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...
A new framework of knowledge representation of fuzzy language field and fuzzy language value structure is shown. Then the generalized cell automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model are put forward. On this basis, the new logic indeterminacy causal inductive automatic reasoning mechanism which is based on fuzzy state description is presented. At the end of this paper its application in the development of intelligent controller is discussed.
J. Dezert; Tacnet, J.M.
In this paper, we present an extension of the multi-criteria decision making based on the Analytic Hierarchy Process (AHP) which incorporates uncertain knowledge matrices for generating basic belief assignments (bba’s). The combination of priority vectors corresponding to bba’s related to each (sub)-criterion is performed using the Proportional Conflict Redistribution rule no. 5 proposed in Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. The...
Current reforms in mathematics education advocate the development of mathematical learning communities in which students have opportunities to engage in mathematical discourse and classroom practices which underlie algebraic reasoning. This article specifically addresses the pedagogical actions teachers take which structure student engagement in…
Reed, Helen C.; Hurks, Petra P. M.; Kirschner, Paul A.; Jolles, Jelle
This study investigates how shared picture book storytelling within a peer-group setting could stimulate causal reasoning in children aged 4½ to 6 years. Twenty-eight children from preschool classes of three schools were allocated to one of six groups (four to five children per group). Each group participated in six storytelling sessions over a…
Zwickl, Benjamin M.; Hu, Dehui; Finkelstein, Noah; Lewandowski, H. J.
[This paper is part of the Focused Collection on Upper Division Physics Courses.] 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 process, within physics education, it has been preferentially applied to the iterative development of broadly applicable principles (e.g., Newton's laws of motion in introductory mechanics). A significant feature of the new framework is that measurement tools (in addition to the physical system being studied) are subjected to the process of modeling. Think-aloud interviews were used to refine the framework and demonstrate its utility by documenting examples of model-based reasoning in the laboratory. When applied to the think-aloud interviews, the framework captures and differentiates students' model-based reasoning and helps identify areas of future research. The interviews showed how students productively applied similar facets of modeling to the physical system and measurement tools: construction, prediction, interpretation of data, identification of model limitations, and revision. Finally, we document students' challenges in explicitly articulating assumptions when constructing models of experimental systems and further challenges in model construction due to students' insufficient prior conceptual understanding. A modeling perspective reframes many of the seemingly arbitrary technical details of measurement tools and apparatus as an opportunity for authentic and engaging scientific sense making.
Full Text Available As geographic information interoperability and sharing developing, more and more interoperable OGC (open geospatial consortium Web services (OWS are generated and published through the internet. These services can facilitate the integration of different scientific applications by searching, finding, and utilizing the large number of scientific data and Web services. However, these services are widely dispersed and hard to be found and utilized with executive semantic retrieval. This is especially true when considering the weak semantic description of geographic information service data. Focusing on semantic retrieval and reasoning of the distributed OWS resources, a deductive and semantic reasoning method is proposed to describe and search relevant OWS resources. Specifically, ①description words are extracted from OWS metadata file to generate GISe ontology-database and instance-database based on geographic ontology according to basic geographic elements category, ②a description words reduction model is put forward to implement knowledge reduction on GISe instance-database based on rough set theory and generate optimized instances database, ③utilizing GISe ontology-database and optimized instance-database to implement semantic inference and reasoning of geographic searching objects is used as an example to demonstrate the efficiency, feasibility and recall ration of the proposed description-word-based reduction model.
Pandit, Mahesh; Mishra, Ashok K.; Paudel, Krishna P.; Larkin, Sherry L.; Rejesus, Roderick M.; Lambert, Dayton M.; English, Burton C.; Larson, James A.; Velandia, Margarita M.; Roberts, Roland K.; Kotsiri, Sofia
We used survey data collected from cotton farmers in 12 southern U.S. states to identify factors influencing cotton farmers’ decisions to adopt precision farming. Using a seemingly unrelated ordered probit model, we found that younger, educated and computer literate farmers chose precision farming for profit reason. Farmers who perceived precision farming to be profitable adopt it to be at the forefront of agricultural technology. We also found that farmers who were concerned with environment...
Full Text Available With the growing abundance of information on the web, it becomes the need of the hour to enrich data with semantics that can be understood and processed by machines. Currently, much of the effort in the area of semantics is focused on the representation of semantic data and its reasoning, which is the processing of semantic information associated with that data. This paper aims at realizing the need for similarity based reasoning of cloud service discovery. It forms a basic requirement of a cloud client to discover the most appropriate cloud service from the list of available services published by service providers. Cloud ontology provides a set of concepts, individuals and relationships among them. The similarity among cloud services can be determined from the semantic similarity of concepts and hence the relevant service can be retrieved.
ZHANG Zhiying; LI Zhen; JIANG Zhibin
Computer-aided block assembly process planning based on rule-reasoning are developed in order to improve the assembly efficiency and implement the automated block assembly process planning generation in shipbuilding. First, weighted directed liaison graph (WDLG) is proposed to represent the model of block assembly process according to the characteristics of assembly relation, and edge list (EL) is used to describe assembly sequences. Shapes and assembly attributes of block parts are analyzed to determine the assembly position and matched parts of parts used frequently. Then, a series of assembly rules are generalized, and assembly sequences for block are obtained by means of rule reasoning. Final, a prototype system of computer-aided block assembly process planning is built. The system has been tested on actual block, and the results were found to be quite efficiency. Meanwhile, the fundament for the automation of block assembly process generation and integration with other systems is established.
Full Text Available There is a vast literature on evidence-based practice (EBP in education. What function does evidence have in practical deliberations toward decisions about what to do? Most writers on EBP seem to think of evidence largely as quantitative data, serving as a foundation from which practice could and should be directly derived. In this paper I argue that we are better served by according a different and more indirect function to evidence in practical reasoning. To establish this claim I employ Toulmin’s model of argumentation. On this model the evidence-as-foundation view amounts to evidence as data/grounds. The model also offers a different function for evidence, as backing of the warrant, and I argue in this paper that this is a more adequate understanding of the function of evidence in practical reasoning
The book puts special stress on the contemporary techniques for reasoning-based image processing and analysis: learning based image representation and advanced video coding; intelligent image processing and analysis in medical vision systems; similarity learning models for image reconstruction; visual perception for mobile robot motion control, simulation of human brain activity in the analysis of video sequences; shape-based invariant features extraction; essential of paraconsistent neural networks, creativity and intelligent representation in computational systems. The book comprises 14 chapters. Each chapter is a small monograph, representing resent investigations of authors in the area. The topics of the chapters cover wide scientific and application areas and complement each-other very well. The chapters’ content is based on fundamental theoretical presentations, followed by experimental results and comparison with similar techniques. The size of the chapters is well-ballanced which permits a thorough ...
In view of the mid and long term runoff forecasting containing many uncertain factors,this paper constructs a uncertain reasoning model (UR) based on the cloud theory to solve the problem of uncertain reasoning.Firstly,in the proposed model,a classification method,i.e.,attribute oriented induction maximum variance (MaxVar),is used to divide the runoff series into different intervals,which are softened and described by the cloud membership with expected value (Ex),entropy (En) and hyper-entropy (He),then an uncertain reasoning rule set is constructed by means of the runoff value generalization and applied to monthly flow for uncertain prediction.Next,a new modification formula is used to calculate He in runoff forecasting,and a confident level probability prediction interval is obtained by statistical method.Finally,this paper takes the monthly flow of Manwan station in China as an example and uses UR model,LSSVM model,and ARMA model to calculate the monthly flow,respectively.The results show that the UR model has the highest prediction accuracy compared to other models,and that it not only provides random output but also supports probability interval prediction.
The paper introduces the complex approach to determining possible geological reasons causing rate decline in the wells of Field T, Russia. Therefore, possible geological reasons are sequentially considered and were divided into three main groups: 1) rate decline due to poorer reservoir quality; 2) rate decline due to facies lateral substitution; 3) rate decline due to active fault tectonics. The most appropriate facies models were constructed on the basis of all available data. Besides, in this study, core, well logging, seismic and well test data were integrated for the fullest reservoir characterization. The core from several recently drilled wells was described in detail to determine clue features. Further, seismic data were interpreted: structural interpretation, including faults and attribute analysis, was implemented. Appropriate electrofacies models were chosen as well. At the final stage, all previously-mentioned data were integrated with appropriate facies model construction. However, as it turned out later, the facies model was not the key factor affecting the rapid decline that appeared in some wells. It is suggested that very proximal faults can be a possible explanation. To confirm this suggestion, well test data were additionally used and both analytical and numerical methods were applied to show the consistency of this theory
A. S. L. Lindawati
Full Text Available The objective of this study is to explore the user’s perceptions of the role of moral reasoning in influencing the implementation of codes of ethics as standards and guidance for professional audit practice by Indonesian public accountants. The study focuses on two important aspects of influence: (i the key factors influencing professional public accountants in implementing a code of ethics as a standard for audit practice, and (ii the key activities performed by public accountants as moral agents for establishing awareness of professional values. Two theoretical approaches/models are used as guides for exploring the influence of moral reasoning of public accountants: first, Kolhberg’s model of moral development (Kolhberg 1982 and, secondly, the American Institute of Certified Public Accountants (AICPA’s Code of Conduct, especially the five principles of the code of ethics (1992, 2004. The study employs a multiple case study model to analyse the data collected from interviewing 15 financial managers of different company categories (as users. The findings indicate that (i moral development is an important component in influencing the moral reasoning of the individual public accountants, (ii the degree of professionalism of public accountants is determined by the degree of the development of their moral reasoning, and (iii moral reasoning of individuals influences both Indonesian public accountants and company financial managers in building and improving the effectiveness of the implementation of codes of conduct. It is concluded that the role of moral reasoning is an important influence on achieving ethical awareness in public accountants and financial managers. The development of a full code of ethics and an effective compliance monitoring system is essential for Indonesia if it is to play a role in the emerging global economy.
Haouchine, Mohamed-Karim; Chebel-Morello, Brigitte; Zerhouni, Noureddine
The main goal of a Case-Based Reasoning (CBR) system is to provide criteria for evaluating the internal behavior and task efficiency of a particular system for a given initial case base and sequence of a solved problems. The choice of Case Base Maintenance (CBM) strategies is driven by the maintainer's performance goals for the system and by constraints on the system's design and the task environment. This paper gives an overview of CBM works and proposes a case deletion strategy based on a c...
Neroladaki Angeliki; Breguet Romain; Botsikas Diomidis; Terraz Sylvain; Becker Christoph D; Montet Xavier
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 fi...
Ahmad, Sabrina; Jalil, Intan Ermahani A.; Ahmad, Sharifah Sakinah Syed
It is seldom technical issues which impede the process of eliciting software requirements. The involvement of multiple stakeholders usually leads to conflicts and therefore the need of conflict detection and resolution effort is crucial. This paper presents a conceptual model to further improve current efforts. Hence, this paper forwards an improved conceptual model to assist the conflict detection and resolution effort which extends the model ability and improves overall performance. The significant of the new model is to empower the automation of conflicts detection and its severity level with rule-based reasoning.
Gay-Bellile, Vincent; Bartoli, Adrien; Sayd, Patrick
The registration problem for images of a deforming surface has been well studied. External occlusions are usually well handled. In 2D image-based registration, self-occlusions are more challenging. Consequently, the surface is usually assumed to be only slightly self-occluding. This paper is about image-based nonrigid registration with self-occlusion reasoning. A specific framework explicitly modeling self-occlusions is proposed. It is combined with an intensity-based, "direct" data term for registration. Self-occlusions are detected as shrinkage areas in the 2D warp. Experimental results on several challenging data sets show that our approach successfully registers images with self-occlusions while effectively detecting the self-occluded regions. PMID:19926901
Ling Weiqing; Yan Junwei; Wang Jian; Xie Youbai
The current method of case-based design (CBD) can be well practiced for configuration design in which design experience knowledge is involved.However, since the design case is confined to a certain application domain, it is difficult for CBD to be applied to conceptual design process that develops concepts to meet design specifications.Firstly, a function factor description space is erected to provide an exhibition room for all functions of design cases.Next, the approach for identifying the space state of function factor in description space is proposed, including the determination of the similarities between function factors of design case.And then a general object-oriented representation for design case is presented by bringing the class of function and in-out flow into the current case representation.Finally, a living example for electro-pet design that illustrates the implementation of the method for case-based conceptual design based on distributed design case repositories is described.
Full Text Available 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 for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain.
Cevik, Yasemin Demiraslan; Andre, Thomas
This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…
Full Text Available Mariam Fida,1 Salah Eldin Kassab2 1Department of Molecular Medicine, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain; 2Department of Medical Education, Faculty of Medicine, Suez Canal University, Ismailia, Egypt Purpose: The development of clinical problem-solving skills evolves over time and requires structured training and background knowledge. Computer-based case simulations (CCS have been used for teaching and assessment of clinical reasoning skills. However, previous studies examining the psychometric properties of CCS as an assessment tool have been controversial. Furthermore, studies reporting the integration of CCS into problem-based medical curricula have been limited. Methods: This study examined the psychometric properties of using CCS software (DxR Clinician for assessment of medical students (n=130 studying in a problem-based, integrated multisystem module (Unit IX during the academic year 2011–2012. Internal consistency reliability of CCS scores was calculated using Cronbach's alpha statistics. The relationships between students' scores in CCS components (clinical reasoning, diagnostic performance, and patient management and their scores in other examination tools at the end of the unit including multiple-choice questions, short-answer questions, objective structured clinical examination (OSCE, and real patient encounters were analyzed using stepwise hierarchical linear regression. Results: Internal consistency reliability of CCS scores was high (α=0.862. Inter-item correlations between students' scores in different CCS components and their scores in CCS and other test items were statistically significant. Regression analysis indicated that OSCE scores predicted 32.7% and 35.1% of the variance in clinical reasoning and patient management scores, respectively (P<0.01. Multiple-choice question scores, however, predicted only 15.4% of the variance in diagnostic performance scores (P<0.01, while
Full Text Available Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.
The authors examine how the Russian judiciary devises legal policies when adjudicating cases in which religious beliefs are concerned. First, the authors describe the theoretical framework within which research on this matter can be conducted. This framework can be constructed on the basis of the theory of legal argumentation. Applying this framework to the investigation of the Russian court practice enables the authors to discover important features which are characteristic of legal reasonin...
Zourlidou, S.; Sester, M.
The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location - thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster) and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.
Full Text Available Urticaria is mainly a fast consisting, scabious, erythematous and swelling lesions of the skin. Acute urticaria usually occurs after having a medicine or food. On the other hand, in the chronic urticaria, the process is longer, more scabious, and the skin lesions are more dramatic. In urticarial vasculitis, the lesions exist longer than 24 hours with pain or swelter instead of itchiness. It can be distinguished from basic urticaria with the damage of the small vessels by histopathologically. Here we present two normocomplementhemic urticarial vasculitis cases.
Sukumar, Sreenivas Rangan [ORNL
Finding actionable insights from data has always been difficult. As the scale and forms of data increase tremendously, the task of finding value becomes even more challenging. Data scientists at Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g. Urika-XA and Urika-GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with unstructured Big Data. We present the deployment of such a framework called ORiGAMI (Oak Ridge Graph Analytics for Medical Innovations) on the National Library of Medicine s SEMANTIC Medline (archive of medical knowledge since 1994). Medline contains over 70 million knowledge nuggets published in 23.5 million papers in medical literature with thousands more added daily. ORiGAMI is available as an open-science medical hypothesis generation tool - both as a web-service and an application programming interface (API) at http://hypothesis.ornl.gov . Since becoming an online service, ORIGAMI has enabled clinical subject-matter experts to: (i) discover the relationship between beta-blocker treatment and diabetic retinopathy; (ii) hypothesize that xylene is an environmental cancer-causing carcinogen and (iii) aid doctors with diagnosis of challenging cases when rare diseases manifest with common symptoms. In 2015, ORiGAMI was featured in the Historical Clinical Pathological Conference in Baltimore as a demonstration of artificial intelligence to medicine, IEEE/ACM Supercomputing and recognized as a Centennial Showcase Exhibit at the Radiological Society of North America (RSNA) Conference in Chicago. The final paper will describe the workflow built for the Cray Urika-XA and Urika-GD appliances that is able to reason with the knowledge of every published medical paper every time a clinical researcher uses the tool.
Dias, Mark S; Boehmer, Susan; Johnston-Walsh, Lucy; Levi, Benjamin H
Physicians and others who provide expert testimony in court cases involving alleged child abuse may be instructed to state their conclusions within a 'reasonable medical certainty' (RMC). However, neither judges nor jurors knows what degree of probability constitutes RMC for a given expert, nor whether different experts use different standards to formulate their opinions. We sought to better understand how experts define RMC in the context of court cases. An email survey was sent to members of six list-serves, representing four specialties, whose members testify in child abuse cases. Respondents were asked to define how RMC corresponded to (1) the numerical probability that abuse occurred, (2) the ordinal probability, and (3) how their determinations relate to common legal standards ('preponderance of the evidence', 'clear and convincing', and 'beyond a reasonable doubt'). Participants were also asked how comfortable they were in defining RMC; whether their definition changed according to the charges or type of proceeding; and how they would apply RMC to several hypothetical cases. The 294 list-serve participants who responded included child abuse pediatricians (46%), forensic pathologists (21%), pediatric neurosurgeons (15%), pediatric ophthalmologists (12%), and others (6%). Though 95% of respondents had testified in court, only 45% had received training in the definition of RMC. Only 37% were comfortable defining RMC. Although many responses were highly clustered and paired comparisons showed that 95% of participants' responses were internally consistent, there was variability in respondents' definitions of RMC. There is some variability in how child abuse expert witnesses define and use the term RMC; we provide suggestions about how to more accurately and transparently define RMC to ensure justice in these cases. PMID:26589362
Dounas-Frazer, Dimitri R.; Van De Bogart, Kevin L.; Stetzer, MacKenzie R.; Lewandowski, H. J.
We explore the overlap of two nationally recognized learning outcomes for physics lab courses, namely, the ability to model experimental systems and the ability to troubleshoot a malfunctioning apparatus. Modeling and troubleshooting are both nonlinear, recursive processes that involve using models to inform revisions to an apparatus. To probe the overlap of modeling and troubleshooting, we collected audiovisual data from think-aloud activities in which eight pairs of students from two institutions attempted to diagnose and repair a malfunctioning electrical circuit. We characterize the cognitive tasks and model-based reasoning that students employed during this activity. In doing so, we demonstrate that troubleshooting engages students in the core scientific practice of modeling.
Time series prediction has been successfully used in several application areas, such as meteorological forecasting, market prediction, network traffic forecasting, etc., and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.
Dounas-Frazer, Dimitri R; Stetzer, MacKenzie R; Lewandowski, H J
We explore the overlap of two nationally-recognized learning outcomes for physics lab courses, namely, the ability to model experimental systems and the ability to troubleshoot a malfunctioning apparatus. Modeling and troubleshooting are both nonlinear, recursive processes that involve using models to inform revisions to an apparatus. To probe the overlap of modeling and troubleshooting, we collected audiovisual data from think-aloud activities in which eight pairs of students from two institutions attempted to diagnose and repair a malfunctioning electrical circuit. We characterize the cognitive tasks and model-based reasoning that students employed during this activity. In doing so, we demonstrate that troubleshooting engages students in the core scientific practice of modeling.
Arruda, Wosley C; Souza, Daniel S; Ralha, Célia G; Walter, Maria Emilia M T; Raiol, Tainá; Brigido, Marcelo M; Stadler, Peter F
Noncoding RNAs (ncRNAs) have been focus of intense research over the last few years. Since characteristics and signals of ncRNAs are not entirely known, researchers use different computational tools together with their biological knowledge to predict putative ncRNAs. In this context, this work presents ncRNA-Agents, a multi-agent system to annotate ncRNAs based on the output of different tools, using inference rules to simulate biologists' reasoning. Experiments with data from the fungus Saccharomyces cerevisiae allowed to measure the performance of ncRNA-Agents, with better sensibility, when compared to Infernal, a widely used tool for annotating ncRNA. Besides, data of the Schizosaccharomyces pombe and Paracoccidioides brasiliensis fungi identified novel putative ncRNAs, which demonstrated the usefulness of our approach. NcRNA-Agents can be be found at: http://www.biomol.unb.br/ncrna-agents. PMID:26223200
Time series prediction has been successfully used in several application areas, such as meteoro-logical forecasting, market prediction, network traffic forecasting, etc. , and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.
We believe that many of the on-the-day surgery cancellations of elective surgery were potentially avoidable. We observed that cancellations due to lack of theatre time were not only a scheduling problem but were mainly caused by surgeons underestimating the timeneeded for the operation. The requirement of the instruments necessary for scheduled surgical listshould be discussed a day prior to planned OR list and arranged. The non-availability of the surgeon should be informed in time so that another case is substituted in that slot. All patients who have met PACU discharge criteria must be discharged promptly to prevent delay in shifting out of the operated patient. Day care patients should be counseled adequately to report on time. Computerized scheduling should be utilized to create a realistic elective schedule. Audit should be carried out at regular intervals to find out the effective functioning of the operation theatre.
Full Text Available Inferences about target variables can be achieved by deliberate integration of probabilistic cues or by retrieving similar cue-patterns (exemplars from memory. In tasks with cue information presented in on-screen displays, rule-based strategies tend to dominate unless the abstraction of cue-target relations is unfeasible. This dominance has also been demonstrated --- surprisingly --- in experiments that demanded the retrieval of cue values from memory (M. Persson and J. Rieskamp, 2009. In three modified replications involving a fictitious disease, binary cue values were represented either by alternative symptoms (e.g., fever vs. hypothermia or by symptom presence vs. absence (e.g., fever vs. no fever. The former representation might hinder cue abstraction. The cues were predictive of the severity of the disease, and participants had to infer in each trial who of two patients was sicker. Both experiments replicated the rule-dominance with present-absent cues but yielded higher percentages of exemplar-based strategies with alternative cues. The experiments demonstrate that a change in cue representation may induce a dramatic shift from rule-based to exemplar-based reasoning in formally identical tasks.
Through the years, the simple word 'nuclear' has become the focal point for a seemingly endless controversy, filled with passions and ideologies that sprang originally from a rational fear of nuclear war - but grew into an emotional, and now somewhat institutionalised, standoff that plagues public discourse as to how the world's nations can best meet their energy needs in the 21st century. Along the way, the very idea of nuclear energy became a political and psychological surrogate. Scepticism about government, distrust of large corporations, worry over toxic industrial effluents, a subconscious fear of cataclysm - all these real feelings and fears are crystallized, for many people, in a vague concept called 'the nuclear industry'. The subject of this presentation is that this is an idea whose time has come: that nuclear energy, a half century after its inception, has reached a moment of truth, in no less than six important respects: first, the technology has come of age; second, on a national level, key issues affecting nuclear energy will soon demand decision; third, fossil supplies may simply be inadequate to meet world energy needs; fourth, the valuable uses of nuclear power will soon multiply; fifth, and of profound importance, a massive shift toward nuclear power is now environmentally indispensable; sixth, this moment of truth for nuclear power requires a telling of the truth. Given the urgent need for public awareness and political decision, those able to do so must now make the case for nuclear energy - forcefully, without apology or equivocation, and with persuasive effect. A great deal depends on developing the wisdom and will to exploit nuclear technology to full benefit
Song, Jinzhong; Yan, Hong; Liu, Guizhi; Kuang, Hong
Electrocardiogram (ECG) is a convenient, economic, and non-invasive detecting tool in myocardial ischemia (MI). Its clinical appearance is mainly exhibited by ST-T complex change. MI events are usually instantaneous and asymptomatic in some cases, which cannot be forecasted to have a precautionary measure in time by doctors. The automatic detection of MI by computer and a cued warning of danger in real time play an important role in diagnosing heart disease. With the help of the medical staff, some quantitative approbatory indicators, such as ST-segment deviation, the amplitude of T-wave peak and the rate of ST and heart rate (HR), were combined to judge MI using fuzzy reasoning. After MIT-BIH database and the long-term ST database (LTST) verification, sensitivity and positive predictive values reached 75% and 78% respectively, and specificity and negative predictive values were 85% and 87% respectively. In addition, the proposed method was close to human way of thinking and understanding, and easy to apply in clinical detection and engineering fields. PMID:22404027
This paper proposes NNF-a fuzzy Petri Net system based on neural network for proposition logic repesentation,and gives the formal definition of NNF.For the NNF model,forward reasoning algorithm,backward reasoning algorithm and knowledge learning algorithm are discussed based on weight training algorithm of neural network-Back Propagation algorithm.Thus NNF is endowed with the ability of learning a rule.The paper concludes with a discussion on extending NNF to predicate logic,forming NNPrF,and proposing the formal definition and a reasoning algorithm of NNPrF.
Nascimento, Marcelle M; Gordan, Valeria V; Qvist, Vibeke;
The authors conducted a study to identify and quantify the reasons used by dentists in The Dental Practice-Based Research Network (DPBRN) for placing restorations on unrestored permanent tooth surfaces and the dental materials they used in doing so.......The authors conducted a study to identify and quantify the reasons used by dentists in The Dental Practice-Based Research Network (DPBRN) for placing restorations on unrestored permanent tooth surfaces and the dental materials they used in doing so....
David Armstrong; Alex Dregan
Typologies of sleep problems have usually relied on identifying underlying causes or symptom clusters. In this study the value of using the patient's own reasons for sleep disturbance are explored. Using secondary data analysis of a nationally representative psychiatric survey the patterning of the various reasons respondents provided for self-reported sleep problems were examined. Over two thirds (69.3%) of respondents could identify a specific reason for their sleep problem with worry (37.9...
Doane, Ashley N; Kelley, Michelle L; Pearson, Matthew R
Few studies have evaluated the effectiveness of cyberbullying prevention/intervention programs. The goals of the present study were to develop a Theory of Reasoned Action (TRA)-based video program to increase cyberbullying knowledge (1) and empathy toward cyberbullying victims (2), reduce favorable attitudes toward cyberbullying (3), decrease positive injunctive (4) and descriptive norms about cyberbullying (5), and reduce cyberbullying intentions (6) and cyberbullying behavior (7). One hundred sixty-seven college students were randomly assigned to an online video cyberbullying prevention program or an assessment-only control group. Immediately following the program, attitudes and injunctive norms for all four types of cyberbullying behavior (i.e., unwanted contact, malice, deception, and public humiliation), descriptive norms for malice and public humiliation, empathy toward victims of malice and deception, and cyberbullying knowledge significantly improved in the experimental group. At one-month follow-up, malice and public humiliation behavior, favorable attitudes toward unwanted contact, deception, and public humiliation, and injunctive norms for public humiliation were significantly lower in the experimental than the control group. Cyberbullying knowledge was significantly higher in the experimental than the control group. These findings demonstrate a brief cyberbullying video is capable of improving, at one-month follow-up, cyberbullying knowledge, cyberbullying perpetration behavior, and TRA constructs known to predict cyberbullying perpetration. Considering the low cost and ease with which a video-based prevention/intervention program can be delivered, this type of approach should be considered to reduce cyberbullying. PMID:26349445
Murphy, Judy Irene
This research explored the effects of instructing first-semester nursing students in the use of focused reflection and articulation to promote clinical reasoning. Student volunteers were randomly assigned to four clinical groups. Two groups that received instruction in the use of focused reflection and articulation scored significantly higher on the practice measure of clinical reasoning, accounting for 29 percent of the variance between groups. Once clinical reasoning scores were tabulated, the top six and bottom six scorers on clinical reasoning were interviewed to identify qualitative differences between students with different reasoning levels. Themes from the interviews revealed that those with high clinical reasoning reported a high frequency of use of focused reflection and articulation, engaged in abstract learning, and were more self-regulated in their learning than those who scored low on clinical reasoning. This study provides empirical evidence that using instructional methods that focus learners' attention on the concrete application of theory in the practicum setting helps enhance their reasoning skills. PMID:15508561
Armstrong, David; Dregan, Alex
Typologies of sleep problems have usually relied on identifying underlying causes or symptom clusters. In this study the value of using the patient's own reasons for sleep disturbance are explored. Using secondary data analysis of a nationally representative psychiatric survey the patterning of the various reasons respondents provided for self-reported sleep problems were examined. Over two thirds (69.3%) of respondents could identify a specific reason for their sleep problem with worry (37.9%) and illness (20.1%) representing the most commonly reported reasons. And while women reported more sleep problems for almost every reason compared with men, the patterning of reasons by age showed marked variability. Sleep problem symptoms such as difficulty getting to sleep or waking early also showed variability by different reasons as did the association with major correlates such as worry, depression, anxiety and poor health. While prevalence surveys of 'insomnia' or 'poor sleep' often assume the identification of an underlying homogeneous construct there may be grounds for recognising the existence of different sleep problem types particularly in the context of the patient's perceived reason for the problem. PMID:24983754
Full Text Available Typologies of sleep problems have usually relied on identifying underlying causes or symptom clusters. In this study the value of using the patient's own reasons for sleep disturbance are explored. Using secondary data analysis of a nationally representative psychiatric survey the patterning of the various reasons respondents provided for self-reported sleep problems were examined. Over two thirds (69.3% of respondents could identify a specific reason for their sleep problem with worry (37.9% and illness (20.1% representing the most commonly reported reasons. And while women reported more sleep problems for almost every reason compared with men, the patterning of reasons by age showed marked variability. Sleep problem symptoms such as difficulty getting to sleep or waking early also showed variability by different reasons as did the association with major correlates such as worry, depression, anxiety and poor health. While prevalence surveys of 'insomnia' or 'poor sleep' often assume the identification of an underlying homogeneous construct there may be grounds for recognising the existence of different sleep problem types particularly in the context of the patient's perceived reason for the problem.
Eisenhawer, S.W.; Bott, T.F.; Smith, R.E.
High-level waste (HLW) produces flammable gases as a result of radiolysis and thermal decomposition of organics. Under certain conditions, these gases can accumulate within the waste for extended periods and then be released quickly into the dome space of the storage tank. As part of the effort to reduce the safety concerns associated with flammable gas in HLW tanks at Hanford, a flammable gas watch list (FGWL) has been established. Inclusion on the FGWL is based on criteria intended to measure the risk associated with the presence of flammable gas. It is important that all high-risk tanks be identified with high confidence so that they may be controlled. Conversely, to minimize operational complexity, the number of tanks on the watchlist should be reduced as near to the true number of flammable risk tanks as the current state of knowledge will support. This report presents an alternative to existing approaches for FGWL screening based on the theory of approximate reasoning (AR) (Zadeh 1976). The AR-based model emulates the inference process used by an expert when asked to make an evaluation. The FGWL model described here was exercised by performing two evaluations. (1) A complete tank evaluation where the entire algorithm is used. This was done for two tanks, U-106 and AW-104. U-106 is a single shell tank with large sludge and saltcake layers. AW-104 is a double shell tank with over one million gallons of supernate. Both of these tanks had failed the screening performed by Hodgson et al. (2) Partial evaluations using a submodule for the predictor likelihood for all of the tanks on the FGWL that had been flagged previously by Whitney (1995).
High-level waste (HLW) produces flammable gases as a result of radiolysis and thermal decomposition of organics. Under certain conditions, these gases can accumulate within the waste for extended periods and then be released quickly into the dome space of the storage tank. As part of the effort to reduce the safety concerns associated with flammable gas in HLW tanks at Hanford, a flammable gas watch list (FGWL) has been established. Inclusion on the FGWL is based on criteria intended to measure the risk associated with the presence of flammable gas. It is important that all high-risk tanks be identified with high confidence so that they may be controlled. Conversely, to minimize operational complexity, the number of tanks on the watchlist should be reduced as near to the true number of flammable risk tanks as the current state of knowledge will support. This report presents an alternative to existing approaches for FGWL screening based on the theory of approximate reasoning (AR) (Zadeh 1976). The AR-based model emulates the inference process used by an expert when asked to make an evaluation. The FGWL model described here was exercised by performing two evaluations. (1) A complete tank evaluation where the entire algorithm is used. This was done for two tanks, U-106 and AW-104. U-106 is a single shell tank with large sludge and saltcake layers. AW-104 is a double shell tank with over one million gallons of supernate. Both of these tanks had failed the screening performed by Hodgson et al. (2) Partial evaluations using a submodule for the predictor likelihood for all of the tanks on the FGWL that had been flagged previously by Whitney (1995)
McHale, P; Keenan, A; Ghebrehewet, S
Uptake rates for the combined measles, mumps and rubella (MMR) vaccine have been below the required 95% in the UK since a retracted and discredited article linking the MMR vaccine with autism and inflammatory bowel disease was released in 1998. This study undertook semi-structured telephone interviews among parents or carers of 47 unvaccinated measles cases who were aged between 13 months and 9 years, during a large measles outbreak in Merseyside. Results showed that concerns over the specific links with autism remain an important cause of refusal to vaccinate, with over half of respondents stating this as a reason. A quarter stated child illness during scheduled vaccination time, while other reasons included general safety concerns and access issues. Over half of respondents felt that more information or a discussion with a health professional would help the decision-making process, while a third stated improved access. There was clear support for vaccination among respondents when asked about current opinions regarding MMR vaccine. The findings support the hypothesis that safety concerns remain a major barrier to MMR vaccination, and also support previous evidence that experience of measles is an important determinant in the decision to vaccinate. PMID:26265115
Full Text Available 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 modeling and predicting either univariate or multivariate time series. Visual-FIR offers an easy-friendly environment to perform this task. In this research, long term prediction of maximum ozone concentration in the downtown of Mexico City Metropolitan Area is performed. The data were registered every hour and include missing values. Two modeling perspectives are analyzed, i.e. monthly and seasonal models. The results show that the developed models are able to predict the diurnal variation of ozone, including its maximum daily value in an accurate manner.
Juan Miguel Rosa González
Full Text Available This article focuses on the process of new business creation, considering the effectuation approach, which explains the phenomenon of entrepreneurship in a different perspective than the traditional causal approach. Beginning with a description of the effectual approach assumptions, a case study about the subject is presented in order to explore the logic of the business creation process. The case discusses a Brazilian organization created in 1980 to produce materials and services in steel industry. Through structured interview with the entrepreneur who idealized the business, the main events in the early stages of the project are described. The results show the relationship between entrepreneur’s means available at the time of the enterprise creation and the new business design. In addition, the entrepreneur preferred a strategy of drawing instead of a decision one, and gave priority to strategic partnerships as a substitute of formal market research. All these aspects are covered by the effectual approach.
Moore, J Christopher
We have found that non-STEM majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower pre-instruction on the Lawson's Classroom Test of Scientific Reasoning (LCTSR) in comparison to national average STEM majors. 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. Pre-scores 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...
U.S. Environmental Protection Agency — The Reasonable Accommodation Information Tracking System (RAITS) is a case management system that allows the National Reasonable Accommodation Coordinator (NRAC)...
Pereira-Fariña, Martín; Díaz-Hermida, Félix; Bugarín Diz, Alberto José
Syllogism is a type of deductive reasoning involving quantified statements. The syllogistic reasoning scheme in the classical Aristotelian framework involves three crisp term sets and four linguistic quantifiers, for which the main support is the linguistic properties of the quantifiers. A number of fuzzy approaches for defining an approximate syllogism have been proposed for which the main support is cardinality calculus. In this paper we analyze fuzzy syllogistic models previously described...
Wang Shitong; Korris F. L. Chung
Syllogistic fuzzy reasoning is introduced into fizzy system, and the new Cascaded Fuzzy System(CFS) is presented. The thoroughly theoretical analysis and experimental results show that syllogistic fuzzy reasoning is more robust than all other implication inferences for noise data and that CFS has better robustness than conventional fuzzy systems, which provide the solid foundation for CFS's potential application in fuzzy control and modeling and so on.
This research hypothesized that a practical approach in the form of a solution framework known as Natural Language Understanding and Reasoning for Intelligence (NaLURI), which combines full-discourse natural language understanding, powerful representation formalism capable of exploiting ontological information and reasoning approach with advanced features, will solve the following problems without compromising practicality factors: 1) restriction on the nature of question and response, and 2) limitation to scale across domains and to real-life natural language text.
Mitchell, Christine M.; Thurman, David A.
This paper describes a project that extends the concept of help desk automation by offering World Wide Web access to a case-based help desk. It explores the use of case-based reasoning and cognitive engineering models to create an 'intelligent' help desk system, one that learns. It discusses the AutoHelp architecture for such a help desk and summarizes the technologies used to create a help desk for NASA data users.
Full Text Available Background: To determine and analyze the reasons why keratorefractive surgery, laser in situ keratomileusis (LASIK and photorefractive keratectomy (PRK were not performed in patients who presented for refractive surgery consultation. Materials and Methods: A retrospective observational study was performed between January 2006 and December 2007 in the Yemen Magrabi Hospital. The case records of 2,091 consecutive new patients who presented for refractive surgery were reviewed. Information from the pre-operative ophthalmic examination, such as refractive error, corneal topography and visual acuity, were analyzed. The reasons for not performing LASIK and PRK in the cases that were rejected were recorded and analyzed. Results: In this cohort, 1,660 (79.4% patients were advised to have LASIK or PRK from the 2,091 patients examined. LASIK and PRK were not advised in 431 (21% patients. The most common reasons for not performing the surgery were high myopia >-11.00 Diopters (19%, keratoconus (18%, suboptimal central corneal thickness (15%, cataract (12% and keratoconus suspect (forme fruste keratoconus (10%. Conclusion: Patients who requested keratorefractive surgery have a variety of problems and warrant comprehensive attention to selection criteria on the part of the surgeon. Corneal topographies and pachymetry of refractive surgery candidates need to be read cautiously. High-refractive error, keratoconus and insufficient corneal thickness were found to be the leading reasons for not performing keratorefractive surgery in this study.
The expert systems development within a real time context, requires both to master the necessary reasoning about the time as well as to master the necessary response time for reasoning. Although rigorous temporal logic formalisms exist, strategies for temporal reasoning are either incomplete or else imply unacceptable response times. The first part presents the logic formalism upon which is based the production system. This formalism contains a three-valued logic system with truth-valued matrix, and a deductive system with a formal system. It does a rigorous work for this no standard logic, where the notions of consistency and completeness can be studied. Its development supports itself on the will to formalise the reasoning used at the elaboration time of the strategies to make them more explicit as the natural deduction method. The second part proposes an extension for the source logic formalism to take explicitly the time into account. The approach proposed through 'TANIS', the prototype of such an expert system shell, using a natural reasoning application is proposed. It allows, at the generation time, the implementation within the expert system, of an adapted deduction strategy to the symbolic temporal reasoning which is complete and ease the determination of the response time. (author)
de Weerd, Hermanes; Verbrugge, Rineke; Verheij, Bart; Herzig, Andreas; Lorini, Emiliano
When people engage in social interactions, they often rely on their theory of mind, their ability to reason about unobservable mental content of others such as beliefs, goals, and intentions. This ability allows them to both understand why others behave the way they do as well as predict future beha
Michael S Vendetti
Full Text Available Relational reasoning, or the ability to integrate multiple mental relations to arrive at a logical conclusion, is a critical component of higher cognition. A bilateral brain network involving lateral prefrontal and parietal cortices has been consistently implicated in relational reasoning. Some data suggest a preferential role for the left hemisphere in this form of reasoning, whereas others suggest that the two hemispheres make important contributions. To test for a hemispheric asymmetry in relational reasoning, we made use of an old technique known as visual half-field stimulus presentation to manipulate whether stimuli were presented briefly to one hemisphere or the other. Across two experiments, 54 neurologically healthy young adults performed a visuospatial transitive inference task. Pairs of colored shapes were presented rapidly in either the left or right visual hemifield as participants maintained central fixation, thereby isolating initial encoding to the contralateral hemisphere. We observed a left-hemisphere advantage for encoding a series of ordered visuospatial relations, but both hemispheres contributed equally to task performance when the relations were presented out of order. To our knowledge, this is the first study to reveal hemispheric differences in relational encoding in the intact brain. We discuss these findings in the context of a rich literature on hemispheric asymmetries in cognition.
Hartley, Laurel M.; Wilke, Brook J.; Schramm, Jonathon W.; D'Avanzo, Charlene; Anderson, Charles W.
Processes that transform carbon (e.g., photosynthesis) play a prominent role in college biology courses. Our goals were to learn about student reasoning related to these processes and provide faculty with tools for instruction and assessment. We created a framework illustrating how carbon-transforming processes can be related to one another during…
Belko Abdoul Aziz Diallo; Thierry Badard; Frédéric Hubert; Sylvie Daniel
Mobile professionals need to be assisted with suitable mobile GeoBI (Geospatial Business Intelligence) systems, which are able to capture, organize and structure the user’s reality into a relevant context model and reason on it. GeoBI context modelling and reasoning are still research issues since there is not yet either a model or a relevant taxonomy regarding GeoBI contextual information. To fill this gap, this paper proposes an extended and detailed OWL-based mobile GeoBI...
Chaipichit, Dudduan; Jantharajit, Nirat; Chookhampaeng, Sumalee
The objectives of this research were to study issues around the management of science learning, problems that are encountered, and to develop a learning management model to address those problems. The development of that model and the findings of its study were based on Constructivist Theory and literature on reasoning strategies for enhancing…
Jaeger, Martin; Adair, Desmond
The purpose of this study is to analyse the feasibility of an evidential reasoning (ER) method for portfolio assessments and comparison of the results found with those based on a traditional holistic judgement. An ER approach has been incorporated into portfolio assessment of an undergraduate engineering design course delivered as a project-based…
Wolf, Sebastian; Weißenberger, Barbara E.; Kabst, Rüdiger; Wehner, Sebastian
Business practice and literature frequently advocate more business oriented roles for management accountants. The aim of this study is to examine reasons for management accountants to act as business partners and to analyze corresponding performance effects. More specifically, two research questions are investigated: (i) why do management accountants act as business partners, and (ii) are business oriented management accountants beneficial to organizations? To answer these research questio...
Schalk, Kelly A.
The purpose of this investigation was to measure specific ways a student interest SSI-based curricular and pedagogical affects undergraduates' ability informally reason. The delimited components of informal reasoning measured were undergraduates' Nature of Science conceptualizations and ability to evaluate scientific information. The socio-scientific issues (SSI) theoretical framework used in this case-study has been advocated as a means for improving students' functional scientific literacy. This investigation focused on the laboratory component of an undergraduate microbiology course in spring 2008. There were 26 participants. The instruments used in this study included: (1) Individual and Group research projects, (2) journals, (3) laboratory write-ups, (4) a laboratory quiz, (5) anonymous evaluations, and (6) a pre/post article exercise. All instruments yielded qualitative data, which were coded using the qualitative software NVivo7. Data analyses were subjected to instrumental triangulation, inter-rater reliability, and member-checking. It was determined that undergraduates' epistemological knowledge of scientific discovery, processes, and justification matured in response to the intervention. Specifically, students realized: (1) differences between facts, theories, and opinions; (2) testable questions are not definitively proven; (3) there is no stepwise scientific process; and (4) lack of data weakens a claim. It was determined that this knowledge influenced participants' beliefs and ability to informally reason. For instance, students exhibited more critical evaluations of scientific information. It was also found that undergraduates' prior opinions had changed over the semester. Further, the student interest aspect of this framework engaged learners by offering participants several opportunities to influentially examine microbiology issues that affected their life. The investigation provided empirically based insights into the ways undergraduates' interest
The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at the Hanford site have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop and improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. Approximate-reasoning models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. In a pilot study to investigate the utility of AR for flammable gas screening, the effort to implement such a model was found to be acceptable, and computational requirements were found to be reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previous screening efforts
The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at the Hanford site have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop an improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. Approximate-reasoning models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. In a pilot study to investigate the utility of AR for flammable gas screening, the effort to implement such a model was found to be acceptable, and computational requirements were found to be reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previous screening efforts
Afzal Ballim; Tomas By; Yorick Wilks; Christian Lieske
Common approaches to using artificial intelligence techniques in legal reasoning have generally been based on the logical reasoning methods developed in AI. In most cases, such systems can be considered to be expert systems applied in the legal domain. Other aspects of AI technology that rely more heavily on human psychology or behavioural patterns have rarely been used. This paper aims to show that some of these techniques have a rightful place in legal reasoning, and in particular that the ...
Quillin, Kim; Thomas, Stephen
The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094
Wang, Chengbo; Johansen, John; Luxhøj, James T.
This paper focuses on one critical element, indexing – retaining and representing knowledge in an applied case-based reasoning (CBR) model for supporting strategic manufacturing vision development (CBRM). Manufacturing vision (MV) is a kind of knowledge management concept and process concerned wi...... summarize the methods, primary conclusions of test runs with the indexing scheme. Further research work to refine the index vocabulary is discussed as well....
Spyridon Klinis, Adelais Markaki, Dimitrios Kounalakis, Emmanouil K. Symvoulakis
Full Text Available The objective of this brief communication was to tabulate common reasons for encounter in a Greek rural general practice, as result of a recently adopted electronic patient record (EPR application. Twenty encounter reasons accounted for 3,797 visits (61% of all patient encounters, whereas 565 other reasons accounted for the remaining 2,429 visits (39%. Number one reason for encounter was health maintenance or disease prevention seeking services, including screening examinations for malignancies, immunization and provision of medical opinion reports. Hypertension, lipid disorder and ischemic heart disease without angina were among the most common reasons for seeking care. A strengths/weaknesses/opportunities/threats (SWOT analysis on the key role of an EPR system in collecting data from rural and remote primary health care settings is also presented.
Klinis, Spyridon; Markaki, Adelais; Kounalakis, Dimitrios; Symvoulakis, Emmanouil K
The objective of this brief communication was to tabulate common reasons for encounter in a Greek rural general practice, as result of a recently adopted electronic patient record (EPR) application. Twenty encounter reasons accounted for 3,797 visits (61% of all patient encounters), whereas 565 other reasons accounted for the remaining 2,429 visits (39%). Number one reason for encounter was health maintenance or disease prevention seeking services, including screening examinations for malignancies, immunization and provision of medical opinion reports. Hypertension, lipid disorder and ischemic heart disease without angina were among the most common reasons for seeking care. A strengths/weaknesses/opportunities/threats (SWOT) analysis on the key role of an EPR system in collecting data from rural and remote primary health care settings is also presented. PMID:23091407
Dole, Shelley; Hilton, Annette; Hilton, Geoff;
Proportional reasoning is widely acknowledged as a key to success in school mathematics, yet students’ continual difficulties with proportion-related tasks are well documented. This paper draws on a large research study that aimed to support 4th to 9th grade teachers to design and implement tasks...... to foster students’ proportional reasoning. Classroom data revealed limited initial teacher knowledge and awareness of the pervasive nature of proportional reasoning required in the mathematics curriculum. Teacher capacity to seize teachable moments for building students’ proportional reasoning...... skills increased throughout the project. From this background, this paper presents an analysis of the proportional reasoning demands and opportunities of topics within the school mathematics curriculum in Australia. Implications for the study of whole number arithmetic (WNA) and other topics to promote...
Wang Shiwei; Tan Jianrong; Zhang Shuyou; Wang Xin; He Chenqi
The increasing complexity and size of configuration knowledge bases requires the provision of advanced methods supporting the development of the actual configuration process and design reuse.A new framework to find a feasible and practical product configuration method is presented in mass customization.The basic idea of the approach is to integrate case-based reasoning (CBR) with a constraint satisfaction problem(CSP).The similarity measure between a crisp and range is also given,which is common in case retrieves.Based on the configuration model,a product platform and customer needs,case adaptation is carried out with the repair-based algorithm.Lastly,the methodology in the elevator configuration design domain is tested.
Marcela HERNÁNDEZ GONZÁLEZ
Full Text Available This study focused on the analysis of professional ethics of teachers. It is considered important because this teaching is itself an ethical activity because it touches on the whole person of the learner to encourage it to be gradually a better subject.Moral reasoning and moral attitudes: to have a professional approach to this ethic two related elements were studied. A case study located in Mexico, in the Superior Normal School of Michoacán (ensm, initial training institution was performed, but also welcomes teachers in service for further studies and graduate. Methods of quantitative and qualitative research in the same investigation were integrated approach known as hybrid or mixed method. The instruments were built Likert scale, hypothetical and real moral dilemmas. And the implementation of group discussion with experts.The work investigated on major ethical problems of secondary teachers, argumentation processes performed to make ethical decisions and principal values present.The results found that ethical aspects have an important place in their educational conception. Also there is a high emotional charge in moral attitudes, which are transformed along the experience and professional cycling stage that is going through.Moreover, the presence of the principles of justice and charity in ethical conflicts was recognized, and the importance of the ability of moral sensibility as an element that favors the appropriate educational practices and ethical development of students and educators.The study provides knowledge of reflection to be implemented in teacher training, seeking to promote professional ethics in secondary teachers respond to the needs and demands of the current context.
The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at Hanford have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop an improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. AR models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. The authors performed a pilot study to investigate the utility of AR for flammable gas screening. They found that the effort to implement such a model was acceptable and that computational requirements were reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previous screening efforts
Chu, K.-K.; Lee, C.-I. [National Univ. of Tainan, Taiwan (China). Dept. of Computer Science and Information Learning Technology
Concept maps are graphical representations of knowledge. Concept mapping may reduce students' cognitive load and extend simple memory function. The purpose of this study was on the diagnosis of students' concept map learning abilities and the provision of personally constructive advice dependant on their learning path and progress. Ontology is a useful method with which to represent and store concept map information. Semantic web rule language (SWRL) rules are easy to understand and to use as specific reasoning services. This paper discussed the selection of grade 7 lakes and rivers curriculum for which to devise a concept map learning path reasoning service. The paper defined a concept map e-learning ontology and two SWRL semantic rules, and collected users' concept map learning path data to infer implicit knowledge and to recommend the next learning path for users. It was concluded that the designs devised in this study were feasible and advanced and the ontology kept the domain knowledge preserved. SWRL rules identified an abstraction model for inferred properties. Since they were separate systems, they did not interfere with each other, while ontology or SWRL rules were maintained, ensuring persistent system extensibility and robustness. 15 refs., 1 tab., 8 figs.
Kristensen, Hanne Kaae; Borg, T.; Hounsgaard, L.
and knowledge use in order to develop their practice knowledge and new skills. Moreover personal values and clinical experiences inﬂuenced clinical reasoning. Current knowledge of the importance of local cultures and leadership was reinforced. Conclusion: The inﬂuence of professional values in the occupational...... therapists’ local cultures was a substantial factor in the implementation processes. In addition personal values and clinical experiences inﬂuenced professional decision-making. Furthermore, the study reinforced current knowledge of the importance of culture and leadership in implementation of research......, and six focus-group interviews. Results: New knowledge concerning the substantial inﬂuence of professional values in the occupational therapists’ local cultures was indicated. It was of importance that the therapists as a group are given the opportunity to explicit and critically appraise values...
Hounsgaard, Lise; Kristensen, H. K.; Borg, T.
and knowledge use in order to develop their practice knowledge and new skills. Moreover personal values and clinical experiences influenced clinical reasoning. Current knowledge of the importance of local cultures and leadership was reinforced. CONCLUSION: The influence of professional values...... in the occupational therapists' local cultures was a substantial factor in the implementation processes. In addition personal values and clinical experiences influenced professional decision-making. Furthermore, the study reinforced current knowledge of the importance of culture and leadership in implementation......, and six focus-group interviews. RESULTS: New knowledge concerning the substantial influence of professional values in the occupational therapists' local cultures was indicated. It was of importance that the therapists as a group are given the opportunity to explicit and critically appraise values...
Zhou, Huan; Wang, Jian-qiang; Zhang, Hong-yu; Chen, Xiao-hong
Linguistic hesitant fuzzy sets (LHFSs), which can be used to represent decision-makers' qualitative preferences as well as reflect their hesitancy and inconsistency, have attracted a great deal of attention due to their flexibility and efficiency. This paper focuses on a multi-criteria decision-making approach that combines LHFSs with the evidential reasoning (ER) method. After reviewing existing studies of LHFSs, a new order relationship and Hamming distance between LHFSs are introduced and some linguistic scale functions are applied. Then, the ER algorithm is used to aggregate the distributed assessment of each alternative. Subsequently, the set of aggregated alternatives on criteria are further aggregated to get the overall value of each alternative. Furthermore, a nonlinear programming model is developed and genetic algorithms are used to obtain the optimal weights of the criteria. Finally, two illustrative examples are provided to show the feasibility and usability of the method, and comparison analysis with the existing method is made.
Highlights: • The reasonability of Chinese government’s CO2 emissions reduction allocation plan is examined. • The stochastic convergence and β-convergence are tested using the provincial panel data. • Both fixed effects and Generalized Method of Moments (GMM) estimators are utilized. • The provinces with high carbon intensity tend to experience faster reduction in carbon intensity, and vise versa. - Abstract: To curb CO2 emissions, the Chinese government has announced ambitious goals to reduce the CO2 intensity of GDP, and the total target has been allocated to all Chinese provinces during the twelfth “Five-year Plan” period (2011–2015). Although setting the target allocation plan is an efficient way to achieve this goal, some key questions, including how the plan is designed, remained unanswered. From an economic perspective, this requires us to test for the existence of convergence in the CO2 intensity of GDP because the convergence is one of the most important intrinsic economic characteristics that policy makers should take into account: if the convergence exists, the provinces with a higher CO2 intensity of GDP tend to experience a more rapid reduction in the intensity and therefore could share a heavier burden of the intensity reduction. The existence of stochastic convergence and β-convergence is verified by employing different estimation methods and using various estimation specifications. As a result, the direct policy implication is that provinces with high CO2 intensity should be assigned tougher reduction targets to cut CO2 intensity at higher speeds, while the provinces with low carbon intensity should be allowed to reduce the CO2 intensity at a relatively lower speed. Because some social and economic indicators such as GDP per capita, industrial structure and population density may influence CO2 intensity, the policy makers should take all these factors into consideration to design reasonable reduction target allocation plan
Cevik, Yasemin Demiraslan; Andre, Thomas
This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…
Eduardo Gomes Salgado; Carlos Eduardo Sanches da Silva; Carlos Henrique Pereira Mello
The search for implementation of Quality Management Systems aims to continuously improve their results. Thus, for the services and/or products offered to convey trust and credibility, they must be designed within appropriate norms and standards. In this sense, this study seeks to assess the reasons that induce incubated technology-based companies to seek adequacy of their quality management system to the NBR ISO 9001:2008 standard. Through an exploratory survey in twenty-six incubated technol...
Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi
Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowle...
Quillin, Kim; Thomas, Stephen
The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-t...
Human beings' intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers' choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.
Ground, Larry; Kott, Alexander; Budd, Ray
Use of knowledge-based planning tools can help alleviate the challenges of planning a complex operation by a coalition of diverse parties in an adversarial environment. We explore these challenges and potential contributions of knowledge-based tools using as an example the CADET system, a knowledge-based tool capable of producing automatically (or with human guidance) battle plans with realistic degree of detail and complexity. In ongoing experiments, it compared favorably with human planners...
Information Quality (IQ) has been always a growing concern for most organizations, since they depend on information for managing their daily tasks, delivering their services to their costumers, making important decisions, etc., and relying on low-quality information may negatively influence their overall performance, or even disasters in the case of critical systems (e.g., air traffic management systems, healthcare systems, etc.). Although there exist several techniques for dealing with IQ r...
Kwon, Okyun; Camp, Scott D.; Daggett, Dawn M.; Klein-Saffran, Jody
Although faith-based correctional programming has become increasingly popular in recent years, offenders' motivation to participate and the impact on prison adjustment have received little attention. Analyzing interview data of 83 participants of the Federal Bureau of Prison's faith-based correctional program, this study explored the different…
A common theme has been consistently woven through the literature on teacher professional development: that practice-based designs and collaboration are two components of effective teacher learning models. In addition to collaboration and practice-based designs, inquiry cycles have been long recognized as catalysts for teacher professional…
Eduardo Gomes Salgado
Full Text Available The search for implementation of Quality Management Systems aims to continuously improve their results. Thus, for the services and/or products offered to convey trust and credibility, they must be designed within appropriate norms and standards. In this sense, this study seeks to assess the reasons that induce incubated technology-based companies to seek adequacy of their quality management system to the NBR ISO 9001:2008 standard. Through an exploratory survey in twenty-six incubated technology-based companies, a twelve-question questionnaire proposed by Bhuiyan and Alam (2005 was applied. After analyzing the data, it is concluded that the reasons for adequacy of QMS to the NBR ISO 9001:2008 standard are: competitive advantage over competitors; consultant´s approach for implementation; improvement in product quality; and government funding for ISO 9001 certification. It is found that the consultant´s approach stands out as a strong reason for seeking the adequacy of QMS to the NBR ISO 9001 standard.
Canessa, Nicola; Pantaleo, Giuseppe; Crespi, Chiara; Gorini, Alessandra; Cappa, Stefano F
We used the "standard" and "switched" social contract versions of the Wason Selection-task to investigate the neural bases of human reasoning about social rules. Both these versions typically elicit the deontically correct answer, i.e. the proper identification of the violations of a conditional obligation. Only in the standard version of the task, however, this response corresponds to the logically correct one. We took advantage of this differential adherence to logical vs. deontical accuracy to test the different predictions of logic rule-based vs. visuospatial accounts of inferential abilities in 14 participants who solved the standard and switched versions of the Selection-task during functional-Magnetic-Resonance-Imaging. Both versions activated the well known left fronto-parietal network of deductive reasoning. The standard version additionally recruited the medial parietal and right inferior parietal cortex, previously associated with mental imagery and with the adoption of egocentric vs. allocentric spatial reference frames. These results suggest that visuospatial processes encoding one's own subjective experience in social interactions may support and shape the interpretation of deductive arguments and/or the resulting inferences, thus contributing to elicit content effects in human reasoning. PMID:24928617
Tylén, Kristian; Fusaroli, Riccardo; Stege Bjørndahl, Johanne;
Many types of everyday and specialized reasoning depend on diagrams: we use maps to find our way, we draw graphs and sketches to communicate concepts and prove geometrical theorems, and we manipulate diagrams to explore new creative solutions to problems. The active involvement and manipulation of...... representational artifacts for purposes of thinking and communicating is discussed in relation to C.S. Peirce’s notion of diagrammatical reasoning. We propose to extend Peirce’s original ideas and sketch a conceptual framework that delineates different kinds of diagram manipulation: Sometimes diagrams are...
Santosh Kumar Swain
Full Text Available We present a comprehensive test case generation technique from UML models. We use the features in UML 2.0 sequence diagram including conditions, iterations, asynchronous messages and concurrent components. In our approach, test cases are derived from analysis artifacts such as use cases, their corresponding sequence diagrams and constraints specified across all these artifacts. We construct Use case Dependency Graph (UDG from use case diagram and Concurrent Control Flow Graph (CCFG from corresponding sequence diagrams for test sequence generation. We focus testing on sequences of messages among objects of use case scenarios. Our testing strategy derives test cases using full predicate coverage criteria. Our proposed test case generation technique can be used for integration and system testing accommodating the object message and condition information associated with the use case scenarios. The test cases thus generated are suitable for detecting synchronization and dependency of use cases and messages, object interaction and operational faults. Finally, we have made an analysis and comparison of our approach with existing approaches, which are based on other coverage criterion through an example.
This study analyzed interventions used in improving the mathematics achievement in spatial reasoning tasks for females called connectedness. Gender achievement in mathematics has been a controversial topic because of the wide variance in research. Some research has found a difference between the genders in mathematics while others argue there is…
Taylor, Kelley R.
This article presents a sample legal battle that illustrates school officials' "reasonable forecasts" of substantial disruption in the school environment. In 2006, two students from a Texas high school came to school carrying purses decorated with images of the Confederate flag. The school district has a zero-tolerance policy for clothing or…
Bledsoe, Karen E.
Reform in science education has often emphasized task-based learning as an instructional method to improve student understanding and retention of concepts, and to promote the development of reasoning and problem-solving. Yet studies assessing student knowledge at the beginning and end of a task-based class show mixed results. Students in task-based science and technology courses may gain greater long-term retention of knowledge than their traditional counterparts, though immediate gains may be comparable. Curriculum developers and educators express concerns that the costs of developing and implementing task-based instruction may not justify the results. Yet the question of whether students learn more in a task-based setting than a traditional setting is difficult to answer without fully understanding how students learn in a task-based context. Toward this end, this study presents a tentative model of learning in task-based contexts. A phenomenological perspective was employed to examine conceptions held by first-year undergraduate electrical engineering students around current, voltage, and resistance in simple and complex circuits. The study also examined how the students' prior knowledge interacted with their reasoning skills as these students engaged in a project based laboratory component of an introductory electrical engineering course. Students entering the course with low prior knowledge and high prior knowledge were selected for the study. Seven volunteered as participants and completed the study. Three were assessed as having low prior knowledge of electrical concepts, and four had high prior knowledge. Subjects were interviewed near the beginning and after the end of an electrical engineering course that included a project-based laboratory. Interviews were analyzed for subject content knowledge. The subjects were observed performing in lab as they carried out various tasks using TekBots(TM) robotic kits. Dialogue between the subjects and others in the lab
Adaptation that is so natural for teaching by humans is a challenging issue for electronic learning tools. Adaptation in classic teaching is based on observations made about students during teaching. Similar idea was employed in user-adapted (personalized) eLearning applications. Knowledge about a...
In order to realize the agility of the fixture design, such asreconfigurability, rescalability and reusability, fixture structure is function unit-based decomposed from a fire-new point of view. Which makes it easy for agile fixture to be reconfigured and modified. Thereby, the base of case-based agile fixture design system info is established.Whole case-based agile fixture design model is presented. In which, three modules are added relative to the other models, including case matching of fixture planning module, conflict arbitration module and agile fixture case modify module. The three modules could solve the previous problem that the experience and result are difficult to be reused in the process of design.Two key techniques in the process of the agile fixture design, the evaluation of case similarity, and restriction-based conflict arbitration, are listed. And some methods are presented to evaluate the similarity and clear up the conflict.
Ng, L. S.
This dissertation looks at the linked issues of justification and public reason – under what conditions do political authorities count as legitimate, and what is the appropriate mode of reasoning together in the public sphere? The main contender in the field currently is Rawls’s political liberalism. His conception of justification gives a key role to the justifiability of political power to each citizen, based on shared (because mutually acceptable) reasons. This approach to justification af...
Fuzzy set systems can be used to solve the problem with uncertain knowledge,and default logic can be used to solve the problem with incomplete knowledge,in some sense.In this paper,based on interval-valued fuzzy sets we introduce a method of inference which combines approximate reasoning an default ogic,and give the procedure of transforming monotonic reasoning into default reasoning.
Full Text Available At present ecology and energy efficiency issue is one of the main problems. Heat flow generation systems take one of the first positions in the list of the greatest energy consumption systems. This is heating and cooling of the rooms, freezing chambers etc. Climatic system of the refrigerating industrial complex is considered in article. Competitiveness of heating and cooling systems based on vortex tubes compared with chillers was shown.
Kamsu-Foguem, Bernard; Diallo, Gayo; Foguem, Clovis
Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of med...
Zhao, Yongwang; Sann, David; Zhang, Fuyuan; Liu, Yang
Assurance of information flow security by formal methods is mandated in security certification of separation kernels. As an industrial standard for separation kernels, ARINC 653 has been complied with by mainstream separation kernels. Security of functionalities defined in ARINC 653 is thus very important for the development and certification of separation kernels. This paper presents the first effort to formally specify and verify separation kernels with ARINC 653 channel-based communication...
Wang, Chengbo; Johansen, John; Luxhøj, James T.;
practices and activity patterns are based on learning and applying the knowledge internal and external to an organisation. To ensure their smooth formulation process, there are two important techniques designed – an expert adaptation approach and an expert evaluation approach. These two approaches provide...... structured processes to execute the organisational learning and knowledge application, which intend to guide the practitioners during the process of manufacturing competence development and improvement. They are based on Case-Based Reasoning (CBR) methodology and rely on cases as the primary knowledge supply....... This paper aims to present the two approaches; introduce two types of tests on these approaches to verify their functionality: role-play testing and real world application testing; and summarises the applicability of the two approaches....
A. S. L. Lindawati; M. J. R. Gaffikin
The objective of this study is to explore the user’s perceptions of the role of moral reasoning in influencing the implementation of codes of ethics as standards and guidance for professional audit practice by Indonesian public accountants. The study focuses on two important aspects of influence: (i) the key factors influencing professional public accountants in implementing a code of ethics as a standard for audit practice, and (ii) the key activities performed by public accountants as moral...
Murcia Agudelo, Nubia Esther; Ramírez Angulo, Pedro Julián
The Colombian government has focused on the education of its citizens. In line with this initiative, this paper aims at making a contribution from educational relationship marketing, to strengthen virtual methodology in the post- graduate level. A qualitative study with in- depth interviews until saturation level is used to ascertain the reasons that affect attrition and retention in the academic program. The factors with greater impact found were first, those programs related to academic ser...
Sights, B.; Ahuja, G.; Kogut, G.; Pacis, E. B.; Everett, H. R.; Fellars, D.; Hardjadinata, S.
The fusion of multiple behavior commands and sensor data into intelligent and cohesive robotic movement has been the focus of robot research for many years. Sequencing low level behaviors to create high level intelligence has also been researched extensively. Cohesive robotic movement is also dependent on other factors, such as environment, user intent, and perception of the environment. In this paper, a method for managing the complexity derived from the increase in sensors and perceptions is described. Our system uses fuzzy logic and a state machine to fuse multiple behaviors into an optimal response based on the robot's current task. The resulting fused behavior is filtered through fuzzy logic based obstacle avoidance to create safe movement. The system also provides easy integration with any communications protocol, plug-and-play devices, perceptions, and behaviors. Most behaviors and the obstacle avoidance parameters are easily changed through configuration files. Combined with previous work in the area of navigation and localization a very robust autonomy suite is created.
Full Text Available This article aims to analyse the phenomenon of the diffusion of interpretive paradigms or argumentation models between constitutional courts. This phenomenon involves the importation of parameters - defined here as extra-systemic to a specific legal system - and the use of the comparative method in applying constitutional texts.The main subject of this study is the analysis of the first 11 years of South African constitutional jurisprudence, which is a convenient scenario since a constitutional provision enables the Constitutional Court to 'consider foreign law' when interpreting the Bill of Rights. In fact, this led to the wide use of foreign jurisprudence and legislation (from which were extracted argumentation models, patterns of balancing between principles and sometimes actual normative 'meanings': in other words, extra-systemic legal inferences. This article shows the existence of several patterns of legal argumentation based on foreign law which were developed by the South African Constitutional Court.
Kildemoes, Helle Wallach; Hendriksen, Carsten; Morten, Andersen
ABSTRACT Purpose To develop a pharmacoepidemiologic method for drug utilization analysis according to indication, gender, and age by means of register-based information. Statin utilization in 2005 was applied as an example. Methods Following the recommendations for statin therapy, we constructed an...... indication hierarchy with eight mutually exclusive levels of register markers of cardiovascular disease and diabetes. Danish residents, as of January 1, 1996, were followed at the individual level in nationwide registers with respect to dispensed prescriptions of cardiovascular drugs and antidiabetics (1996...... prescription patterns of statins. The method can be implemented for other drug categories and could be useful for studying trends in drug utilization, differential drug adherence, and cross-national comparisons...
Alexander, Patricia A.; Dumas, Denis; Grossnickle, Emily M.; List, Alexandra; Firetto, Carla M.
Relational reasoning is the foundational cognitive ability to discern meaningful patterns within an informational stream, but its reliable and valid measurement remains problematic. In this investigation, the measurement of relational reasoning unfolded in three stages. Stage 1 entailed the establishment of a research-based conceptualization of…
Ormand, C. J.; Shipley, T. F.; Tikoff, B.; Manduca, C. A.; Dutrow, B. L.; Goodwin, L. B.; Hickson, T.; Atit, K.; Gagnier, K. M.; Resnick, I.
Spatial visualization is an essential skill in many, if not all, STEM disciplines. It is a prerequisite for understanding subjects as diverse as fluid flow through 3D fault systems, magnetic and gravitational fields, atmospheric and oceanic circulation patterns, cellular and molecular structures, engineering design, topology, and much, much more. Undergraduate geoscience students, in both introductory and upper-level courses, bring a wide range of spatial skill levels to the classroom. However, spatial thinking improves with practice, and can improve more rapidly with intentional training. As a group of geoscience faculty members and cognitive psychologists, we are collaborating to apply the results of cognitive science research to the development of teaching materials to improve undergraduate geology majors' spatial thinking skills. This approach has the potential to transform undergraduate STEM education by removing one significant barrier to success in the STEM disciplines. Two promising teaching strategies have emerged from recent cognitive science research into spatial thinking: gesturing and predictive sketching. Studies show that students who gesture about spatial relationships perform better on spatial tasks than students who don't gesture, perhaps because gesture provides a mechanism for cognitive offloading. Similarly, students who sketch their predictions about the interiors of geologic block diagrams perform better on penetrative thinking tasks than students who make predictions without sketching. We are developing new teaching materials for Mineralogy, Structural Geology, and Sedimentology & Stratigraphy courses using these two strategies. Our data suggest that the research-based teaching materials we are developing may boost students' spatial thinking skills beyond the baseline gains we have measured in the same courses without the new curricular materials.
The concept of remote damage control resuscitation (RDCR) is still in its infancy and there is significant work to be done to improve outcomes for patients with life-threatening bleeding secondary to injury. The prehospital phase of resuscitation is critical and if shock and coagulopathy can be rapidly minimized before hospital admission this will very likely reduce morbidity and mortality. The optimum transfusion strategy for these patients is still highly debated and the potential implications of the recently published pragmatic, randomize, optimal platelet, and plasma ratios trial (PROPPR) for RDCR have been reviewed. Identifying the appropriate transfusion strategy is mandatory before adopting prehospital hemostatic resuscitation strategies. An alternative approach is based on the early administration of coagulation factor concentrates combined with the antifibrinolytic tranexamic acid (TXA). The three major components to this approach in the context of RDCR target the following steps to achieve hemostasis: 1) stop (hyper)fibrinolysis; 2) support clot formation; and 3) increase thrombin generation. Strong evidence exists for the use of TXA. The data from the prospective fibrinogen in trauma induced coagulopathy (FIinTIC) study will inform on the prehospital use of fibrinogen in bleeding trauma patients. Deficits in thrombin generation may be addressed by the administration of prothrombin complex concentrates. Handheld point-of-care devices may be able to support and guide the prehospital and remote use of intravenous hemostatic agents including coagulation factor concentrates along with clinical presentation, assessment, and the extent of bleeding. Combinations may even be more effective for bleeding control. More studies are urgently needed. PMID:27100752
Much of human reasoning is approximate in nature. Formal models of reasoning traditionally try to be precise and reject the fuzziness of concepts in natural use and replace them with non-fuzzy scientific explicata by a process of precisiation. As an alternate to this approach, it has been suggested that rather than regard human reasoning processes as themselves approximating to some more refined and exact logical process that can be carried out with mathematical precision, the essence and power of human reasoning is in its capability to grasp and use inexact concepts directly. This view is supported by the widespread fuzziness of simple everyday terms (e.g., near tall) and the complexity of ordinary tasks (e.g., cleaning a room). Spatial reasoning is an area where humans consistently reason approximately with demonstrably good results. Consider the case of crossing a traffic intersection. We have only an approximate idea of the locations and speeds of various obstacles (e.g., persons and vehicles), but we nevertheless manage to cross such traffic intersections without any harm. The details of our mental processes which enable us to carry out such intricate tasks in such apparently simple manner are not well understood. However, it is that we try to incorporate such approximate reasoning techniques in our computer systems. Approximate spatial reasoning is very important for intelligent mobile agents (e.g., robots), specially for those operating in uncertain or unknown or dynamic domains.
Gillham, David; Tucker, Katie; Parker, Steve; Wright, Victoria; Kargillis, Christina
Nurse educators are challenged to keep up with highly specialised clinical practice, emerging research evidence, regulation requirements and rapidly changing information technology while teaching very large numbers of diverse students in a resource constrained environment. This complex setting provides the context for the CaseWorld project, which aims to simulate those aspects of clinical practice that can be represented by e-learning. This paper describes the development, implementation and evaluation of CaseWorld, a simulated learning environment that supports case based learning. CaseWorld provides nursing students with the opportunity to view unfolding authentic cases presented in a rich multimedia context. The first round of comprehensive summative evaluation of CaseWorld is discussed in the context of earlier formative evaluation, reference group input and strategies for integration of CaseWorld with subject content. This discussion highlights the unique approach taken in this project that involved simultaneous prototype development and large scale implementation, thereby necessitating strong emphasis on staff development, uptake and engagement. The lessons learned provide an interesting basis for further discussion of broad content sharing across disciplines and universities, and the contribution that local innovations can make to global education advancement. PMID:26522447
Miriam RODRÍGUEZ PALLARES
Full Text Available In the academic year 2013-2014, the MediaCom UCM research group conducted a study among students in the first and fourth year of the Degree in Journalism at UCM with the pretention to know the reasons that they decided to pursue these studies, their perceptions of journalism and media influence. From a quantitative analysis model relatively vocational criteria among students are perceived; generally they believe that journalists are not very independent and that political and economic factors influence in the activity of the media sector, whose influence on policy choices and consumption is subject to debate. This article is part of an academic project, whose results are intended to work with universities to improve their teaching and training model of students according to their perception of journalism as a profession.
How can we advance knowledge? Which methods do we need in order to make new discoveries? How can we rationally evaluate, reconstruct and offer discoveries as a means of improving the ‘method’ of discovery itself? And how can we use findings about scientific discovery to boost funding policies, thus fostering a deeper impact of scientific discovery itself? The respective chapters in this book provide readers with answers to these questions. They focus on a set of issues that are essential to the development of types of reasoning for advancing knowledge, such as models for both revolutionary findings and paradigm shifts; ways of rationally addressing scientific disagreement, e.g. when a revolutionary discovery sparks considerable disagreement inside the scientific community; frameworks for both discovery and inference methods; and heuristics for economics and the social sciences.
Jia Tian; Xun Chen; Sheng-Ping Dong
In this paper, a Multi Modal Reasoning (MMR) method integrated with probabilistic reasoning is proposed for the diagnosis support module of the open eHealth platform. MMR is based on both Rule Based Reasoning (RBR) and Case Based Reasoning (CBR). It is not only applied to the identification of diseases and syndromes based on medical guidelines,but also deals with exceptional cases and individual therapies in order to improve diagnostic accuracy. Moreover, a new rule expression frame is introduced to deal with uncertainty, which can represent and process vague, imprecise, and incomplete information. Furthermore, this system is capable of updating the attributes of rules and inducing rules with a small data sample.
刘嘉; 童格明; 李明; 臧凤奎
Unified modelling language (UML) is a semi -formal language, its semantics sector is described with natural language, which leads to the semantic inconformity in the process of modelling. The paper presents a formal method of UML class diagram based on detailed comparison of UML class diagram and ontology. Firstly we transform the UML class diagram to corresponding ontology; then we reason the transformed ontology according to the reasoning algorithm of Tableau provided by the ontology, and detect the inconformity in it so as to modify the UML class diagram, at the end we obtain the accurate UML class diagram.%统一建模语言(IJML)是一个半形式化的语言,其语义部分是采用自然语言描述的,使得它在建模过程中会产生语义不一致等问题.在详细比较UML类图与本体的基础上,提出了一种UML类图的形式化方法;首先将UML类图转换为相应的本体;然后根据本体提供的推理算法(Tableau)对转换得到的本体进行推理,检测其中的不一致性从而修改UML类图,最后达到精确UML类图.
Acar, Ömer; Patton, Bruce R.
This study had two research purposes. First, we examined the scientific reasoning gains of prospective science teachers who are concrete, formal, and postformal reasoners in an argumentation-based physics inquiry instruction. Second, we sought conceptual knowledge and achievement gaps between these student groups before and after the instruction.…
La recerca presentada en aquesta dissertació glossa sobre transformacions de tempo de gravacions monofòniques de saxo jazz preservant l'expressivitat musical. Es una contribució al processament d'audio basat en el contingut, un camp de recerca que ha emergit recentment com a resposta a la necessitat creixent de gestionar intel·ligentment la creixent quantitat d'informació digital multimedia disponible actualment. S'ha investigat com una execució musical, tocada a un tempo concret, es pot...
Kun Chang Lee; Namho Lee
Recent advent of mobile commerce or m-commerce suggests a need to incorporate intelligent techniques capable of providing decision support consistent with past instances as well as coordination support for conflicting goals and preferences among mobile users. Since m-commerce allows users to move around while doing business transactions, it seems imperative for the m-commerce users to be given high quality of decision support which should be timely and consistent with past instances. For this...
Heidar Hashemi; Awaluddin Mohamed Shaharoun; Izman, S.; Denni Kurniawan
Fixture design is an important issue in the process of manufacturing. As a critical design activity process, automation in fixture design plays an integral role in linking computer aided designs and computer aided manufacturing. This paper carries out a literature review of computer aided fixture design (CAFD) developments using intelligent methods that have been commonly utilized in automation in the last two decades. The first part of this review considers the steps of fixture design along ...
The ore grade, the geometry of an orebody as well as the mineralogical properties of the ore determine process selection for gold extraction. These factors have an effect on the metallurgical response of an ore to a proposed treatment scheme. The uniqueness of each ore deposit is the main challenge in the extraction process development for any ore. The mineralogical mode of occurrence of gold, gold grain size distribution, host and gangue mineral type, mineral associations and alterations all...
In this paper a CBR system for mammography CAD that uses feature scaling to improve the systems classification performance is proposed. The CBR system was evaluated on the public DDSM mammography database. We use ROC analysis and leaving-one-out sampling to show that the feature weighting approach results in improved ROC performance. (orig.)
Marzouk, Mohamed M.; Rasha M. Ahmed
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 t...
Carneiro, Davide Rua; Novais, Paulo; Andrade, Francisco Carneiro Pacheco; Zeleznikow, John; Neves, José
The growing use of Information Technology in the commercial arena leads to an urgent need to find alternatives to traditional dispute resolution. New tools from fields such as Artificial Intelligence should be considered in the process of developing novel Online Dispute Resolution platforms, in order to make the ligation process simpler, faster and conform with the new virtual environments. In this work, we describe UMCourt, a project built around two sub-fields of Artificial Intelligence res...
Jorge Bacca; Silvia Baldiris; Ramon Fabregat; Cecilia Avila
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 th...
Smyth, Barry; Keane, Mark T.
Case-based reasoning (CBR) has been applied with some success to complex planning and design tasks. In such systems, the best case is retrieved and adapted to solve a particular target problem. In general, the best case is that which can be most easily adapted to the target problem (as the overhead in adaptation is often very high). Standard CBR systems use semantic-similarity to retrieve cases, on the assumption that the most similar case is the best or easiest case to adapt. ...
The use of Knowledge-Based systems and advanced graphic concepts are described using the Automated Reasoning Tool (ART) for a model nuclear plant system. Through the sue of asynchronous graphic input/output, the user is allowed to communicate through a graphical display to a Production-Rule Analysis System modelling the plant while its rules are actively being fired. The user changes the status of system components by pointing at them on the system configuration display with a mouse cursor and clicking one of the buttons on the mouse. The Production-Rule Analysis System accepts the new input and immediately displays its diagnosis of the system state and any associated recommendations as to the appropriate course of action. This approach offers a distinct advantage over typing the components statuses in response to queries by a conventional Production-Rule Analysis system. Moreover, two effective ways of communication between man and machine are combined
Johnson, J K; Cotman, C W; Tasaki, C S; Shaw, G L
Several recent studies have investigated the effectiveness of various behavioral interventions on the cognitive performance of subjects with Alzheimer's disease (AD). Simulations of Shaw's structured model of the cortex led to the predictions that music might enhance spatial-temporal reasoning. A subsequent behavioral study in college students documented an improvement in scores on a spatial-temporal task after listening to a Mozart piano sonata. In this study, we investigated the enhancement of scores on a spatial-temporal task after a Mozart listening condition in a set of twins who are discordant for AD. After listening to an excerpt from a Mozart piano sonata, the AD twin showed considerable improvement on the spatial-temporal task when compared with pretest scores. Furthermore, no enhancement of scores was seen following either of the control conditions (i.e., silence or 1930s popular tunes). This finding suggests that music may be used as a tool to investigate functional plasticity in Alzheimer's disease and to better understand the underlying pathophysiology. PMID:9864729
Eggert, Sabina; Nitsch, Anne; Boone, William J.; Nückles, Matthias; Bögeholz, Susanne
Climate change is one of the most challenging problems facing today's global society (e.g., IPCC 2013). While climate change is a widely covered topic in the media, and abundant information is made available through the internet, the causes and consequences of climate change in its full complexity are difficult for individuals, especially non-scientists, to grasp. Science education is a field which can play a crucial role in fostering meaningful education of students to become climate literate citizens (e.g., NOAA 2009; Schreiner et al., 41, 3-50, 2005). If students are, at some point, to participate in societal discussions about the sustainable development of our planet, their learning with respect to such issues needs to be supported. This includes the ability to think critically, to cope with complex scientific evidence, which is often subject to ongoing inquiry, and to reach informed decisions on the basis of factual information as well as values-based considerations. The study presented in this paper focused on efforts to advance students in (1) their conceptual understanding about climate change and (2) their socioscientific reasoning and decision making regarding socioscientific issues in general. Although there is evidence that "knowledge" does not guarantee pro-environmental behavior (e.g. Schreiner et al., 41, 3-50, 2005; Skamp et al., 97(2), 191-217, 2013), conceptual, interdisciplinary understanding of climate change is an important prerequisite to change individuals' attitudes towards climate change and thus to eventually foster climate literate citizens (e.g., Clark et al. 2013). In order to foster conceptual understanding and socioscientific reasoning, a computer-based learning environment with an embedded concept mapping tool was utilized to support senior high school students' learning about climate change and possible solution strategies. The evaluation of the effect of different concept mapping scaffolds focused on the quality of student
Tang, Antony; van Vliet, Hans
Despite recent advancements in software architecture knowledge management and design rationale modeling, industrial practice is behind in adopting these methods. The lack of empirical proofs and the lack of a practical process that can be easily incorporated by practitioners are some of the hindrance for adoptions. In particular, the process to support systematic design reasoning is not available. To rectify this issue, we propose a design reasoning process to help architects cope with an architectural design environment where design concerns are cross-cutting and diversified.We use an industrial case study to validate that the design reasoning process can help improve the quality of software architecture design. The results have indicated that associating design concerns and identifying design options are important steps in design reasoning.
Fatemeh Rezaei; Saharnaz Nedjat; Banafsheh Golestan; Reza Majdzadeh
Objectives: Identifying the underlying factors contributing to smoking among teenagers is important in establishing smoking control programs. The present study was designed to identify and compare factors revealed in a preceding qualitative study conducted on 13-15 year-old boys living in two different socio-economic districts in the Northern and Southern parts of Tehran. Methods: Two completely similar case-control studies, each with 200 subjects, were conducted using a snowball sampling....
Balkman, Jason D; Loehfelm, Thomas W
Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. PMID:24819664
Nissen, Ulrik Becker
Taking the startingpoint in an assertion of an ambiguity in the Lutheran tradition’s assessment of reason, the essay argues that the Kantian unreserved confidence in reason is criticised in Bonhoeffer. Based upon a Christological understanding of reason, Bonhoeffer endorses a view of reason which...... is treated in the essay. Here it is argued that Bonhoeffer may be appropriated in attempting to outline a Christological ontology of reason holding essential implications for the sources and conditions of public discourse....
The purpose of this thesis was to explore the Reasons for the transition of the processing trade indus-try from OEM to OBM. The study was commissioned by Sandy Chen who is the manager of the case company is Hangzhou Alpha Imp & Exp Co., Ltd. The theoretical part of the study consists of litera-ture on strategic marketing management, brand management and value chain; most of data, informa-tion were collected in related records, news, reports, thesis, article and webpage. The study was co...
Simonson, Itamar; Nowlis, Stephen M.
This research investigates the interaction effect of a very common task, explaining decisions, and an individual difference, need for uniqueness (NFU), on buyer decision-making. We propose that explaining (or providing reasons for) decisions shifts the focus from the choice options to the choice of reasons. Furthermore, buyers who explain their decisions and have high NFU tend to select unconventional reasons and are, consequently, more likely to make unconventional choices. These predictions...
Bogaart, Patrick; Rupp, David; Selker, John; van der Velde, Ype
Recession discharge from hillslopes and catchments is commonly summarized by the top-down Brutsaert and Nieber (1977) analysis in which a power law of the form -dQ/dt = aQb is fitted through recession data. In many cases exponent b is found to be within the range 1 to 2. A key question in hillslope and catchment hydrology is how this range can be explained from underlying bottom-up physical theory and system properties. A common approach in hillslope hydrology is to apply the Boussinesq equation, either in it's original nonlinear form, or a a linearized simplification, in concert with assumptions like thin soils of uniform hydraulic conductivity. We found that the nonlinear Boussinesq equation in this setting leads to b = 0, and thus is inconsistent with observations. Careless interpretation of the recession response from a Boussinesq model could lead to an erroneous conclusion of b = 1. We demonstrate how this artifactual model response arises from the internal numerics of spatially distributed PDE models that hinder complete drying out. We demonstrate how this trait - models that can't dry out - by necessity lead to b ≥ 1 behaviour. Some commonly used model approaches share this trait: As described above, numerical implementations of the nonlinear Boussinesq equation retain the last bits of water, and therefore suggest b = 1 (which is shown to be an artifact) Both analytical and numerical solutions to the linearized Boussinesq equation are unable to move the drainage front downhill (as explained earlier by Stagnitti et al. (2004)), which causes retainment of water, leading to b = 1 at all times. Vertically decreasing hydraulic conductivity, e.g. a power-law or exponential profile, leads to b = 1 to 2. Based on the reasoning that the linearized Boussinesq equation (as a meta-model) is only valid if it adequately mimics the essential dynamics of the nonlinear Boussinesq equation (as a reference model) we conclude that explanations of observed b = 1 based on the
Itzhak Gilboa; David Schmeidler
"Case-Based Decision Theory" is a theory of decision making under uncertainty, suggesting that people tend to choose acts that performed well in similar cases they recall. The theory has been developed from a decision-/game-/economic-theoretical point of view, as a potential alternative to expected utility theory. In this paper we attempt to re-consider CBDT as a theory of knowledge representation and of planning, to contrast it with the rule-based approach, and to study its implications rega...
Mohamad Mahdi Hazavehei
Full Text Available Background & Objective: Divorce, unwanted pregnancies, and unsuccessful marriages create mental, emotional, physical, and financial problems for individuals, families, and ultimately the community. Premarital education and counseling is one of the most effective ways for the prevention of such problems. The purpose of this study was to describe and evaluate the effectiveness of a premarital educational program by using the TRA (Theory of Reasoned Action. Materials and Methods: Four hundred couples who attended premarital education and counseling classes voluntarily participated in this descriptive and analytical study. Variables such as attitude, subjective norms, and intention, were collected by using a validated questionnaire based on the TRA components. The questionnaire was filled out before and after the educational classes. Results: The mean age of the couples was 23.16 ± 5.64 years old. Statistically significant differences were found in knowledge, attitude, and subjective norms before and after participation in the classes (p value 0.05. Conclusion: Although the mean knowledge and attitude of the couples under study increased after the classes, the increase was not high and only 20% of the couples gained acceptable knowledge. The effectiveness of such classes in the current manner is very low. Application of appropriate educational methods and media-based models and theories is highly recommended.
Analogical reasoning is known as a powerful mode for drawing plausible conclusions and solving problems. It has been the topic of a huge number of works by philosophers, anthropologists, linguists, psychologists, and computer scientists. As such, it has been early studied in artificial intelligence, with a particular renewal of interest in the last decade. The present volume provides a structured view of current research trends on computational approaches to analogical reasoning. It starts with an overview of the field, with an extensive bibliography. The 14 collected contributions cover a large scope of issues. First, the use of analogical proportions and analogies is explained and discussed in various natural language processing problems, as well as in automated deduction. Then, different formal frameworks for handling analogies are presented, dealing with case-based reasoning, heuristic-driven theory projection, commonsense reasoning about incomplete rule bases, logical proportions induced by similarity an...
Rivet, Ann E.; Kastens, Kim A.
In recent years, science education has placed increasing importance on learners' mastery of scientific reasoning. This growing emphasis presents a challenge for both developers and users of assessments. We report on our effort around the conceptualization, development, and testing the validity of an assessment of students' ability to reason around…
Full Text Available 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 a user performs, a single type of knowledge and reasoning method is often not sufficient. It is often necessary to determine which reasoning method would be the most appropriate for each task, and a combination of different methods has often shown the best results. In this study CBR was mixed with other RBR and MBR approaches to promote synergies and benefits beyond those achievable using CBR or other individual reasoning approaches alone. Each approach has advantages and disadvantages, which are proved to be complementary in a large degree. So, it is well-justified to combine these to produce effective hybrid approaches, surpassing the disadvantages of each component method. “KNAPS-CR” model integrates problem solving with learning from experience within an extensive model of different knowledge types. “KNAPS-CR” has a reasoning strategy which first attempts case-based reasoning, then rule-based reasoning, and, finally, model-based reasoning. It learns from each problem solving session by updating its collection of cases, irrespective of which reasoning method that succeeded in solving the problem.
Gupta, Ayush; Elby, Andrew; Conlin, Luke D.
Many science education researchers have argued that learners' commitment to a substance (matter-based) ontology impedes the learning of scientific concepts that scientists typically conceptualize as processes or interactions, such as force, electric current, and heat. By this account, students' tendency to classify these entities as substances or properties of substances leads to robust misconceptions, and instruction should steer novices away from substance-based reasoning. We argue that substance-based reasoning can contribute to the learning and understanding of these very same physics concepts. Our case study focuses on a group of elementary school science teachers in our professional development program. Starting from substance-based metaphors for gravity, the teachers build a sophisticated explanation for why objects of different masses fall with the same acceleration. We argue that, for conceptual, epistemological, and affective reasons, instructional interventions should focus on tapping these productive substance-based resources when they arise rather than attempting to suppress them.
Blomberg, Karin; Ternestedt, Britt-Marie; Törnberg, Sven; Tishelman, Carol
In Stockholm, Sweden, women are invited to a cost-free population-based cervical cancer screening programme (PCCSP) at regular intervals. Despite this, many women choose not to attend screening at all or to take opportunistic tests instead. This study explores how women who actively declined participation in the PCCSP reasoned about their choice. Qualitative telephone interviews and fax messages from women who actively declined participation in the PCCSP were analysed inductively. The manner in which women defined and conceptualized distinctions between, and the roles and responsibilities of, both private and public spheres were found to be central in explanations of decision making. Factors related to women's decisions not to participate in screening at all include a lack of confidence in the benefits of screening, previous negative health care and preventive experiences, a belief in one's own ability to discern health changes or a belief that one was not at risk for cervical cancer, as well as a number of unconventional standpoints on social and political issues. Women who chose not to participate in the organized PCCSP, but who did use private opportunistic screening, generally motivated this with direct or indirect criticism of the screening programme itself. Not only was the examination itself sensitive but also all facets of the PCCSP, from invitation letter on, were found to influence women's decisions. Using Jepson et al.'s ethical framework to peruse the evidence-base underlying women's 'informed decision-making' about CCS is suggested to be more constructive than discussing potential participants' knowledge versus lack of knowledge. PMID:17886262
Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine
Incorrect or improper diagnostic tests uses have important implications for health outcomes and costs. Clinical Decision Support Systems purports to optimize the use of diagnostic tests in clinical practice. The computerized medical reasoning should not only focus on existing medical knowledge but also on physician's previous experiences and new knowledge. Such medical knowledge is vague and defines uncertain relationships between facts and diagnosis, in this paper, Case Based Fuzzy Cognitive Maps (CBFCM) are proposed as an evolution of Fuzzy Cognitive Maps. They allow more complete representation of knowledge since case-based fuzzy rules are introduced to improve diagnosis decision. We have developed a framework for interacting with patient's data and formalizing knowledge from Guidelines in the domain of Urinary Tract Infection. The conducted study allowed us to test cognitive approaches for implementing Guidelines with Semantic Web tools. The advantage of this approach is to enable the sharing and reuse of knowledge from Guidelines, physicians experiences and simplify maintenance. PMID:22874199
Halpern, Joseph Y.; Pucella, Riccardo
Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the underlying representation of uncertainty. We give sound and complete axiomatizations for the logic in the case that the underlying representation is (a) probability, (b) sets of probability measures, (c) belief functions, and (d) possibility measures. We show th...
Ørngreen, Rikke; Guralnick, David
in the Workplace). The purpose of this paper is to describe the two online learning methodologies and to raise questions for future discussion. In the workshop, the organizers and participants work with and discuss differences and similarities within the two pedagogical methodologies, focusing on how......Abstract- This paper has its origin in the authors' reflection on years of practical experiences combined with literature readings in our preparation for a workshop on learn-by-doing simulation and case-based learning to be held at the ICELW 2008 conference (the International Conference on E-Learning...... they are applied in workplace related and e-learning contexts. In addition to the organizers, a small number of invited presenters will attend, giving demonstrations of their work within learn-by-doing simulation and cases-based learning, but still leaving ample of time for discussion among all...
The representation and acquisition of a product gene is a crucial problem in product evolutionary design. A new methodology of product gene representation and acquisition from a population of product cases is proposed, and the methodology for product evolutionary design based on a population of product cases is realized. By properly classifying product cases according to its product species, the populations of product cases are divided and a model is established. Knowledge of the scheme design is extracted and formulated as the function base, principle base, and structure base, which are then combined to form a product gene. Subsequently, the product gene tree is created and represented by object-oriented method. Then combining this method with the evolutionary reasoning technology, an intelligent and automatic evolutionary scheme design of product based on the population of product cases is realized. This design method will be helpful in the processing of knowledge formulation, accumulation, and reuse, and in addressing the difficulty of acquiring design knowledge in traditional design. In addition, the disadvantages of manual case adaptation and update in case-based reasoning can be eliminated. Moreover, by optimizing the design scheme in multiple levels and aspects of product function, principle, and structure etc., the level of creativity in the scheme design can be improved.
Gupta, Ayush; Conlin, Luke D
Many science education researchers have argued that learners' commitment to a substance (matter-based) ontology impedes the learning of scientific concepts that scientists typically conceptualize as processes or interactions, such as such as force, electric current, and heat. By this account, students' tendency to classify these entities as substances or properties of substances leads to robust misconceptions, and instruction should steer novices away from substance-based reasoning. We argue that substance-based reasoning, when it supports learners' sense-making, can form the seeds for sophisticated understanding of these very same physics concepts. We present a case study of a group of elementary school science teachers in our professional development program. The teachers build a sophisticated explanation for why objects of different masses have the same acceleration due to gravity, starting from substance-based metaphors for gravity. We argue that, for conceptual, epistemological, and affective reasons, in...
Muhammad Khalid Khan
Full Text Available This study is an attempt to investigate the tourism marketing and attraction strategies adopted by various countries. A case study based approach is adopted in this study. On the basis of investigation of tourism development strategies adopted by various countries, suggestions are also made at the end. These suggestions are aimed to increase visitors our tourists’ base in a country. These suggestions can be used by any country to increase visitors or tourists. Future directions are also given at the end.
Santosh Kumar Swain; Durga Prasad Mohapatra; Rajib Mall
We present a comprehensive test case generation technique from UML models. We use the features in UML 2.0 sequence diagram including conditions, iterations, asynchronous messages and concurrent components. In our approach, test cases are derived from analysis artifacts such as use cases, their corresponding sequence diagrams and constraints specified across all these artifacts. We construct Use case Dependency Graph (UDG) from use case diagram and Concurrent Control Flow Graph (CCFG) from cor...
Christiansen, Ellen Tove
The aim of this paper is to position interaction design and information architecture in relation to design of interfaces to ICT applications meant to serve the goal of supporting users’ reasoning, be it learning applications or self-service applications such as citizen self-service. Interaction...... with such applications comprises three forms of reasoning: deduction, induction and abduction. Based on the work of Gregory Bateson, it is suggested that the disciplines of interaction design and information architecture are complementary parts of information processes. To show that abduction...... are different, complementary, and indispensible for the information processes, and that design of sense making can not need both disciplines....
Chen, Tzy-Ling; Chen, Tzu-Jung
This study examined attitudes of university faculty specialising in the field of human resource (HR) in Taiwan towards participation in the teaching of online courses using the theory of reasoned action (TRA). The population targeted for investigation consisted of the full-time university faculty in the HR field in Taiwan regardless of their…
With the development of information technology, DSS can be used to resolve the complex process of the feasible reasoning and scientific decision-making of projects. This paper offers 7 exploiting principles for the computer support system on feasible reasoning and scientific decision-making of projects, that is, the principles of standardization, procedure, specification, agility, currency, practicability and development. On the basis of analysis on systematic procedure, the computer support system on feasible reasoning and scientific decisionmaking of projects is formed based on WEB, and its general structure, system function and the methods to be realized are introduced. The data composition of this system is analyzed following the principles of integrality,development, perspicuity and consistency. Also, the model-base management system is designed for the management of model storage and management of model operation.
Nilüfer Onak KANDEMİR
Full Text Available Objective: Fine needle aspiration cytology is the first step in the diagnosing breast lesions. This study evaluated factors causing falsenegative and false-positive diagnoses when evaluating breast lesions using this technique.Material and Method: In this study, we retrospectively examined 511 breast diagnoses, based on Fine needle aspiration cytology specimens, made in the Medical School of Zonguldak Karaelmas University, Department of Pathology, between 2002 and 2009. Factors affecting the reliability of fine needle aspiration cytology were evaluated by comparing the cytological and biopsy diagnoses and using the clinical parameters in the diagnosis of breast lesions.Result: In our series, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of fine needle aspiration cytology were 77%, 99%, 95%, 93%, and 95%, respectively. The falsenegative diagnosis rate was 4% and the false-positive diagnosis rate was 1%.Conclusion: Sampling errors and erroneous interpretation of cellular monomorphism are the most important reasons for false-negative diagnosis results in the evaluation of breast lesions with fine needle aspiration cytology. Increased cellularity and reactive cell atypia in benign proliferative breast lesions are the most frequent reasons for false-positive diagnosis.
Vilstrup Pedersen, Klaus; Boye, Niels
is stored and made accessible when relevant to the reasoning context and the specific patient case. Furthermore, the information structure supports the creation of new generalized knowledge using data mining tools. The patient case is divided into an observation level and an opinion level. At the opinion......, Knowledge Management Systems and Business Intelligence to make context based, patient case specific analysis and knowledge management. The knowledge base integrates three sources of information that supports clinical reasoning: general information, guidelines and health records. New generalized knowledge...... level, reasoning participants can express their argument based opinions about a patient case, thereby enhancing the knowledge about the state of and plans for the patient. An opinion language that supports expressing a possible imprecise/uncertain opinion based on imprecise...
Sharkey, Leslie; Michael, Helen; LeBeau, Brandon; Center, Bruce; Wingert, Deb
Our second-year core clinical pathology course uses free-response case-based learning exercises in an otherwise traditional lecture or laboratory course format to augment the development of skills in application of knowledge and critical thinking and clinical reasoning. We previously reported increased learner confidence accompanied by perceived improvements in understanding and ability to apply information, along with enhanced feelings of preparedness for examinations that students attributed to the case-based exercises. The current study prospectively follows a cohort of students to determine the ability of traditional multiple-choice versus free-response case-based assessments to predict future academic performance and to determine if the perceived value of the case-based exercises persists through the curriculum. Our data show that after holding multiple-choice scores constant, better performance on case-based free-response exercises led to higher GPA and better class rank in the second and third years and better class rank in the fourth year. Students in clinical rotations reported that the case-based approach was superior to traditional lecture or multiple-choice exam format for learning clinical reasoning, retaining factual information, organizing information, communicating medical information clearly to colleagues in clinical situations, and preparing high quality medical records. In summary, this longitudinal study shows that case-based free-response writing assignments are efficacious above and beyond standard measures in determining students' GPAs and class rank and in students' acquisition of knowledge, skills, and clinical reasoning. Students value these assignments and overwhelmingly find them an efficient use of their time, and these opinions are maintained even two years following the course. PMID:23187033
Yu Tongmin; Li Guanhua; Li Youmin; Lan Jian
On the basis of the comprehensive analysis about the automatic generation of the injection mold parting surface, the parting surface design method which introduces knowledge and casebased reasoning (CBR) into the computer-aided design is described by combining with the actual characteristic in injection mold design, and the design process of case-based reasoning method is also given. A case library including the information of parting surface is built with the index of main shape features. The automatic design of the mold parting surface is realized combined with the forward-reasoning method and the similarity solution procedure. The rule knowledge library is also founded including the knowledge, principles and experiences for parting surface design. An example is used to show the validity of the method, and the quality and the efficiency of the mold design are improved.
Modi, Jyoti Nath; Anshu; Gupta, Piyush; Singh, Tejinder
Clinical reasoning is a core competency expected to be acquired by all clinicians. It is the ability to integrate and apply different types of knowledge, weigh evidence critically and reflect upon the process used to arrive at a diagnosis. Problems with clinical reasoning often occur because of inadequate knowledge, flaws in data gathering and improper approach to information processing. Some of the educational strategies which can be used to encourage acquisition of clinical reasoning skills are: exposure to a wide variety of clinical cases, activation of previous knowledge, development of illness scripts, sharing expert strategies to arrive at a diagnosis, forcing students to prioritize differential diagnoses; and encouraging reflection, metacognition, deliberate practice and availability of formative feedback. Assessment of clinical reasoning abilities should be done throughout the training course in diverse settings. Use of scenario based multiple choice questions, key feature test and script concordance test are some ways of theoretically assessing clinical reasoning ability. In the clinical setting, these skills can be tested in most forms of workplace based assessment. We recommend that clinical reasoning must be taught at all levels of medical training as it improves clinician performance and reduces cognitive errors. PMID:26519715
目的：探讨米非司酮配伍米索前列醇终止早期妊娠致阴道出血过多的原因及防治。方法：分析2008年9月至2011年12月46例药物流产后出血量＞100ml者出血原因。结果：药物流产阴道出血过多与孕龄、胚胎组织排出时间及组织残留情况存在密切关系，与孕妇年龄无关。结论：药物流产后出血时间长及阴道出血过多是药物流产的最大缺点。预防的措施是严格掌握门诊药物流产指征，适时清宫，预防感染。%Objective To explore the reasons and Prevention and control measures of mifepristion and misoprostol to terminatc early pregnancy excessive vaginal bleeding. Methods The reason of bleeding in 46 cases whose bleeding volume were more than 100 ml caused by drug abortion from September 2008 to December 2011 was analyzed. Results Abortion drug caused excessive vaginal bleeding was related to gestational age,embryo tissue residue from time,had nothing to do with maternal age. Conclusion The most critical shortcoming of drug abortion is the long time and excessive vaginal bleeding,which comes after using drugs. The measurement is that,controling the outpatient drug abortion standard strictly,curettage timely,and preventing infection.
Johnson, E. A.; Ball, T. C.
An important objective in general education geoscience courses is to help students evaluate social and ethical issues based upon scientific knowledge. It can be difficult for instructors trained in the physical sciences to design effective ways of including ethical issues in large lecture courses where whole-class discussions are not practical. The Quality Enhancement Plan for James Madison University, "The Madison Collaborative: Ethical Reasoning in Action," (http://www.jmu.edu/mc/index.shtml) has identified eight key questions to be used as a framework for developing ethical reasoning exercises and evaluating student learning. These eight questions are represented by the acronym FOR CLEAR and are represented by the concepts of Fairness, Outcomes, Responsibilities, Character, Liberty, Empathy, Authority, and Rights. In this study, we use the eight key questions as an inquiry-based framework for addressing ethical issues in a 100-student general education Earth systems and climate change course. Ethical reasoning exercises are presented throughout the course and range from questions of personal behavior to issues regarding potential future generations and global natural resources. In the first few exercises, key questions are identified for the students and calibrated responses are provided as examples. By the end of the semester, students are expected to identify key questions themselves and justify their own ethical and scientific reasoning. Evaluation rubrics are customized to this scaffolding approach to the exercises. Student feedback and course data will be presented to encourage discussion of this and other approaches to explicitly incorporating ethical reasoning in general education geoscience courses.
Bouchon-Meunier, B; Delechamp, J.; Marsala, C.; Rifqi, M.
We present a general framework representing analogy, on the basis of a link between variables and measures of comparison between values of variables. This analogical scheme is proven to represent a common description of several forms of reasoning used in fuzzy control or in the management of knowledge-based systems, such as deductive reasoning, inductive reasoning or prototypical reasoning, gradual reasoning.
Mohamad Mahdi Hazavehei; Samane Shirahmadi*; Ghodratollah Roshanaei; Mohamad kazem- zade; Mohamad Mahdi majzubi
Background & Objective: Divorce, unwanted pregnancies, and unsuccessful marriages create mental, emotional, physical, and financial problems for individuals, families, and ultimately the community. Premarital education and counseling is one of the most effective ways for the prevention of such problems. The purpose of this study was to describe and evaluate the effectiveness of a premarital educational program by using the TRA (Theory of Reasoned Action). Materials and Methods: Four hund...
Heit, Evan; Rotello, Caren M.
One of the most important open questions in reasoning research is how inductive reasoning and deductive reasoning are related. In an effort to address this question, we applied methods and concepts from memory research. We used 2 experiments to examine the effects of logical validity and premise-conclusion similarity on evaluation of arguments.…
Caliendo, Julia C.
Problem-based learning in clinical practice has become an integral part of many professional preparation programs. This quasi-experimental study compared the effect of a specialized 90-hour field placement on elementary pre-service teachers' scientific reasoning and attitudes towards teaching STEM (science, technology, engineering, and math) subjects. A cohort of 53 undergraduate elementary education majors, concurrent to their enrollment in science and math methods classes, were placed into one of two clinical practice experiences: (a) a university-based, problem-based learning (PBL), STEM classroom, or (b) a traditional public school classroom. Group gain scores on the Classroom Test of Scientific Reasoning (CTSR) and the Teacher Efficacy and Attitudes Toward STEM Survey-Elementary Teachers (T-STEM) survey were calculated. A MANCOVA revealed that there was a significant difference in gain scores between the treatment and comparison groups' scientific reasoning (p = .011) and attitudes towards teaching STEM subjects (p = .004). The results support the hypothesis that the pre-service elementary teachers who experienced STEM mentoring in a PBL setting will have an increase in their scientific reasoning and produce positive attitudes towards teaching STEM subjects. In addition, the results add to the existing research suggesting that elementary pre-service teachers require significant academic preparation and mentored support in STEM content.
Xu, L D
The traditional approach to the development of knowledge-based systems (KBS) has been rule-based, where heuristic knowledge is encoded in a set of production rules. A rule-based reasoning (RBR) system needs a well constructed domain theory as its reasoning basis, and it does not make substantial use of the knowledge embedded in previous cases. An RBR system performs relatively well in a knowledge-rich application environment. Although its capability may be limited when previous experiences are not a good representation of the whole population, a case-based reasoning (CBR) system is capable of using past experiences as problem solving tools, therefore, it is appropriate for an experience-rich domain. In recent years, both RBR and CBR have emerged as important and complementary reasoning methodologies in artificial intelligence. For problem solving in AIDS intervention and prevention, it is useful to integrate RBR and CBR. In this paper, a hybrid KBS which integrates a deductive RBR system and an inductive CBR system is proposed to assess AIDS-risky behaviors. PMID:8666473
Juan Miguel Rosa González; Miguel Eduardo Moreno Añez; Hilka Vier Machado
This article focuses on the process of new business creation, considering the effectuation approach, which explains the phenomenon of entrepreneurship in a different perspective than the traditional causal approach. Beginning with a description of the effectual approach assumptions, a case study about the subject is presented in order to explore the logic of the business creation process. The case discusses a Brazilian organization created in 1980 to produce materials and services in steel i...
Barry, Brock; Yadav, Aman
The case method: Using case-based instruction to increase ethical understanding in engineering courses Introduction The paper presents a discussion of how case-based instruction is performed and the perceived benefits of its application. We begin with a brief discussion of the historical background of case- based instruction and then discuss the use of case methodologies within various educational contexts. Connections are then made to its use in general ethics instruction, as well as spec...
I shall first introduce the idea of reasoning, and of defeasible reasoning in particular. I shall then argue that cognitive agents need to engage in defeasible reasoning for coping with a complex and changing environment. Consequently, defeasibility is needed in practical reasoning, and in particular in legal reasoning
YANG Lan-rong; ZHANG Jin-long
This paper presents a Case-Based system for assisting construction project managers in identifying risk factors and the corresponding construction project risk. The construction project risk identification model captures the case, acquired from previous completed construction projects and experience. A prototype is developed based on the proposed Case-Based system to determine risk factors along with their risk effects.
Objective To improve root canal treatment for the elderly by analyzing reasons for the unsuccessful cases.Method Analyzing symptoms,physical signs and accessory examination based on 30 unsuccessful cases of root canal treatment for the elderly in the hospital from 2010~2013.Result 3 cases of loose defective teeth III°,12 cases of defective teeth with crown fractures,root fractures and restoration falling,4 cases of recurrent caries,7cases of lack of filling of root canal,1 case of vertical root fractures,1 case of root canal instrument fracture,2 cases of missed root canal.Conclusion Unsuccessful root canal treatment for the elderly is attributed to physical conditions of patients,aging changes of medullary cavity and root canals,changes in periodontal tissue and a disorder of occluding relation.%目的：探讨老年人根管治疗失败的原因，使老年人根管治疗的成功率有所提高。方法收集2010～2013年我院接诊的根管治疗失败的老年患者30例，根据患者症状、体征、X线检查分析判断导致治疗失败的原因。结果患牙III°松动3例，冠折、根折、充填物脱落12例，继发龋4例，根管欠填7例，牙根纵裂1例，根管内器械折断1例，遗漏根管2例。结论老年人根管治疗失败的主要原因为患者自身因素的影响、牙周组织的改变、髓腔及根管增龄性变化、咬合关系紊乱等。
Jin, Xiaoping; Mao, Enrong; Cheng, Bo
The similarity of varied vehicle package is a critical design feature that affects method selection, optimized design and driver performance. However there is limited understanding of what constitutes similarity in package design and limited computer-based support to identify this feature in a layout model. This paper contributes a case-based framework for representing and reasoning about layout similarity that builds on domain-specific ontological modeling and case-based reasoning techniques. Validation study of the system provides evidence that the framework is general and enables a more efficient package layout design process.
Full Text Available We report a rare case of base of tongue tuberculosis following pulmonary tuberculosis. Patient presented to us with chief complaints of sore throat and pain on swallowing for period of 3 months. On examination with 70 degree telescope, we observed an ulcer on right side of base of tongue. The edges of the ulcer appeared to be undermined with whitish slough at the centre of the ulcer. Examination of neck showed a multiple small palpable middle deep cervical lymph nodes on right side of neck. Biopsy of the ulcer was taken, which showed granulomatous inflammation, suggestive of tuberculosis. Laboratory investigations revealed a raise in erythrocyte sedimentation rate, sputum for acid fast bacilli was strongly positive. Chest X ray was performed for patient showed multiple areas of consolidation. Patient was referred to chest clinic for further management of tuberculosis and was started on anti-tuberculous drugs. In conclusion tuberculosis of oral cavity is rare, but should be considered among one of the differential diagnosis of the oral lesions and biopsy is necessary to confirm the diagnosis.
Bergqvist, Tomas; Lithner, Johan
This paper presents a study of the opportunities presented to students that allow them to learn different types of mathematical reasoning during teachers' ordinary task solving presentations. The characteristics of algorithmic and creative reasoning that are seen in the presentations are analyzed. We find that most task solutions are based on…
Coyle, Lorcan; Cunningham, Padraig
Intelligent software assistants are becoming more common in the e-commerce domain. We are working on a personal travel assistant. The goal of this application is to use case based reasoning to assist the user in arranging flights. It offers personalised service to its users and automatically learns their travel preferences. It stores these preferences in a user model that is directly related to the CBR process. It learns the user preferences by exploiting user feedback on sets of ...
The common idea is to consider agents whose mental state comprises the three attitudes of belief、desire andintention. The relationships among these entities have received considerable attention. There still remains a large gapbetween theory and practice. In this paper, the authors implement a BDI agent system based on rule reasoning andshow the procedure of planning. The experiment shows the system can handle application problem.
Hackman CL; Knowlden AP
Christine L Hackman, Adam P KnowldenDepartment of Health Science, The University of Alabama, Tuscaloosa, AL, USABackground: Childhood obesity has reached epidemic proportions in many nations around the world. The theory of planned behavior (TPB) and the theory of reasoned action (TRA) have been used to successfully plan and evaluate numerous interventions for many different behaviors. The aim of this study was to systematically review and synthesize TPB and TRA-based dietary behavior interven...
Ali Khan-Jeihooni; Fatemeh Shahidi; Seyed Mansour Kashfi
Introduction: Cesarean section is considered as a major surgery accompanied by several complications. The present study aimed to determine the effect of educational intervention based on the theory of reasoned action to reduce the rate of cesarean section among pregnant women in Fasa, Southern Iran. Materials and Methods: This quasi-experimental study was performed on 100 (50 participants in each of the control and intervention groups) primiparous women in the third trimester of pregnancy...
周亮; 黄志球; 倪川
Ontology has a strong ability to express knowledge and has become a hot research topic in computer science currently. But on-tology has a weak ability in knowledge reasoning,which makes it a main bottleneck in spreading ontology technology. It will greatly im-prove the ability of reasoning by introducing Semantic Web Rule Language ( SWRL) into ontology,which can gain implicit knowledge. In this paper,introduce ontology into fault tree domain and study how to construct a FT domain ontology and SWRL. First,construct a FT domain ontology by Web Ontology Language. Second,transform the logical relationship among events of FT into SWRL. Finally,put these SWRL rules and the FT ontology into an inference engine JESS. Then new knowledge is produced and it is exploited for the rapid location of system faults. Through the experiment,it proves the correctness and effectiveness of proposed method.%本体具有较强的知识表达能力,目前已经成为计算机学科的一个研究热点。本体在知识推理方面的能力比较弱,已成为OWL技术推广应用的主要瓶颈。将语义Web规则语言( Semantic Web Rule Language,SWRL)引入到本体中,能大大改善本体的推理能力,从而挖掘出许多新的隐含知识。文中将本体引入到故障树领域中,对如何构建故障树本体及相应的SWRL规则进行了研究。首先采用OWL语言构建故障树领域本体,然后将故障树中事件之间的逻辑关系转化成SWRL规则语言,最后将故障树领域本体和SWRL规则放入JESS推理机中进行推理,能挖掘出故障树中的隐含知识,从而解决系统故障的快速定位。通过实验证明了文中提出方法的可行性和有效性。
This paper first puts forward a case-based system framework basedon data mining techniques. Then the paper examines the possibility of using neural n etworks as a method of retrieval in such a case-based system. In this system we propose data mining algorithms to discover case knowledge and other algorithms.
This paper outlines a new metasemantic theory of moral reason statements, focused on explaining how the reasons thus stated can be inescapable. The motivation for the theory is in part that it can explain this and other phenomena concerning moral reasons. The account also suggests a general recipe for explanations of conceptual features of moral reason statements.
Full Text Available Introduction: Cesarean section is considered as a major surgery accompanied by several complications. The present study aimed to determine the effect of educational intervention based on the theory of reasoned action to reduce the rate of cesarean section among pregnant women in Fasa, Southern Iran. Materials and Methods: This quasi-experimental study was performed on 100 (50 participants in each of the control and intervention groups primiparous women in the third trimester of pregnancy admitted to health centers of Fasa city, Fars province, Iran. The data-gathering tool was a multipart questionnaire containing demographic variables and the theory of reasoned action structures. After the pretest, the intervention group underwent exclusive training based on the theory of reasoned action. Then, after 3 months, both groups took part in the posttest. Data was analyzed by paired T-test, independent T-test and chi-square using SPSS-18 software. Results: A significant difference was found between the two groups regarding knowledge, evaluations behavioral outcomes, Behavioral beliefs and intention (P<0.001. Chi-square analysis showed a significant difference between the two groups regarding their performance (P<0.001. Conclusion: The present intervention was effective in increasing the pregnant women’s knowledge, evaluation of outcomes, attitude and strengthening their intention as well as performance. Therefore, it is suggested to use this model and other systematic straining for pregnant women to decrease the rate of cesarean section.
We analyse the philosopher Davidson's semantics of actions, using a strongly typed logic with contexts given by sets of partial equations between the outcomes of actions. This provides a perspicuous and elegant treatment of reasoning about action, analogous to Reiter's work on artificial intelligence. We define a sequent calculus for this logic, prove cut elimination, and give a semantics based on fibrations over partial cartesian categories: we give a structure theory for such fibrations. The existence of lax comma objects is necessary for the proof of cut elimination, and we give conditions on the domain fibration of a partial cartesian category for such comma objects to exist.
Maher, Carolyn A; Uptegrove, Elizabeth B
"Combinatorics and Reasoning: Representing, Justifying and Building Isomorphisms" is based on the accomplishments of a cohort group of learners from first grade through high school and beyond, concentrating on their work on a set of combinatorics tasks. By studying these students, the editors gain insight into the foundations of proof building, the tools and environments necessary to make connections, activities to extend and generalize combinatoric learning, and even explore implications of this learning on the undergraduate level. This volume underscores the power of attending to b
Maher, Carolyn A; Uptegrove, Elizabeth B
Combinatorics and Reasoning: Representing, Justifying and Building Isomorphisms is based on the accomplishments of a cohort group of learners from first grade through high school and beyond, concentrating on their work on a set of combinatorics tasks. By studying these students, the editors gain insight into the foundations of proof building, the tools and environments necessary to make connections, activities to extend and generalize combinatoric learning, and even explore implications of this learning on the undergraduate level. This volume underscores the power of attending to basic ideas i
Robarge, W. P.
Ammonia loss from fertilizers can impact formation of atmospheric aerosols, as well as contribute to nitrogen (N) deposition in terrestrial and aquatic ecosystems. Urea is the predominant form of N fertilizer used worldwide due to its high N content (46.6% N) and low cost. Once in contact with soil or vegetation, urea is hydrolyzed to ammonium via naturally occurring urease enzymes. Losses of N from surface applied urea as ammonia can exceed 30%. To address this issue, various physical and chemical mechanisms have been incorporated into granular urea. The most common approach is incorporation of urease inhibitors such as N-(n-butyl) thiophosphoric triamide (NBPT). We have been investigating ammonia volatilization from urea granules (+/- urease inhibitors) in various field and laboratory controlled experiments for the past several years. Laboratory experiments are conducted with a customized growth chamber system designed to continuously measure ammonia volatilization. Field measurements are conducted using a passive sampler technology with an acid-coated trap in PVC cylinders, or annular denuder technology using flow-through PVC chambers. Daily exchanges of acid-coated denuder tubes enhance the sensitivity of ammonia volatilization measurements for the urease-inhibitor treated product. Loss of N from commercial urea granules has ranged from 6 - ~ 35%, depending on ambient temperature. This loss typically occurs within the first 5-10 days under field conditions. Some urease-inhibitors can minimize loss of N via volatilization (crop yields or NUE, but the consistency of inhibitors incorporating NBPT suggest that these formulations represent a reasonable available control technology for use in agriculture to reduce ammonia emissions.
According to the acceptance of ICRP Publication 60 (1990), the dose equivalent limit for the boarder of controlled area will be defined as 1.3 mSv/3 months in the Regulation for the Enforcement of the Medical Service Law which is scheduled to be revised. The calculating methods of radiation shielding to be considered are as follows: The first method is calculating the dose equivalent for each nuclide using 3-month maximum estimated use dose. The second method is calculating the dose equivalent using 3-month maximum estimated use dose after the conversion of all nuclide dose into that of 131I. The third method is calculating the dose equivalent using 1 day maximum estimated use dose after the conversion of all nuclide dose into that of 131I. We've investigated which of methods can meet the new regulation value (1.3 mSv/3 months). In modeled facility, we've tried to calculate the dose by the first method to confirm if we can perform the reasonable control in safe. Total dose equivalent for the boarder of controlled area (B) was 883 μSv/3 months by the first method, and its value turned out to be about 1/4 of that of the third method. Only the result by the first method was found to be within the confines of new dose equivalent limit of 1.3 mSv/3 months. The results of both method the second and the third were found to be within the confines of existing dose equivalent limit. The method as to calculate the shielding for each nuclide by using 3-month maximum estimated use dose has been accepted in the Law Concerning Prevention from Radiation Hazards due to Radioisotopes, etc. As the method is practically in accordance with the current use of radioisotope in nuclear medicine facility, the possibility of it coping with the new dose equivalent limit was indicated. (author)
Günther Rolf W
Full Text Available Abstract Background Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. Methods We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii Case-based reasoning (CBR parallels the human problem-solving process; (iii Content-based image retrieval (CBIR can be useful for computer-aided diagnosis (CAD. To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE. The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL. In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. Results We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i the IRMA core, i.e., the IRMA CBIR engine; and (ii the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM and Health Level Seven (HL7. Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. Conclusions The IBCR-RE paradigm
Stereotypical reasoning assumes that the situation at hand is one of a kind and that it enjoys the properties generally associated with that kind of situation. It is one of the most basic forms of nonmonotonic reasoning. A formal model for stereotypical reasoning is proposed and the logical properties of this form of reasoning are studied. Stereotypical reasoning is shown to be cumulative under weak assumptions.
Full Text Available A web-based remote customization platform is developed for hardware product in this paper. To realize the rapid product customization, a case-based reasoning approach based on fuzzy set is put forward. To retrieve the most similar case from the case base, a parabola membership function is constructed based on the fuzzy set, and synthesis weights are introduced by combining subjective weights with objective weights which are calculated based on the deviation information of similarity. Then the model for solving cases' global similarity is set up based on synthesis weights. To improve the accuracy of the similarity measurement, center distance revision method based on area is presented for the Bi-interval type which is one of fuzzy numeric attribute. Implementation example applying above methods is given in the area of electric drill customization. Results show that the presented approach helps to improve the accuracy of the similarity of the case product, and reduce the time and cost of product design process
Full Text Available ABSTRACT In todays world software testing with statistical fault localization technique is one of most tedious expensive and time consuming activity. In faulty program a program element contrast dynamic spectra that estimate location of fault. There may have negative impact from coincidental correctness with these technique because in non failed run the fault can also be triggered out and if so disturb the assessment of fault location. Now eliminating of confounding rules on the recognizing the accuracy. In this paper coincidental correctness which is an effective interface is the reason of success of fault location. We can find out fault predicates by distribution overlapping of dynamic spectrum in failed runs and non failed runs and slacken the area by referencing the inter class distances of spectra to clamp the less suspicious candidate. After that we apply coverage matrix base reduction approach to reduce the test cases of that program and locate the fault in that program. Finally empirical result shows that our technique outshine with previous existing predicate based fault localization technique with test case reduction.
尹文君; 刘民; 吴澄
Knowledge plays an active role in job-shop scheduling,especially in dynamic environments.A novel case-based immune framework was developed for static and dynamic job-shop problems,using the associative memory and knowledge reuse from case-based reasoning (CBR) and immune response mechanisms.A 2-level similarity index which combines both job routing and problem solution characteristics based on DNA matching ideas was defined for both the CBR and immune algorithms.A CBR-embedded immune algorithms (CBR-IAs) framework was then developed focusing on case retrieval and adaptation methods.In static environments,the CBR-IAs have excellent population diversity and fast convergence which are necessary for dynamic problems with jobs arriving and leaving continually.The results with dynamic scheduling problems further confirm the CBR-IAs effectiveness as a problem solving method with knowledge reuse.
He, Wu; Yuan, Xiaohong; Yang, Li
Case-based learning has been widely used in many disciplines. As an effective pedagogical method, case-based learning is also being used to support teaching and learning in the domain of information security. In this paper, we demonstrate case-based learning in information security by sharing our experiences in using a case study to teach security…
This paper deals with bases in a finite-dimensional Hilbert space. Such a space can be realized as a subspace of the representation space of SU2 corresponding to an irreducible representation of SU2. The representation theory of SU2 is reconsidered via the use of two truncated deformed oscillators. This leads to replace the familiar scheme [j2, jz] by a scheme [j2, vra], where the two-parameter operator vra is defined in the universal enveloping algebra of the Lie algebra su2. The eigenvectors of the commuting set of operators [j2, vra] are adapted to a tower of chains SO3 includes C2j+1 (2j belongs to N*), where C2j+1 is the cyclic group of order 2j + 1. In the case where 2j + 1 is prime, the corresponding eigenvectors generate a complete set of mutually unbiased bases. Some useful relations on generalized quadratic Gauss sums are exposed in three appendices. (authors)
Full Text Available Present paper continues the researches on cognitive system design. The goal ofthe paper is to illustrate the variety of models which can be constructed using the Bayesianplausible reasoning theory. The first case study develops a classical inverse kinematicalmodel into a Bayesian model. The second case study models the human reasoningpresented by the famous story of Sun Tzu: ‘Advance to Chengang by a hidden path’.
陶倩; 马刚; 史忠植
针对传统专家系统推理模型结构在知识获取方面适应性差的现状，从系统科学的视角，运用复杂适应系统理论，对传统专家系统的结构及运行机制进行了改进。引入 Agent 来模拟人脑中的神经元，用来承载专家系统中相互作用的知识，然后，基于 Multi-Agent 之间的相互作用来构建复杂适应的专家系统推理模型。从而，将专家系统中的知识获取机制、知识库、推理机三者统一于由 Multi-Agent 进行相互作用的复杂适应系统之中。通过设计体育赛事申办决策专家系统的原型，进行了专家系统推理模型的验证。原型运行结果表明：基于 Multi-Agent 的专家系统推理模型结构能够有效地提高专家系统知识获取的适应性。这为研究更加接近人脑智能的专家系统提供了崭新的研究思路。%The traditional expert system reasoning model structure has poor adaptability in acquiring knowledge . From the viewpoint of system science, the complex adaptive system theory is used to improve the structure and oper -ation mechanism of a traditional expert system .Firstly, an Agent was introduced to simulate neurons in the human brain and load the knowledge interacting in the expert system reasoning model .Then an expert system reasoning model of complex adaptation was constructed based on the Multi -Agent interaction.Consequently, the knowledge acquiring mechanism, knowledge base and reasoning engine were unified into the Agents interaction in the complex adaptive expert system.Finally, by designing the expert system reasoning model prototype in decision -making of in-ternational sporting events bidding , the effectiveness of the expert system reasoning model based on Agent was veri -fied.The results of the prototype running show that the expert system reasoning structure based on Multi -Agent model can effectively improve the adaptability of expert system knowledge acquisition .That
Evidence Theory used in calculating the uncertain metrics of the uncertain events is developed based on probability theory. And the organization goals describe the future states of an enterprise during some time so that the possibility of one goal satisfied is evaluated with some uncertainty which is accorded with the uncertain evaluating method in evidence theory. In this article, evidence theory is employed to formulate the organization goals and to define a reasoning method with goals. With goal model built reasoning is done according to the automatic reasoning algorithm in which only uncertain metric of some goals is needed.%目标建模是早期信息系统需求分析的关键技术.针对企业高层目标难以评估的问题,提出一种企业目标量化建模方法,以证据理论作为逻辑基础,对企业目标可满足性进行定量表征,借助Dempster证据合成法则,设计多目标贡献关系合算法,通过实验验证方法的有效性.
Edgar Abarca López
Full Text Available This paper presents a case report of thanatophoric displasia diagnosed in the prenatal period using ultrasound standards. The course of the case pregnancy, birth process, and postnatal period is described. This report invites bioethical analysis using its principles, appealing to human dignity, diversity and otherness, particularly in the mother-child dyad and their family. An early diagnosis allows parental support as they face the course of this condition and its potentially fatal outcome.
Edgar Abarca López; Alejandra Rodríguez Torres; Donovan Casas Patiño; Esteban Espíndola Benítez
This paper presents a case report of thanatophoric displasia diagnosed in the prenatal period using ultrasound standards. The course of the case pregnancy, birth process, and postnatal period is described. This report invites bioethical analysis using its principles, appealing to human dignity, diversity and otherness, particularly in the mother-child dyad and their family. An early diagnosis allows parental support as they face the course of this condition and its potentially fatal outcome.
Settels, Volker; Schubert, Alexander; Tafipolski, Maxim; Liu, Wenlan; Stehr, Vera; Topczak, Anna K; Pflaum, Jens; Deibel, Carsten; Fink, Reinhold F; Engel, Volker; Engels, Bernd
The exciton diffusion length (LD) is a key parameter for the efficiency of organic optoelectronic devices. Its limitation to the nm length scale causes the need of complex bulk-heterojunction solar cells incorporating difficulties in long-term stability and reproducibility. A comprehensive model providing an atomistic understanding of processes that limit exciton trasport is therefore highly desirable and will be proposed here for perylene-based materials. Our model is based on simulations with a hybrid approach which combines high-level ab initio computations for the part of the system directly involved in the described processes with a force field to include environmental effects. The adequacy of the model is shown by detailed comparison with available experimental results. The model indicates that the short exciton diffusion lengths of α-perylene tetracarboxylicdianhydride (PTCDA) are due to ultrafast relaxation processes of the optical excitation via intermolecular motions leading to a state from which further exciton diffusion is hampered. As the efficiency of this mechanism depends strongly on molecular arrangement and environment, the model explains the strong dependence of LD on the morphology of the materials, for example, the differences between α-PTCDA and diindenoperylene. Our findings indicate how relaxation processes can be diminished in perylene-based materials. This model can be generalized to other organic compounds. PMID:24909402
李韧; 杨丹; 胡海波; 谢娟; 吴云松; 傅鹂
With the explosion of semantic web technologies, large amounts of OWL ontologies are common place. Conventional rule engines inevitably meet the bottleneck of computing performance and scalability. A cloud computing based SWRL distributed reasoning framework named CloudSWRL is proposed. Based on the Hadoop open-source framework and SWRL semantics, the storage schema for OWL ontologies is designed to implement efficient data retrieving from HBase. Some novel data models for SWRL rules and intermediate data are defined. At last, a MapReduce paradigm based distributed SWRL reasoning algorithm is proposed under DL-safe restriction. An experiment on a simulation environment shows our framework is more efficient and scalable than conventional rule engines when reasoning over large-scale of OWL data.%为解决传统推理引擎在进行大规模OWL本体数据的SWRL规则推理时存在的计算性能和可扩展性不足等问题,提出了云计算环境下的SWRL规则分布式推理框架CloudSWRL.根据SWRL规则语义,并以Hadoop开源云计算框架为基础,设计了OWL本体在HBase分布式数据库中的存储策略,定义了SWRL规则解析模型和相关推理中间数据模型,提出了在DL-safe限制下基于MapReduce的SWRL规则分布式推理算法.实验结果表明,在对大规模OWL本体进行SWRL规则推理时,CloudSWRL框架在计算性能和可扩展性方面均优于传统推理引擎.
Dantley, Scott Jackson
This study investigated the effects of inquiry-based technology-enhanced, laboratories with the use of Microcomputer Based Laboratory (MBL) activities on graphing skills, content knowledge, science reasoning skills, and attitudes of introductory general chemistry community college students. The study employed a quasi-experimental pretest posttest comparison and treatment group design. The treatment group received a MBL technology. Inquiry-based laboratory activities were used for each. Four major research questions were explored in my study. The following instruments were used: the Modified Lawson Test of Scientific Reasoning; the Test of Graphing in Science (TOGS); the modified laboratory instrument ("Behavior of Gases" and "Lights, Color and Absorption" with accompanies content questions, validated by a panel of chemists, as well as an attitude survey. Mean scores from the Lawson, TOGS, Behavior of Gases and Lights, Color and Absorption labs, content knowledge questions were analyzed using t-tests to determine if a statistical significance exists between their mean scores. Basic statistics were used to analyze the attitude survey. The results from the Lawson revealed that students' mean score performance were not statistically significant between treatment and comparison groups. The t-test results indicated that each group had similar reasoning ability. The TOGS t-test results revealed that the mean scores were not statistically significant between each group. The results suggest that each group had similar graphing abilities. However, significant differences in the mean scores were found on their performance for the "Behavior of Gases" and "Lights, Color and Absorption" laboratories. Conducting a follow-up assessment of content knowledge for Behavior of Gases and Lights, Color and Absorption, revealed that no statistically significant difference exists on their mean scores, suggesting that though treatment students' performance was improved in the laboratory by
My thesis research has focused broadly on how the environment shapes the structure and function of prefrontal cortex, for better or worse. I am interested in understanding in how experience-dependent plasticity can be harnessed to boost, or in some cases, remediate prefrontal function. I focused on training reasoning, the ability to solve novel problems, for two reasons: 1) reasoning is highly predictive of academic outcomes, and 2) reasoning was originally conceptualized as a fixed trait, an...
This article mainly presents the phenomenon of results of acquiring different language in China as a Korean student. Obvi-ously, the acquiring of Chinese is much easier in China. Moreover, it puts forward reasons of dif-ferent languages’ effects, which are attitude, motivation between Chinese and English.
Khan, Steven; Francis, Krista; Davis, Brent
As we witness a push toward studying spatial reasoning as a principal component of mathematical competency and instruction in the twenty first century, we argue that enactivism, with its strong and explicit foci on the coupling of organism and environment, action as cognition, and sensory motor coordination provides an inclusive, expansive, apt,…
Moss, Joan; Hawes, Zachary; Naqvi, Sarah; Caswell, Beverly
Increased efforts are needed to meet the demand for high quality mathematics in early years classrooms. Despite the foundational role of geometry and spatial reasoning for later mathematics success, the strand receives inadequate instructional time and is limited to concepts of static geometry. Moreover, early years teachers typically lack both…
Coates, Daniel Justin
In this dissertation I develop a theory of practical reasons as such, and then I extend that theory to specifically moral reasons. According to the theory of practical reasons that I develop in Part I, the existence and weight of an agent's reason to act in a particular way depends on an agent's motivational states--specifically those motivational states issuing from practical orientations that play some role in structuring the agent's practical identity. I then argue that this account of p...
Markovits, Henry; Thompson, Valerie A; Brisson, Janie
The nature of people's meta-representations of deductive reasoning is critical to understanding how people control their own reasoning processes. We conducted two studies to examine whether people have a metacognitive representation of abstract validity and whether familiarity alone acts as a separate metacognitive cue. In Study 1, participants were asked to make a series of (1) abstract conditional inferences, (2) concrete conditional inferences with premises having many potential alternative antecedents and thus specifically conducive to the production of responses consistent with conditional logic, or (3) concrete problems with premises having relatively few potential alternative antecedents. Participants gave confidence ratings after each inference. Results show that confidence ratings were positively correlated with logical performance on abstract problems and concrete problems with many potential alternatives, but not with concrete problems with content less conducive to normative responses. Confidence ratings were higher with few alternatives than for abstract content. Study 2 used a generation of contrary-to-fact alternatives task to improve levels of abstract logical performance. The resulting increase in logical performance was mirrored by increases in mean confidence ratings. Results provide evidence for a metacognitive representation based on logical validity, and show that familiarity acts as a separate metacognitive cue. PMID:25416026
McHugh, Conor; Way, Jonathan
Among the many important contributions of John Broome’s Rationality Through Reasoning is an account of what reasoning is and what makes reasoning correct. In this paper we raise some problems for both of these accounts and recommend an alternative approach.
Vladyková, Petra; Rode, Carsten
A passive house is a highly insulated building with an efficient ventilation system with heat recovery providing heating and good indoor climate. A passive house utilises the solar and internal gains in an effective way. And the heating with fresh air provided by a ventilation system does not req...... use in the Arctic. Through the adaptation of a passive house to the Arctic climate by modification of the building, the optimal energy-efficient house for the Arctic is found.......A passive house is a highly insulated building with an efficient ventilation system with heat recovery providing heating and good indoor climate. A passive house utilises the solar and internal gains in an effective way. And the heating with fresh air provided by a ventilation system does not...... require a conventional hydronic heating system. The passive house concept has been successfully implemented in latitudes 40° to 60°, mainly in German-speaking countries, in Europe, and in Scandinavia. The most interesting locations for a passive house in the Arctic regions are selected based on cross...
Argues the importance of presenting ethics and communication as twin concepts in the management communication class. Presents two cases useful in the classroom that address two contemporary issues (harassment in the workplace and the consumption of alcohol by pregnant women) that have implications for business professionals and allow students to…
Bohøj, Morten; Bouvin, Niels Olof
We explore in this paper using timelines to represent bureaucratic processes in a municipal setting. The system described herein enables citizens and case workers to collaborate over the application for and configuration of parental leave, which is a highly involved process under Danish law....
Khemlani, Sangeet S.; Barbey, Aron K.; Johnson-Laird, Philip N
This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews e...
孙文舟; 岳冬梅; 石晨光; 彭亮
针对故障诊断领域知识异构和故障机理复杂的问题，提出基于灰色理论的本体模型。利用SWRL规则和推理引擎在本体模型中实现灰色关联度的表达及其联接故障现象和故障原因的作用。在基于灰色理论的故障诊断本体推理机制框架下，建立了液压系统的故障诊断灰色本体模型。实例验证，该方法诊断效果良好。%Against the main problem of semantic heterogeneity and complicated fault mechanism ,ontology model for fault diagnosis based on grey theory is mentioned .By means of SWRL rules and inference engine ,the representation of grey correlation implement the connection between fault phenomenon and fault reason in the ontology model .In the framework of ontology reasoning mechanism for fault diagnosis based on grey theory ,an ontology model for hydraulic system is built .The case study show s that result is satisfied .
Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the velocity is big and the distance from the object is small, hit the brakes and decelerate as fast as possible' into an actual control. To apply this transformation, one must choose appropriate methods for reasoning with uncertainty, i.e., one must: (1) choose the representation for words like 'small', 'big'; (2) choose operations corresponding to 'and' and 'or'; (3) choose a method that transforms the resulting uncertain control recommendations into a precise control strategy. The wrong choice can drastically affect the quality of the resulting control, so the problem of choosing the right procedure is very important. From a mathematical viewpoint these choice problems correspond to non-linear optimization and are therefore extremely difficult. In this project, a new mathematical formalism (based on group theory) is developed that allows us to solve the problem of optimal choice and thus: (1) explain why the existing choices are really the best (in some situations); (2) explain a rather mysterious fact that fuzzy control (i.e., control based on the experts' knowledge) is often better than the control by these same experts; and (3) give choice recommendations for the cases when traditional choices do not work.
Full Text Available Abstract Objective Prior to 2007, forced sex with male children in South Africa did not count as rape but as "indecent assault", a much less serious offence. This study sought to document prevalence of male sexual violence among school-going youth. Design A facilitated self-administered questionnaire in nine of the 11 official languages in a stratified (province/metro/urban/rural last stage random national sample. Setting Teams visited 5162 classes in 1191 schools, in October and November 2002. Participants A total of 269,705 learners aged 10–19 years in grades 6–11. Of these, 126,696 were male. Main outcome measures Schoolchildren answered questions about exposure in the last year to insults, beating, unwanted touching and forced sex. They indicated the sex of the perpetrator, and whether this was a family member, a fellow schoolchild, a teacher or another adult. Respondents also gave the age when they first suffered forced sex and when they first had consensual sex. Results Some 9% (weighted value based on 13915/127097 of male respondents aged 11–19 years reported forced sex in the last year. Of those aged 18 years at the time of the survey, 44% (weighted value of 5385/11450 said they had been forced to have sex in their lives and 50% reported consensual sex. Perpetrators were most frequently an adult not from their own family, followed closely in frequency by other schoolchildren. Some 32% said the perpetrator was male, 41% said she was female and 27% said they had been forced to have sex by both male and female perpetrators. Male abuse of schoolboys was more common in rural areas while female perpetration was more an urban phenomenon. Conclusion This study uncovers endemic sexual abuse of male children that was suspected but hitherto only poorly documented. Legal recognition of the criminality of rape of male children is a first step. The next steps include serious investment in supporting male victims of abuse, and in prevention of
Smith, Janet C.; Diaz, Ricardo
Case study-based teacher education has been advocated since the mid-1980s. The evolution of technology-facilitated, case study-based professional development for adult education professionals may be traced by examining three projects involving the National Center on Adult Literacy and the International Literacy Institute at University of…
Venglar, Mollie; Theall, Michael
Physical therapist students often think ethics content to be less relevant than other course material. The purpose of this study was to assess whether changing from lecture to case-based method, would impact ethics awareness and integration. In focus groups, students in the case-based course reported greater perceived value of the ethics content…
Hakkarainen, Paivi; Saarelainen, Tarja; Ruokamo, Heli
This paper reports an action research case study in which a traditional lecture based, face to face "Network Management" course at the University of Lapland's Faculty of Social Sciences was developed into two different course versions resorting to case based teaching: a face to face version and an online version. In the face to face version, the…
Learning physics requires understanding the applicability of fundamental principles in a variety of contexts that share deep features. One way to help students learn physics is via analogical reasoning. Students can be taught to make an analogy between situations that are more familiar or easier to understand and another situation where the same physics principle is involved but that is more difficult to handle. Here, we examine introductory physics students' ability to use analogies in solving problems involving Newton's second law. Students enrolled in an algebra-based introductory physics course were given a solved problem involving tension in a rope and were then asked to solve another problem for which the physics is very similar but involved a frictional force. They were asked to point out the similarities between the two problems and then use the analogy to solve the friction problem.
Jakob, Michal; Pěchouček, Michal; Chábera, Jiří; Miles, Simon; Luck, Michael; Oren, Nir; Kollingbaum, Martin; Holt, Camden; Vazquez, Javier; Storms, Patrick; Dehn, Martin
Of the ways in which agent behaviour can be regulated in a multi-agent system, electronic contracting - based on explicit representation of different parties' responsibilities, and the agreement of all parties to them - has significant potential for modern industrial applications. Based on this assumption, the CONTRACT project aims to develop and apply electronic contracting and contract-based monitoring and verification techniques in real world applications. This paper presents results from ...
In this paper, we draw insights from resource-based theory, institutional theory, and Bourdieu’s concepts of cultural consecration and symbolic capital to propose a concept of Institution-Based Resource (IBR) as a novel source of sustainable competitive advantage. We define an IBR as a valuable and symbolic resource that is consecrated and institutionalized by legitimate consecrating institutions, granted to or attained by individuals and/or firms based on each institution’s merit system, and...
Pedrosa, Alex; Näslund, Dag; Jasmand, Claudia
analysis of 134 case study based articles published in six leading logistics and supply chain management (SCM) journals between 1998 and 2010 is used to assess and evaluate the quality of the case study based research approach as documented in these publications. Findings – This research provides an...... overview of the quality of the case study based research approach. Results show that the quality is generally low, supporting the ongoing, but empirically unsupported criticism on the quality of case study based research. The results also highlight which specific aspects authors and reviewers need to...... address to ensure high quality of the case study based research approach in published articles. Research limitations/implications – This study is limited to the analysis of published articles in six logistics and SCM journals. Further research should investigate different journals in logistics and other...
Cohn, Ellen S; Coster, Wendy J; Kramer, Jessica M
We describe an integrated master of science in occupational therapy curriculum and a coordinated sequence of evidence-based practice (EBP) courses that incorporate systematic, pragmatic teaching strategies to develop students' EBP skills and habits of reasoning. The EBP courses focus sequentially on the occupational lives of clients and methods for gaining information about occupational performance and needs; appraising the internal, external, and statistical validity of intervention evidence; and generating evidence from one's own practice to answer questions about individual or group client outcomes. All EBP courses use facilitated learning processes that encourage graduate students to take responsibility for their own learning, guided by a carefully structured series of assignments. The integrated curriculum scaffolds the translation and application of previously learned knowledge and skills, including EBP knowledge, into different contexts. Student survey data suggest that graduating students view EBP as an integral part of the clinical process and begin to internalize the habits necessary to be evidence-based practitioners. PMID:25397942
Bench-Capon, Trevor; Prakken, Henry; Sartor, Giovanni
A popular view of what Artificial Intelligence can do for lawyers is that it can do no more than deduce the consequences from a precisely stated set of facts and legal rules. This immediately makes many lawyers sceptical about the usefulness of such systems: this mechanical approach seems to leave out most of what is important in legal reasoning. A case does not appear as a set of facts, but rather as a story told by a client. For example, a man may come to his lawyer saying that he had developed an innovative product while working for Company A. Now Company B has made him an offer of a job, to develop a similar product for them. Can he do this? The lawyer firstly must interpret this story, in the context, so that it can be made to fit the framework of applicable law. Several interpretations may be possible. In our example it could be seen as being governed by his contract of employment, or as an issue in Trade Secrets law.
S. W. Loke
Full Text Available Context-aware smart things are capable of computational behaviour based on sensing the physical world, inferring context from the sensed data, and acting on the sensed context. A collection of such things can form what we call a thing-ensemble, when they have the ability to communicate with one another (over a short range network such as Bluetooth, or the Internet, i.e. the Internet of Things (IoT concept, sense each other, and when each of them might play certain roles with respect to each other. Each smart thing in a thing-ensemble might have its own context-aware behaviours which when integrated with other smart things yield behaviours that are not straightforward to reason with. We present Sigma, a language of operators, inspired from modular logic programming, for specifying and reasoning with combined behaviours among smart things in a thing-ensemble. We show numerous examples of the use of Sigma for describing a range of behaviours over a diverse range of thing-ensembles, from sensor networks to smart digital frames, demonstrating the versatility of our approach. We contend that our operator approach abstracts away low-level communication and protocol details, and allows systems of context-aware things to be designed and built in a compositional and incremental manner.
Mathematical learning environments help students in mastering mathematical knowledge. Mature environments typically offer thousands of interactive exercises. Providing feedback to students solving interactive exercises requires domain reasoners for doing the exercise-specific calculations. Since a domain reasoner has to solve an exercise in the same way a student should solve it, the structure of domain reasoners should follow the layered structure of the mathematical domains. Furthermore, learners, teachers, and environment builders have different requirements for adapting domain reasoners, such as providing more details, disallowing or enforcing certain solutions, and combining multiple mathematical domains in a new domain. In previous work we have shown how domain reasoners for solving interactive exercises can be expressed in terms of rewrite strategies, rewrite rules, and views. This paper shows how users can adapt and configure such domain reasoners to their own needs. This is achieved by enabling users...
Full Text Available Abstract Background Priority setting for artemisinin-based antimalarial drugs has become an integral part of malaria treatment policy change in malaria-endemic countries. Although these drugs are more efficacious, they are also more costly than the failing drugs. When Tanzania changed its National Malaria Treatment Policy in 2006, priority setting was an inevitable challenge. Artemether-lumefantrine was prioritised as the first-line drug for the management of uncomplicated malaria to be available at a subsidized price at public and faith-based healthcare facilities. Methods This paper describes the priority-setting process, which involved the selection of a new first-line antimalarial drug in the implementation of artemisinin-based combination therapy policy. These descriptions were further evaluated against the four conditions of the accountability for reasonableness framework. According to this framework, fair decisions must satisfy a set of publicity, relevance, appeals, and revision and enforcement conditions. In-depth interviews were held with key informants using pretested interview guides, supplemented with a review of the treatment guideline. Purposeful sampling was used in order to explore the perceptions of people with different backgrounds and perspectives. The analysis followed an editing organising style. Results Publicity: The selection decision of artemether-lumefantrine but not the rationale behind it was publicised through radio, television, and newspaper channels in the national language, Swahili. Relevance: The decision was grounded on evidences of clinical efficacy, safety, affordability, and formulation profile. Stakeholders were not adequately involved. There was neither an appeals mechanism to challenge the decision nor enforcement mechanisms to guarantee fairness of the decision outcomes. Conclusions The priority-setting decision to use artemether-lumefantrine as the first-line antimalarial drug failed to satisfy the four
This paper reviews the psychological investigation of reasoning with conditionals, putting an emphasis on recent work. In the first part, a few methodological remarks are presented. In the second part, the main theories of deductive reasoning (mental rules, mental models, and the probabilistic approach) are considered in turn; their content is summarised and the semantics they assume for if and the way they explain formal conditional reasoning are discussed, in particular in the light of expe...
Fletcher, Logan; Carruthers, Peter
This article considers the cognitive architecture of human meta-reasoning: that is, metacognition concerning one's own reasoning and decision-making. The view we defend is that meta-reasoning is a cobbled-together skill comprising diverse self-management strategies acquired through individual and cultural learning. These approximate the monitoring-and-control functions of a postulated adaptive system for metacognition by recruiting mechanisms that were designed for quite other purposes.
By the similarity between the syllogism in logic and a path proposition in graph theory,a new concept,fuzzy reasoning graph G has been given in this paper. Transitive closure has been studied and used to do reasoning related to self-loop in G,and an algorithm has been designed to cope with reasoning in other cycles in G. Both approaches are applicable and efficient.
Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e., set of individuals with common properties. The experience in using DLs in applications has shown that in many cases we would like to extend their capabilities. In particular, their use in the context of Multimedia Information Retrieval (MIR) leads to the convincement that such DLs should allow the treatment of the inherent imprecision in multimedia object content representation and retrieval. In this paper we will present a fuzzy extension of ALC, combining Zadeh's fuzzy logic with a classical DL. In particular, concepts becomes fuzzy and, thus, reasoning about imprecise concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.
Cramer-Petersen, Claus Lundgaard; Ahmed-Kristensen, Saeema
Reasoning is at the core of design activity and thinking. Thus, understanding and explaining reasoning in design is fundamental to understand and support design practice. This paper investigates reasoning in design and its relationship to varying foci at the stage of idea generation and subsequent...... investigate idea generation sessions of two industry cases. Reasoning was found to appear in sequences of alternating reasoning types where the initiating reasoning type was decisive. The study found that abductive reasoning led to more radical ideas, whereas deductive reasoning led to ideas being for project...... requirements, but having a higher proportion being rejected as not valuable. The study sheds light on the conditions that promote these reasoning types. The study is one of the first of its kind and advances an understanding of reasoning in design by empirical means and suggests a relationship between...
D'Aquin, Mathieu; Lieber, Jean; Napoli, Amedeo
Kasimir is a case-based decision support system in the domain of breast cancer treatment. For this system, a problem is given by the description of a patient and a solution is a set of therapeutic decisions. Given a target problem, Kasimir provides several suggestions of solutions, based on several justified adaptations of source cases. Such adaptation processes are based on adaptation knowledge. The acquisition of this kind of knowledge from experts is presented in this paper. It is shown ho...
Hastarini Dwi Atmani
Full Text Available In this time, teacher centered learning is a methods in part of higher education in Indonsia. This method, students passively receive information.Case base learning is an instructional design model that is a variant of project oriented learning. Cases are factually-based, complex problems written to stimulate classroom discussion and collaborative analysis. This one, students construct knowledge through gathering and synthesizing information and integrating it with the general skills of inquiry, communication, critical thinking, and problem solving. Key words : active learning, case base learning.
Full Text Available Testing is an integral part of any software development lifecycle. It takes considerable amount of time and capital to generate test cases and apply testing. Genetic Algorithms are proving to be great tool in optimizing software testing. This paper uses the concept of Genetic algorithms in optimizing software testing. In this paper, we have analysed genetic algorithms and studied their effectiveness to find the faults and time overhead-based criteria to -prioritize test cases. The proposed approach is providing the solution of test cases sequencing as well as reduction by using an intelligent dynamic approach. The proposed system will generate the test cases based on the priorities, which are assigned by the algorithm to test cases on the basis of some intelligent operations. A cumulative mutation probability (CMP metric is used to determine the effectiveness of the new test case orderings
Riveros Rotge, Hector G.
The objective of Physics courses is that the students learn how to use what they know to solve problems in the real world (competencies), but no one learns to do that seeing as the professor think in the blackboard. The program of a course uses topics as examples of reasoning. Reasoning involves the ability to use their knowledge. If we precisely…
In this paper we discuss the role of emotions in artificial agent design, and the use of logic in reasoning about the emotional or affective states an agent can reside in. We do so by extending the KARO framework for reasoning about rational agents appropriately. In particular we formalize in this f
Karahan, Engin; Roehrig, Gillian
Research in socioscientific issue (SSI)-based interventions is relatively new (Sadler in Journal of Research in Science Teaching 41:513-536, 2004; Zeidler et al. in Journal of Research in Science Teaching 46:74-101, 2009), and there is a need for understanding more about the effects of SSI-based learning environments (Sadler in Journal of Research in Science Teaching 41:513-536, 2004). Lee and Witz (International Journal of Science Education 31:931-960, 2009) highlighted the need for detailed case studies that would focus on how students respond to teachers' practices of teaching SSI. This study presents case studies that investigated the development of secondary school students' science understanding and their socioscientific reasoning within SSI-based learning environments. A multiple case study with embedded units of analysis was implemented for this research because of the contextual differences for each case. The findings of the study revealed that students' understanding of science, including scientific method, social and cultural influences on science, and scientific bias, was strongly influenced by their experiences in SSI-based learning environments. Furthermore, multidimensional SSI-based science classes resulted in students having multiple reasoning modes, such as ethical and economic reasoning, compared to data-driven SSI-based science classes. In addition to portraying how participants presented complexity, perspectives, inquiry, and skepticism as aspects of socioscientific reasoning (Sadler et al. in Research in Science Education 37:371-391, 2007), this study proposes the inclusion of three additional aspects for the socioscientific reasoning theoretical construct: (1) identification of social domains affecting the SSI, (2) using cost and benefit analysis for evaluation of claims, and (3) understanding that SSIs and scientific studies around them are context-bound.
Full Text Available Presented study shows that considerable reserves still exist for increasing the service times (lifetimes of CrN – coated dies for Al hot extrusion. The main reasons for the decreased service times are revealed and explained regarding the selected CrN - coated die for hot extrusion, i.e. why the service time of the coated-die is not in accordance with the wear resistance of the CrN - coating. The shaping of the bearing surface and presence of the scratches, size and amount of nonmetalic inclusions in the die steel, nodular defects in the CrN - coating, as well as thicknesses uniformity of CrN - coatings along the bearing surface, are relevant influential parameters.
Clark, Glenn T.; And Others
The use of interactive computer-based simulation of cases of chronic orofacial pain and temporomandibular joint disfunction patients for clinical dental education is described. Its application as a voluntary study aid in a third-year dental course is evaluated for effectiveness and for time factors in case completion. (MSE)
Engel, Francoise E.; Hendricson, William D.
A case-based, student-centered instructional model designed to mimic orthodontic problem solving and decision making in dental general practice is described. Small groups of students analyze case data, then record and discuss their diagnoses and treatments. Students and instructors rated the seminars positively, and students reported improved…
Politzer, Guy; Bourmaud, Gaëtan
This paper begins with a review of the literature on plausible reasoning with deductive arguments containing a conditional premise. There is concurring evidence that people presented with valid conditional arguments such as Modus Ponens and Modus Tollens generally do not endorse the conclusion, but rather find it uncertain, in case (i) the plausibility of the major conditional premise is debatable, (ii) the major conditional premise is formulated in frequentist or probabilistic terms, or (iii...
The focus of this research is in the area of Supply Chain Collaboration (SCC). More precisely we studied the TeleCom Installation Services supply chain in the case company Digita Oy. Our goal was to identify the key elements to be considered when pursuing towards SCC; highlight the development areas in Supply Chain Management (SCM) in the case company; study how the SCC efforts can improve SCM in the case company; and construct a Collaboration Based SCM Framework for the case company. Overall...
Dolan, Erin; Grady, Julia
Teaching by inquiry is touted for its potential to encourage students to reason scientifically. Yet, even when inquiry teaching is practiced, complexity of students' reasoning may be limited or unbalanced. We describe an analytic tool for recognizing when students are engaged in complex reasoning during inquiry teaching. Using classrooms that represented “best case scenarios” for inquiry teaching, we adapted and applied a matrix to categorize the complexity of students' reasoning. Our results...
Oldager, Steen Nikolaj
One of the main areas in knowledge representation and logic-based artificial intelligence concerns logical formalisms that can be used for representing and reasoning with concepts. For almost 30 years, since research in this area began, the issue of intensionality has had a special status in that...
Sunstein, Cass Robert
Can computers, or artificial intelligence, reason by analogy? This essay urges that they cannot, because they are unable to engage in the crucial task of identifying the normative principle that links or separates cases. Current claims, about the ability of artificial intelligence to reason analogically, rest on an inadequate picture of what legal reasoning actually is. For the most part, artificial intelligence now operates as a kind of advanced version of LEXIS, offering research assistance...