The Genomic HyperBrowser: inferential genomics at the sequence level

The immense increase in the generation of genomic scale data poses an unmet analytical challenge, due to a lack of established methodology with the required flexibility and power. We propose a first principled approach to statistical analysis of sequence-level genomic information. We provide a growing collection of generic biological investigations that query pairwise relations between tracks, represented as mathematical objects, along the genome. The Genomic HyperBrowser implements the approach and is available at http://hyperbrowser.uio.no

Improving the Quality of Teaching Internships with the Help of the Platforms

This article presents an empirical study on the perceptions of university students toward the development of the teaching practicum, using the CourseSites platform as a communication and support tool for their training. The opinions of the students were collected through a questionnaire. The sample consisted of 1500 students who were registered in the degrees of Early Childhood Education, Primary Education and Pedagogy (2008-2018). A descriptive, inferential and multi-level analysis was conducted, which confirmed that future teachers had activated their professional competences, as they had the chance to share their internship experiences with their faculty members and with their own classmates

An exploratory comparison of the inferential ability of EFL and ESL students : a thesis presented in partial fulfilment of the requirements for the degree of Master of Management at Massey University

The ability to access and interpret information is a very important component in generating knowledge. However, people are not always able to discover information, quickly evaluate the importance of the information and access it (Tichenor, Donohue & Olien, 1970; Chatman, 1991; Sligo & Williams, 2002). Especially in a tertiary academic setting, the ability to access information and integrate information from various sources to infer what is not overtly stated in a text is an essential skill during the reading process (Kintsch, 1994; Barnes, Dennis, & Haefele-Kalvaitis, 1996; Cain, Oakhill, Barnes, & Bryant, 2001). Because of differences among people's educational background, existing pools of knowledge and communication abilities, the ability to access information will affect their inferential ability in the reading process (Alexander, 1994; Ericsson, 1996; Mckoon & Ratcliff, 1992). Although inferential ability is to be of consequence for academic functioning, very little research has been done on the comparison of inferential ability among students with English as their first language and those with English as their second language. This study examines the relative extent of text inferential ability among students with English as a first language (EFL) and students to whom English is a second language (ESL), employing the knowledge gap hypothesis, and assesses its implications. Using a procedure to assess inferential ability, this thesis compares the differences in inferential ability demonstrated by EFL and ESL students, employing cloze tests. This study found that EFL students' performance on the inferential ability and cloze item completion task is significantly better than that of their ESL counterparts via the first two scoring methods (Methods A and B). However, the inferential ability of ESL students is almost as good as their EFL counterparts when assessed by the third scoring method (Method C). The research findings suggest that Sligo and Williams (2002) are right in terming the knowledge gap as an amalgam of knowledge, comprehension and inference (p.6). Subsidiary analyses of the source of inference failures revealed different underlying sources of difficulty for both EFL and ESL students. The results of the research provide insights into the nature of gaps in accessing information and inference making. Education in a tertiary institution may or may not reduce gaps. Though both EFL and ESL students improved from their original starting level, the gaps of inferential ability between EFL and ESL students in the two tests, especially via Methods A and B, widened. In the second test, both EFL and ESL students made progress in inferential ability. Yet there still remained a gap between the two groups of students in test two as the knowledge rich individuals improved at a similar rate as the knowledge poor. The present study supports the contention of Sligo and Williams (2002) that there is an unexamined area at the heart of the knowledge gap hypothesis literature. The findings of the present study suggest the correctness of the proposal by Sligo and Williams (2002) that what knowledge gap hypothesis researchers call knowledge gaps should in fact be better described as some amalgam of gaps in knowledge, and/or inferential ability. This is the most significant finding of the present research

Adaptive inferential sensors based on evolving fuzzy models

A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can a- ddress the challenges of the modern advanced process industry

Jeremy Bentham, social criticism and levels of meaning

Published in an e-journal

Logic in the tradition of Prabhacandra

The characterization of truth-preserving arguments is a core issue in India and received the detailed attention of philosophers. This chapter presents Prabhācandra’s theory of inference from the eleventh century, stressing its uniqueness and detailed critique of Dignāga and Dharmakīrti. In Prabhācandra’s framework, the inferential evidence has not three but just one characteristic, “being impossible otherwise.” The epistemological problem of the means to know when evidence has this characteristic is solved without regress by appeal to a non-inferential source of knowing, the “discernment of universals” (tarka). Finally, important advances in the role of negation in logical inference are related to a greater emphasis on linguistic form

Teachers' use of questioning and modelling comprehension skills in primary classrooms

Research suggests that children's understanding of text can be improved by the explicit teaching of those comprehension strategies that are used implicitly by skilled readers, particularly the use of self-regulating strategies to generate questions about text. This study of the teaching of comprehension in 51 London Key Stage 2 classrooms explores the extent to which comprehension strategies are explicitly taught within the literacy hour and the amount of opportunity which is provided for children to generate there own questions. Evidence from teacher interviews and classroom observations shows that direct teacher questioning, mostly in the form of 'teacher-led recitation', is both the most frequently advocated, and the dominant strategy used for teaching comprehension. When sharing books with children, teachers model the strategies which are used by skilled comprehenders, but they neither make these strategies explicit nor encourage children to generate their own questions about the text

Predicting continuous conflict perception with Bayesian Gaussian processes

Conflict is one of the most important phenomena of social life, but it is still largely neglected by the computing community. This work proposes an approach that detects common conversational social signals (loudness, overlapping speech, etc.) and predicts the conflict level perceived by human observers in continuous, non-categorical terms. The proposed regression approach is fully Bayesian and it adopts Automatic Relevance Determination to identify the social signals that influence most the outcome of the prediction. The experiments are performed over the SSPNet Conflict Corpus, a publicly available collection of 1430 clips extracted from televised political debates (roughly 12 hours of material for 138 subjects in total). The results show that it is possible to achieve a correlation close to 0.8 between actual and predicted conflict perception