Information extraction from clinical and radiology notes for liver cancer staging

Thesis (Ph.D.)--University of Washington, 2016-06

Does industry matter? Examining the role of industry structure and organizational learning in innovation and brand performance

A manager's perception of industry structure (dynamism) has the potential to impact various organizational strategies and behaviors. This may be particularly so with regard to perceptions driving organizational learning orientations and innovation based marketing strategy. The position taken here suggests that firms operating within a competitive industry tend to pursue innovative ways of performing value-creating activities, which requires the development of learning capabilities. The results of a study of SMEs suggest that market focused learning, relative to other learning capabilities plays a key role in the relationships between industry structure, innovation and brand performance. The findings also show that market focused learning and internally focused learning influence innovation and that innovation influences a brand's performance. (c) 2005 Elsevier Inc. All rights reserved.

Rule induction for data exploration

This paper describes how the statistical technique of cluster analysis and the machine learning technique of rule induction can be combined to explore a database. The ways in which such an approach alleviates the problems associated with other techniques for data analysis are discussed. We report the results of experiments carried out on a database from the medical diagnosis domain. Finally we describe the future developments which we plan to carry out to build on our current work.

Elaboration and testing of new methodologies for automatic abstracting

The primary objective of this research was to understand what kinds of knowledge and skills people use in `extracting' relevant information from text and to assess the extent to which expert systems techniques could be applied to automate the process of abstracting. The approach adopted in this thesis is based on research in cognitive science, information science, psycholinguistics and textlinguistics. The study addressed the significance of domain knowledge and heuristic rules by developing an information extraction system, called INFORMEX. This system, which was implemented partly in SPITBOL, and partly in PROLOG, used a set of heuristic rules to analyse five scientific papers of expository type, to interpret the content in relation to the key abstract elements and to extract a set of sentences recognised as relevant for abstracting purposes. The analysis of these extracts revealed that an adequate abstract could be generated. Furthermore, INFORMEX showed that a rule based system was a suitable computational model to represent experts' knowledge and strategies. This computational technique provided the basis for a new approach to the modelling of cognition. It showed how experts tackle the task of abstracting by integrating formal knowledge as well as experiential learning. This thesis demonstrated that empirical and theoretical knowledge can be effectively combined in expert systems technology to provide a valuable starting approach to automatic abstracting.

Dynamic learning as entrepreneurial action in the context of open innovation:an instrumental case from a communities-of-practice perspective

Recent scholarly discussion on open innovation put forward the notion that an organisation's ability to internalise external knowledge and learn from various sources in undertaking new product development is crucial to its competitive performance. Nevertheless, little attention has been paid to how growth-oriented small firms identify and exploit entrepreneurial opportunities (i.e. take entrepreneurial action) related to such development, in an open innovation context, from a social learning perspective. This chapter, based on an instrumental case-firm, demonstrates analytically how learning as entrepreneurial action takes place, drawing on situated learning theory. It is argued that such learning is dynamic in nature and is founded on specific organising principles that foster both inter- and intracommunal learning. © 2012, IGI Global.

Personal knowledge development in online learning:a model for measuring externalisation, combination and internalisation

This paper presents a model for measuring personal knowledge development in online learning environments. It is based on Nonaka‘s SECI model of organisational knowledge creation. It is argued that Socialisation is not a relevant mode in the context of online learning and was therefore not covered in the measurement instrument. Therefore, the remaining three of SECI‘s knowledge conversion modes, namely Externalisation, Combination, and Internalisation were used and a measurement instrument was created which also examines the interrelationships between the three modes. Data was collected using an online survey, in which online learners report on their experiences of personal knowledge development in online learning environments. In other words, the instrument measures the magnitude of online learners‘ Externalisation and combination activities as well as their level of internalisation, which is the outcome of their personal knowledge development in online learning.

The Experience of Development and Application Perspectives of Learning Integrated Expert Systems in the Educational Process

The main principles and experience of development of learning integrated expert systems based on the third generation instrumental complex AT-TECHNOLOGY are considered.

An improved conflicting evidence combination approach based on a new supporting probability distance

To avoid counter-intuitive result of classical Dempster's combination rule when dealing with highly conflict information, many improved combination methods have been developed through modifying the basic probability assignments (BPAs) of bodies of evidence (BOEs) by using a certain measure of the degree of conflict or uncertain information, such as Jousselme's distance, the pignistic probability distance and the ambiguity measure. However, if BOEs contain some non-singleton elements and the differences among their BPAs are larger than 0.5, the current conflict measure methods have limitations in describing the interrelationship among the conflict BOEs and may even lead to wrong combination results. In order to solve this problem, a new distance function, which is called supporting probability distance, is proposed to characterize the differences among BOEs. With the new distance, the information of how much a focal element is supported by the other focal elements in BOEs can be given. Also, a new combination rule based on the supporting probability distance is proposed for the combination of the conflicting evidences. The credibility and the discounting factor of each BOE are generated by the supporting probability distance and the weighted BOEs are combined directly using Dempster's rules. Analytical results of numerical examples show that the new distance has a better capability of describing the interrelationships among BOEs, especially for the highly conflicting BOEs containing non-singleton elements and the proposed new combination method has better applicability and effectiveness compared with the existing methods.

Online learning in discrete hidden Markov models

We present and analyze three different online algorithms for learning in discrete Hidden Markov Models (HMMs) and compare their performance with the Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of the generalization error we draw learning curves in simplified situations and compare the results. The performance for learning drifting concepts of one of the presented algorithms is analyzed and compared with the Baldi-Chauvin algorithm in the same situations. A brief discussion about learning and symmetry breaking based on our results is also presented. © 2006 American Institute of Physics.

Differences in learning style preference among students of diverse ethnicities, gender, academic placement level, and academic achievement

This investigation studied the differences in learning styles among ethnically diverse secondary science students from a multicultural urban high school. It examined whether there were learning style differences among samples based on ethnicity, gender, academic grouping, and academic achievement. The learning style elements were based on scores of the Dunn, Dunn, and Price Learning Style Inventory (LSI) (1997). The sample (n = 476) consisted of students enrolled in Life Science courses. The analyses of data were made by one way analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). ^ Significant differences were found among students for three of the four groups tested. The largest numbers of differences in learning style element preference were in academic grouping, with eight significant differences showing small or medium effect sizes. There were four significant differences between genders and one significant difference among ethnic groups. Effect size was small. The data analyses showed that individual differences have a much bigger effect than group differences on learning style, and that proportions in learning style element categories reveal more information than means of groups. ^ This study implied the need to increase awareness of differences in learning styles among students and help educators to understand them. Other predictors of learning styles might account for a large amount of the unexplained variation. Overall, this study reinforces the body of existing literature. ^

Nursing faculty intention to use service learning as pedagogy in higher education

The purpose of this study was to identify the factors that motivate nursing faculty to use service learning. The study was based on the theory of planned behavior (TPB), which implies that the target behavior of intention to use service learning in higher education is influenced by the predictor variables of behavior beliefs (attitude), normative beliefs (peer influence), and control beliefs (confidence and resources). External variables were also considered (years of teaching experience, tenure status, and the type of curriculum). ^ Group interviews and a pilot test were conducted to create the instrument for the study, and Cronbach alpha were calculated for survey item reliability. The participants were full time undergraduate nursing faculty members ( n = 160) in the Southeastern United States who taught in universities with accredited nurse education programs. Demographic data as well as scores on scaled survey responses were used to evaluate the intention of nursing faculty to use service learning in their classes. ^ Pearson product moment correlation coefficient and path analysis were applied to the data. The correlation findings indicated that there were statistically significant relationships between behavior beliefs, normative beliefs, and control beliefs and nursing faculty intention to use service learning. The path analysis also indicated that behavior beliefs and normative beliefs were significant, while control beliefs were not a strong influence on intention to use service learning. Normative beliefs showed the strongest direct influence. The use of a community based curriculum also had a positive influence on intention, and faculty with tenure status were more likely to have positive behavior beliefs (attitude) towards service learning. Finally, as teaching experience increased, positive attitudes towards the intention to use service learning decreased. Seventy-nine percent of the variation in the intention to use service learning was explained by the theory of planned behavior, the type of curriculum, teaching experience, and tenure status. These results will assist nursing administration and faculty to design strategies to facilitate the implementation of service learning pedagogy, as well as a community based curriculum which will help meet the 21st century goals set forth from the American Association of Colleges of Nursing. ^

Neural network based off-line handwritten text recognition system

This dissertation introduces a new system for handwritten text recognition based on an improved neural network design. Most of the existing neural networks treat mean square error function as the standard error function. The system as proposed in this dissertation utilizes the mean quartic error function, where the third and fourth derivatives are non-zero. Consequently, many improvements on the training methods were achieved. The training results are carefully assessed before and after the update. To evaluate the performance of a training system, there are three essential factors to be considered, and they are from high to low importance priority: (1) error rate on testing set, (2) processing time needed to recognize a segmented character and (3) the total training time and subsequently the total testing time. It is observed that bounded training methods accelerate the training process, while semi-third order training methods, next-minimal training methods, and preprocessing operations reduce the error rate on the testing set. Empirical observations suggest that two combinations of training methods are needed for different case character recognition. Since character segmentation is required for word and sentence recognition, this dissertation provides also an effective rule-based segmentation method, which is different from the conventional adaptive segmentation methods. Dictionary-based correction is utilized to correct mistakes resulting from the recognition and segmentation phases. The integration of the segmentation methods with the handwritten character recognition algorithm yielded an accuracy of 92% for lower case characters and 97% for upper case characters. In the testing phase, the database consists of 20,000 handwritten characters, with 10,000 for each case. The testing phase on the recognition 10,000 handwritten characters required 8.5 seconds in processing time.

Nursing faculty intention to use service learning as pedagogy in higher education

The purpose of this study was to identify the factors that motivate nursing faculty to use service learning. The study was based on the theory of planned behavior (TPB), which implies that the target behavior of intention to use service learning in higher education is influenced by the predictor variables of behavior beliefs (attitude), normative beliefs (peer influence), and control beliefs (confidence and resources). External variables were also considered (years of teaching experience, tenure status, and the type of curriculum). Group interviews and a pilot test were conducted to create the instrument for the study, and Cronbach alpha were calculated for survey item reliability. The participants were full time undergraduate nursing faculty members (n=-160) in the Southeastern United States who taught in universities with accredited nurse education programs. Demographic data as well as scores on scaled survey responses were used to evaluate the intention of nursing faculty to use service learning in their classes. Pearson product moment correlation coefficient and path analysis were applied to the data. The correlation findings indicated that there were statistically significant relationships between behavior beliefs, normative beliefs, and control beliefs and nursing faculty intention to use service learning. The path analysis also indicated that behavior beliefs and normative beliefs were significant, while control beliefs were not a strong influence on intention to use service learning. Normative beliefs showed the strongest direct influence. The use of a community based curriculum also had a positive influence on intention, and faculty with tenure status were more likely to have positive behavior beliefs (attitude) towards service learning. Finally, as teaching experience increased, positive attitudes towards the intention to use service learning decreased. Seventy-nine percent of the variation in the intention to use service learning was explained by the theory of planned behavior, the type of curriculum, teaching experience, and tenure status. These results will assist nursing administration and faculty to design strategies to facilitate the implementation of service learning pedagogy, as well as a community based curriculum which will help meet the 21st century goals set forth from the American Association of Colleges of Nursing.

O Ensino de ligações químicas por meio do conceito de energia: uma proposta didática para o ensino médio

This work presents discussions on the teaching of Chemical Bonds in high school and some implications of this approach in learning chemistry by students. In general, understanding how the chemicals combine to form substances and compounds, it is a key point for understanding the properties of substances and their structure. In this sense, the chemical bonds represent an extremely important issue, and their knowledge is essential for a better understanding of the changes occurring in our world. Despite these findings, it is observed that the way in which this concept is discussed in chemistry class has contributed, paradoxically, to the emergence of several alternative designs, making the understanding of the subject by students. It is believed that one of the explanations for these observations is the exclusive use of the "octet rule" as an explanatory model for the Chemical Bonds. The use of such a model over time eventually replace chemical principles that gave rise to it, transforming knowledge into a series of uninteresting rituals and even confusing for students. Based on these findings, it is deemed necessary a reformulation in the way to approach this content in the classroom, taking into account especially the fact that the explanations of the formation of substances should be based on the energy concept, which is fundamental to understanding how atoms combine. Thus, the main question of the survey and described here of the following question: Can the development of an explanatory model for the Chemical Bonds in high school based on the concept of energy and without the need to use the "octet rule"? Based on the concepts and methodologies of modeling activity, we sought the development of a teaching model was made through Teaching Units designed to give subsidies to high school teachers to address the chemical bonds through the concept of energy. Through this work it is intended to make the process of teaching and learning of Chemical Bonds content becomes more meaningful to students, developing models that contribute to the learning of this and hence other basic fundamentals of chemistry.

O Ensino de ligações químicas por meio do conceito de energia: uma proposta didática para o ensino médio

This work presents discussions on the teaching of Chemical Bonds in high school and some implications of this approach in learning chemistry by students. In general, understanding how the chemicals combine to form substances and compounds, it is a key point for understanding the properties of substances and their structure. In this sense, the chemical bonds represent an extremely important issue, and their knowledge is essential for a better understanding of the changes occurring in our world. Despite these findings, it is observed that the way in which this concept is discussed in chemistry class has contributed, paradoxically, to the emergence of several alternative designs, making the understanding of the subject by students. It is believed that one of the explanations for these observations is the exclusive use of the "octet rule" as an explanatory model for the Chemical Bonds. The use of such a model over time eventually replace chemical principles that gave rise to it, transforming knowledge into a series of uninteresting rituals and even confusing for students. Based on these findings, it is deemed necessary a reformulation in the way to approach this content in the classroom, taking into account especially the fact that the explanations of the formation of substances should be based on the energy concept, which is fundamental to understanding how atoms combine. Thus, the main question of the survey and described here of the following question: Can the development of an explanatory model for the Chemical Bonds in high school based on the concept of energy and without the need to use the "octet rule"? Based on the concepts and methodologies of modeling activity, we sought the development of a teaching model was made through Teaching Units designed to give subsidies to high school teachers to address the chemical bonds through the concept of energy. Through this work it is intended to make the process of teaching and learning of Chemical Bonds content becomes more meaningful to students, developing models that contribute to the learning of this and hence other basic fundamentals of chemistry.