruction on spatial visualization, geometry achievement, and geometric reasoning of tenth-grade students in Turkey. The sample ("n" = 184) was chosen from a tenth-grade population of a public high school in Turkey. It was a quasi-experimental pretest/posttest design. A…
In this talk, we present a work in progress on the representation and manipulation of semi-structured data in an object-based representation environment. This research work is carried out in the field of knowledge representation and reasoning in order to build intelligent systems (according to artificial intelligence standards).
Witschonke, Christopher; Herrera, Jose Maria
The authors describe an economics-based game they have developed to instruct student teachers in the value of games and gaming for developing reasoning and decision-making skills in economics in K-12 students (5-18-year-olds). The game is designed to progress through each grade level so that by high school students have a thorough appreciation and…
Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nyström, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit
Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2012). Conveying clinical reasoning based on visual observation via eye-movement modelling examples. Instructional Science, 40(5), 813-827. doi:10.1007/s11251-012-9218-5
Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nystrom, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit
Complex perceptual tasks, like clinical reasoning based on visual observations of patients, require not only conceptual knowledge about diagnostic classes but also the skills to visually search for symptoms and interpret these observations. However, medical education so far has focused very little on how visual observation skills can be…
Algorithms of inference in a computer system oriented to input and semantic processing of text information are presented. Such inference is necessary for logical questions when the direct comparison of objects from a question and database can not give a result. The following classes of problems are considered: a check of hypotheses for persons and non-typical actions, the determination of persons and circumstances for non-typical actions, planning actions, the determination of event cause and state of persons. To form an answer both deduction and plausible reasoning are used. As a knowledge domain under consideration is social behavior of persons, plausible reasoning is based on laws of social psychology. Proposed algorithms of inference and plausible reasoning can be realized in computer systems closely connected with text processing (criminology, operation of business, medicine, document systems).
Head, Katharine J; Noar, Seth M
This paper explores the question: what are barriers to health behaviour theory development and modification, and what potential solutions can be proposed? Using the reasoned action approach (RAA) as a case study, four areas of theory development were examined: (1) the theoretical domain of a theory; (2) tension between generalisability and utility, (3) criteria for adding/removing variables in a theory, and (4) organisational tracking of theoretical developments and formal changes to theory. Based on a discussion of these four issues, recommendations for theory development are presented, including: (1) the theoretical domain for theories such as RAA should be clarified; (2) when there is tension between generalisability and utility, utility should be given preference given the applied nature of the health behaviour field; (3) variables should be formally removed/amended/added to a theory based on their performance across multiple studies and (4) organisations and researchers with a stake in particular health areas may be best suited for tracking the literature on behaviour-specific theories and making refinements to theory, based on a consensus approach. Overall, enhancing research in this area can provide important insights for more accurately understanding health behaviours and thus producing work that leads to more effective health behaviour change interventions. PMID:25053006
In exploring the question of how humans reason in ambiguous situations or in the absence of complete information, we stumbled onto a body of knowledge that addresses issues beyond the original scope of our effort. We have begun to understand the importance that philosophy, in particular the work of C. S. Peirce, plays in developing models of human cognition and of information theory in general. We have a foundation that can serve as a basis for further studies in cognition and decision making. Peircean philosophy provides a foundation for understanding human reasoning and capturing behavioral characteristics of decision makers due to cultural, physiological, and psychological effects. The present paper describes this philosophical approach to understanding the underpinnings of human reasoning. We present the work of C. S. Peirce, and define sets of fundamental reasoning behavior that would be captured in the mathematical constructs of these newer technologies and would be able to interact in an agent type framework. Further, we propose the adoption of a hybrid reasoning model based on his work for future computational representations or emulations of human cognition
Iglesias Alvarez, Josué; Gómez Cordero, David; Bernardos Barbolla, Ana M.; Casar Corredera, Jose Ramon
This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his...
Shehab, Essam; H. S. Abdalla
Design for assembly automation (DFAA) is an important part of the concurrent engineering strategy for reduction of product manufacturing costs and lead times. An intelligent knowledge-based system (KBS) for design for automation and early cost modelling within a concurrent engineering environment has been developed. This paper focuses upon the development of the design for an assembly automation system. The system framework encompasses an extensive knowledge-based reasoning system, a CAD syst...
Sarah Kuipers, BA, BS
Full Text Available Background: Saccadic eye movements and visual information processing play an important role in reading success. Vision therapy can be a successful tool in the treatment of these conditions, but there is a variety of reasons why patients chose not to continue with this recommended treatment. Case Report: A nine-year-old male presented due to poor language arts performance on the ISTEP standardized test. He was diagnosed with saccadic dysfunction and reduced figure-ground, which made reading on the computer difficult. The patient was given educational accommodations based on the findings. Vision therapy was recommended, but his mother declined the treatment. Conclusion: This non-ideal case outlines the testing and assessment for oculomotor dysfunction and visual information processing and draws attention to issues surrounding vision therapy that may contribute to increased patient drop-out. By providing flexible office hours, increasing insurance coverage, and working with other eye care professionals to change the professional opinion regarding vision therapy, optometrists can increase the capture rate of patients in need of vision therapy services.
The purpose of the present study was twofold. First, the present study set out to investigate the learners‟ attitudes towards academic writing courses that they have to take as part of their curriculum, whether they experience second language writing anxiety and what reasons they report for their anxiety and failure in academic writing courses. Second, the study aimed to develop a selfreport measure of second language writing anxiety reasons
Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field
J. Fernandez Galarreta
Full Text Available Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs. 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.
Littlejohn, Clayton Mitchell
Pritchard’s epistemological disjunctivist thinks that when we come to know things through vision our perceptual beliefs are based on reasons that provide factive support. The reasons that constitute the rational basis for your belief that the page before you is white and covered in black marks entails that it is and includes things that could not have provided rational support for your beliefs if you had been hallucinating. There are some issues that I would like to raise. First, what motivat...
In this report, we show how to use the Simple Fluent Calculus (SFC) to specify generic tracers, i.e. tracers which produce a generic trace. A generic trace is a trace which can be produced by different implementations of a software component and used independently from the traced component. This approach is used to define a method for extending a java based CHRor platform called CHROME (Constraint Handling Rule Online Model-driven Engine) with an extensible generic tracer. The method includes a tracer specification in SFC, a methodology to extend it, and the way to integrate it with CHROME, resulting in the platform CHROME-REF (for Reasoning Explanation Facilities), which is a constraint solving and rule based reasoning engine with explanatory traces.
Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.
Lewandowski, Heather; Stetzer, Mackenzie; van de Bogart, Kevin; Dounas-Frazer, Dimitri
Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.
Chua Kia; Mohd Rizal Arshad
This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system ...
Nebot, A.; V. Mugica; Escobet, A.
MILAGRO project was conducted in Mexico City during March 2006 with the main objective of study the local and global impact of pollution generated by megacities. The research presented in this paper is framed in MILAGRO project and is focused on the study and development of modeling methodologies that allow the forecasting of daily ozone concentrations. The present work aims to develop Fuzzy Inductive Reasoning (FIR) models using the Visual-FIR platform. FIR offers a model-based approach to m...