10,387 research outputs found
Agent Based Test and Repair of Distributed Systems
No full textThis article demonstrates how to use intelligent agents for testing and repairing a distributed system, whose elements may or may not have embedded BIST (Built-In Self-Test) and BISR (Built-In Self-Repair) facilities. Agents are software modules that perform monitoring, diagnosis and repair of the faults. They form together a society whose members communicate, set goals and solve tasks. An experimental solution is presented, and future developments of the proposed approach are explore
Measuring the Effectiveness of Visual Narrative Illustrations for Learning Pathophysiology Concepts
Get PDFBackground: Patients’ health needs require detailed knowledge of diseases and the
associated pathophysiology to understand and manage their complex care. Nurses rely
on concepts from anatomy, physiology, microbiology, and pathophysiology to ground
their practice. While knowledge of disease processes is a critical requirements for
competent practice nursing, students often struggle with learning and applying
pathophysiology concepts to clinical practice.
Method: A novel teaching innovation known as “Visual Narrative Illustrations” (VNI)
was piloted in a pathophysiology course. Students (n=75), participated in two phases of
exploratory study that analyzed the impact of VNI on students’ understanding of
pathophysiology concepts and assessed whether VNI is an effective teaching method.
Results: Students taught using the VNI strategy performed significantly better on the
post-test than students taught using a traditional lecture format.
Conclusion: VNI assist students in learning complex concepts through the use of
humor and visual images and facilitate their understanding of pathophysiology
processes
Regression Test Suite Study using Classic Statistical Methods and Machine Learning
No full textThis work is inter disciplinary in nature. This work tries to apply latest discoveries in Artificial Intelligence to classic testing methodologies. Machine Learning which is the field of Artificial Intelligence is explored in this work. The
work demonstrates that provided the test team maintains the required data, Machine Learning Algorithms can aid in deciphering patterns from the test data. Patterns of interest are the relation between testers experience in the project and bugs uncovered, relations between the testers experience and the efficiency of test case with respect to code coverage and test execution time. Relation between testers experience and efficiency of test case with respect to code coverage and execution
time, relation between testers experience and bugs uncovered are explored using classic statistical techniques and clustering Machine Learning Algorithms. This clustering can be of immense help in test selection, prioritization, pruning and Regression test execution time reduction
Connecting does not necessarily mean learning: Course handbooks as mediating tools in school-university partnerships
Get PDFThis is the author's accepted manuscript (titled "Course handbooks as mediating tools in learning to teach"). The final published article is available from the link below. Copyright @ 2011 American Association of Colleges for Teacher Education.Partnerships between schools and universities in England use course handbooks to guide student teacher learning during long field experiences. Using data from a yearlong ethnographic study of a postgraduate certificate of education programme in one English university, the function of course handbooks in mediating learning in two high school subject departments (history and modern foreign languages) is analyzed. Informed by Cultural Historical Activity Theory, the analysis focuses on the handbooks as mediating tools in the school-based teacher education activity systems. Qualitative differences in the mediating functions of the handbooks-in-use are examined and this leads to a consideration of the potential of such tools for teacher learning in school–university partnerships. Following Zeichner’s call for rethinking the relationships between schools and universities, the article argues that strong structural connections between different institutional sites do not necessarily enhance student teacher learning
Also By The Same Author: AKTiveAuthor, a Citation Graph Approach to Name Disambiguation
No full textThe desire for definitive data and the semantic web drive for inference over heterogeneous data sources requires co-reference resolution to be performed on those data. In particular, name disambiguation is required to allow accurate publication lists, citation counts and impact measures to be determined. This paper describes a graph-based approach to author disambiguation on large-scale citation networks. Using self-citation, co-authorship and document source analyses, AKTiveAuthor clusters papers, achieving precision of 0.997 and recall of 0.818 over a test group of eight surname clusters
Continuous-time Model-based Reinforcement Learning
No full textModel-based reinforcement learning (MBRL) approaches rely on discrete-time state transition models whereas physical systems and the vast majority of control tasks operate in continuous-time. To avoid time-discretization approximation of the underlying process, we propose a continuous-time MBRL framework based on a novel actor-critic method. Our approach also infers the unknown state evolution differentials with Bayesian neural ordinary differential equations (ODE) to account for epistemic uncertainty. We implement and test our method on a new ODE-RL suite that explicitly solves continuous-time control systems. Our experiments illustrate that the model is robust against irregular and noisy data, and can solve classic control problems in a sample-efficient manner.Peer reviewe
LCDB 1.0: An Extensive Learning Curves Database for Classification Tasks
No full textThe use of learning curves for decision making in supervised machine learning is standard practice, yet understanding of their behavior is rather limited. To facilitate a deepening of our knowledge, we introduce the Learning Curve Database (LCDB), which contains empirical learning curves of 20 classification algorithms on 246 datasets. One of the LCDB’s unique strength is that it contains all (probabilistic) predictions, which allows for building learning curves of arbitrary metrics. Moreover, it unifies the properties of similar high quality databases in that it (i) defines clean splits between training, validation, and test data, (ii) provides training times, and (iii) provides an API for convenient access (pip install lcdb). We demonstrate the utility of LCDB by analyzing some learning curve phenomena, such as convexity, monotonicity, peaking, and curve shapes. Improving our understanding of these matters is essential for efficient use of learning curves for model selection, speeding up model training, and to determine the value of more training data.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Pattern Recognition and Bioinformatic
From e-Learning to m-learning: A MOOC case study
No full textTechnically e-learning material can be downloaded from a PC environment to a mobile phone environment. But the context, environment, physical limitations of a mobile phone, sets limits to a mobile learning environment. The didactic model cannot be transferred usually from e-learning to mobile learning environment. In an experiment we test the limitations of a mobile learning environment and possible constraints after downloading e-learning material on a mobile device. Finally we researched possible didactic models.Intelligent InteractionElectrical Engineering, Mathematics and Computer Scienc
The Use of Project Work to Promote Students’ Motivation toward English Class among 10 Graders of State Senior High School 1 Purworejo
No full textThis classroom action research aimed at using project work to promote the students’ motivation toward English class among 10 graders of State Senior High School 1 Purworejo in the Regency of Purworejo.
This research employed Kemmis & McTaggart’s model with two cycles. The subjects of the research were 10 graders of State Senior High School 1 Purworejo in the academic year of 2010/2011. The objects of this research were the project work and the students’ motivation toward English class. The data in this research were collected through observations, field notes, and interviews. The data of the research were in the forms of qualitative and quantitative data. The qualitative data were the observation records, interview records, field notes, students’ notes and photographs.
The data were analyzed through the reduction of data, display of data, and conclusion. The quantitative data were in the students’ scores from the questionnaire on motivation. The average scores of the preliminary test, first cycles’ test and the second cycle’s test were compared to see the progress made by the students on their motivation.
The results of the research showed that the use of project work promoted 80% of the students to have a high motivation toward English class on their attitudes, desires, and efforts in learning English. The results of the research were as follows. 1) The use of project work as a teaching technique changed the attitudes of students to be more proactive in English class. They found that learning English through project work was interesting and challenging. 2) The use of project work as a teaching technique promoted the effort of the students in mastering English. The students became active participants in practicing English in real life context. 3) Use of project work promoted the desire of students in learning English. 4) Project work also promoted the students' innovative, communicative and cooperative abilities.
The results of the analysis of the questionnaire on motivation showed that project work promoted the students’ motivation. In the preliminary test, it was found that
9.38% of students had low motivation, 59.38% of students had fair motivation, and 31.25% of the students had high motivation. Therefore, it was concluded that project work improved the students' motivation toward English class among 10 graders in State Senior High School 1 Purworejo
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