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University of Colorado Boulder, United States

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5 Papers

Modeling the Serial Position Effect - Using the Emergent Neural Network Simulation System

Topic: Simulation

Authors: Katherine Goodman and John K. Bennett

Affiliation: University of Colorado Boulder, United States

Digital Object Identifier: 10.5220/0004802701640171

Proceedings of BIOINFORMATICS 2014/BIOSTEC, ISBN: 978-989-758-012-3

Quick Abstract

The Serial Position Effect (SPE) is a well-studied phenomenon in experimental psychology. SPE captures the idea that, when subjects are asked to recall list items, they are more likely to remember the first items and the last items, whether those items are numbers, non-words or elements of a story. Until recently, SPE has been generally considered to rely upon a two-store memory model, i.e., primacy (remembering initial items) and recency (remembering latter items) were thought to be the work of long term memory and short term memory, respectively. This paper reports the results of a basic hippocampus simulation study using the Leabra algorithm within the Emergent Neural Network Simulation System to model the SPE. Simulation results demonstrate that both primacy and recency of the SPE in a serial recall task can be replicated using only the hippocampus, suggesting that a one-store model of memory for this recall task is sufficient. It remains to be seen if this simulation mirrors the actual biological mechanism utilized.

Related Ontology Subjects/Areas/Topics (9)

Agents	Biomedical Engineering	Methodologies and Technologies
Artificial Intelligence	Enterprise Information Systems	Operational Research
Bioinformatics	Information Systems Analysis and Specification	Simulation

Partopens at the Point of Care - Evaluating Digital Pen-based Maternal Labor Monitoring in Kenya

Topics: Decision Support Systems; Medical and Nursing Informatics; Evaluation and Use of Healthcare IT; Software Systems in Medicine; Clinical Problems and Applications

Authors: Heather Underwood ¹ , John Ong’ech ² , Maya Appley ¹ , Sara Rosenblum ¹ , Addie Crawley ¹ , S. Revi Sterling ¹ and John K. Bennett ¹

Affiliations: ¹ University of Colorado Boulder, United States , ² Kenyatta National Hospital, Kenya

Digital Object Identifier: 10.5220/0004798600900100

Proceedings of HEALTHINF 2014/BIOSTEC, ISBN: 978-989-758-010-9

Quick Abstract

The goal of the PartoPen system is to enhance the partograph, a paper-based labor monitoring tool intended to promote timely delivery of quality care by birth attendants in developing countries. The PartoPen digital pen hardware and software system supports partograph use by providing audio instructions for measuring and recording labor progress indicators, real-time decision support based on recorded measurements, and time-based patient-specific reminders for taking measurements. Earlier work found the PartoPen system effective in nursing classrooms at the University of Nairobi (UoN), Kenya where the PartoPen was used to support teaching and training of students in maternal labor monitoring procedures. This paper presents the results of several follow-on studies conducted in the maternity ward of Kenyatta National Hospital (KNH) in Nairobi. Through these studies, we successively refine our understanding of the benefits of PartoPen use in this setting. We also identify and discuss the interrelated factors impacting PartoPen adoption and use in the labor ward at KNH, and review the challenges and opportunities likely to face digital pen deployments in other healthcare settings.

Related Ontology Subjects/Areas/Topics (10)

Biomedical Engineering	Decision Support Systems	Health Information Systems
Cardiovascular Technologies	Evaluation and Use of Healthcare IT	Medical and Nursing Informatics
Clinical Problems and Applications	Health Engineering and Technology Applications	Software Systems in Medicine
Computing and Telecommunications in Cardiology

The PartoPen in Training and Clinical Use - Two Preliminary Studies in Kenya

Topics: Decision Support Systems; Medical and Nursing Informatics; Clinical Problems and Applications

Authors: Heather Underwood , S. Revi Sterling and John K. Bennett

Affiliation: University of Colorado Boulder, United States

Digital Object Identifier: 10.5220/0004251101120121

Proceedings of HEALTHINF 2013/BIOSTEC, ISBN: 978-989-8565-37-2

Quick Abstract

This paper presents the findings from two studies of the PartoPen system – a digital pen software application that enhances the partograph, a paper-based labor-monitoring tool used extensively in developing regions. The PartoPen provides nurses with real-time decision support, instructions, and patient-specific reminders by playing short audio clips when a nurse records data on the existing paper partograph form. Previous studies have shown that correct use of the partograph significantly reduces pregnancy complications; however, the partograph is not always reliably or correctly completed due to resource and training challenges commonly found in developing world clinics. The PartoPen system addresses several significant barriers to correct partograph use in developing countries. The preliminary studies described in this paper examine how the PartoPen system affects classroom-based partograph training among nursing students at the University of Nairobi, and partograph completion and accuracy in actual labor and delivery situations by nurse-midwives at Kenyatta National Hospital in Nairobi, Kenya. The initial results of these studies indicate that using the PartoPen system enhances student performance on partograph worksheets, and that use of the PartoPen system in labor wards positively affects partograph completion rates and nurses’ level of expertise using the partograph form.

Related Ontology Subjects/Areas/Topics (8)

Biomedical Engineering	Computing and Telecommunications in Cardiology	Health Information Systems
Cardiovascular Technologies	Decision Support Systems	Medical and Nursing Informatics
Clinical Problems and Applications	Health Engineering and Technology Applications

TIME SERIES SEGMENTATION AS A DISCOVERY TOOL - A Case Study of the US and Japanese Financial Markets

Topics: Information Extraction; Mining High-Dimensional Data; Clustering and Classification Methods; Visual Data Mining and Data Visualization

Authors: Jian Cheng Wong ¹ , Gladys Hui Ting Lee ¹ , Yiting Zhang ¹ , Woei Shyr Yim ¹ , Robert Paulo Fornia ² , Danny Yuan Xu ³ , Jun Liang Kok ¹ and Siew Ann Cheong ¹

Affiliations: ¹ Nanyang Technological University, Singapore , ² University of Colorado at Boulder, United States , ³ Bard College, United States

Digital Object Identifier: 10.5220/0003653700520063

Proceedings of KDIR 2011/IC3K, ISBN: 978-989-8425-79-9

Quick Abstract

In this paper we explain how the dynamics of a complex system can be understood in terms of the lowdimensional manifolds (phases), described by slowly varying effective variables, it settles onto. We then explain how we can discover these phases by grouping the large number of microscopic time series or time series segments, based on their statistical similarities, into the a small number of time series classes, each representing a distinct phase. We describe a specific recursive scheme for time series segmentation based on the Jensen-Shannon divergence, and check its performance against artificial time series data. We then apply the method on the high-frequency time series data of various US and Japanese financial market indices, where we found that the time series segments can be very naturally grouped into four to six classes, corresponding roughly with economic growth, economic crisis, market correction, and market crash. From a single time series, we can estimate the lifetimes of these macroeconomic phases, and also identify potential triggers for each phase transition. From a cross section of time series, we can further estimate the transition times, and also arrive at an unbiased and detailed picture of how financial markets react to internal or external stimuli.

Related Ontology Subjects/Areas/Topics (8)

Artificial Intelligence	Knowledge Discovery and Information Retrieval	Symbolic Systems
Clustering and Classification Methods	Knowledge-Based Systems	Visual Data Mining and Data Visualization
Information Extraction	Mining High-Dimensional Data

PORTING LEGACY APPLICATIONS TO IMMERSIVE VIRTUAL ENVIRONMENTS - A Case Study

Topics: Augmented, Mixed and Virtual Environments; Distributed Augmented, Mixed and Virtual Reality; Real-Time Graphics; Graphical Interfaces

Authors: Kenny Gruchalla , Jonathan Marbach and Mark Dubin

Affiliation: University of Colorado at Boulder, United States

Digital Object Identifier: 10.5220/0002078401790184

Proceedings of GRAPP 2007, ISBN: 978-972-8865-72-6

Quick Abstract

Immersive virtual environments are becoming increasingly common, driving the need to develop new software or adapt existing software to these environments. We discuss some of the issues and limitations of porting an existing molecular graphics system, PyMOL, into an immersive virtual environment. Presenting macromolecules inside an interactive immersive virtual environment may provide unique insights into molecular structure and improve the rational design of drugs that target a specific molecule. PyMOL was successfully extended to render molecular structures immersively; however, elements of the legacy interactive design did not scale well into three-dimensions. Achieving an interactive frame rate for large macromolecules was also an issue. The immersive system was developed and evaluated on both a shared-memory parallel machine and a commodity cluster.

Related Ontology Subjects/Areas/Topics (6)

Augmented, Mixed and Virtual Environments		Distributed Augmented, Mixed and Virtual Reality		Interactive Environments
Computer Vision, Visualization and Computer Graphics		Graphical Interfaces		Real-Time Graphics