Four decades of health economics through a bibliometric lens

This paper takes a bibliometric tour of the past 40 years of health economics using bibliographic"metadata"from EconLit supplemented by citation data from Google Scholar and the authors'topical classifications. The authors report the growth of health economics (33,000 publications since 1969 -- 12,000 more than in the economics of education) and list the 300 most-cited publications broken down by topic. They report the changing topical and geographic focus of health economics (the topics'Determinants of health and ill-health'and'Health statistics and econometrics'both show an upward trend, and the field has expanded appreciably into the developing world). They also compare authors, countries, institutions, and journals in terms of the volume of publications and their influence as measured through various citation-based indices (Grossman, the US, Harvard and the JHE emerge close to or at the top on a variety of measures).Health Monitoring&Evaluation,Health Systems Development&Reform,Health Economics&Finance,Rural Development Knowledge&Information Systems,Health Law

Model-based workflow for scale-up of process strategies developed in miniaturized bioreactor systems

Miniaturized bioreactor (MBR) systems are routinely used in the development of mammalian cell culture processes. However, scale-up of process strategies obtained in MBR- to larger scale is challenging due to mainly non-holistic scale-up approaches. In this study, a model-based workflow is introduced to quantify differences in the process dynamics between bioreactor scales and thus enable a more knowledge-driven scale-up. The workflow is applied to two case studies with antibody-producing Chinese hamster ovary cell lines. With the workflow, model parameter distributions are estimated first under consideration of experimental variability for different scales. Second, the obtained individual model parameter distributions are tested for statistical differences. In case of significant differences, model parametric distributions are transferred between the scales. In case study I, a fed-batch process in a microtiter plate (4 ml working volume) and lab-scale bioreactor (3750 ml working volume) was mathematically modeled and evaluated. No significant differences were identified for model parameter distributions reflecting process dynamics. Therefore, the microtiter plate can be applied as scale-down tool for the lab-scale bioreactor. In case study II, a fed-batch process in a 24-Deep-Well-Plate (2 ml working volume) and shake flask (40 ml working volume) with two feed media was investigated. Model parameter distributions showed significant differences. Thus, process strategies were mathematically transferred, and model predictions were simulated for a new shake flask culture setup and confirmed in validation experiments. Overall, the workflow enables a knowledge-driven evaluation of scale-up for a more efficient bioprocess design and optimization

Function modeling based on interactions of mass, energy and information.

Although the ultimate goal of engineering design is to present a physical form (components and their relationships) of a certain product, function modeling is regarded as the initial and determining stage in the entire design process. While a variety of research efforts have studied and continue to study the role of function modeling in design, the concepts and representations of function among researchers are quite different. This makes it very difficult to utilize research achievements in developing an integrated knowledge-based system (e.g. the AIM-D system established in [1]) that can be used universally throughout an arbitrary engineering design process. In this thesis, a new function model called Interaction-based Function Model (IFM) which is based on the basic interactions between mass, energy, and information is presented. A small set of primitive function types which could represent most (perhaps all) product functions is deduced from this model. The author believes that IFM can provide a widely accepted function-modeling platform that could integrate the current research achievements in this area. Furthermore, by applying IFM to knowledge aided design systems (e.g. ACM system establish by Salustri in [2]), it can be used to shorten the lead-time of product development, motivate creative design, and organize design information system. An example of implementing IFM to facilitate the conceptual design process is presented. The results demonstrate that this methodology can be used as a design guide to help designers identify key issues in the early design stage without blocking the creativeness of the designers.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .Y34. Source: Masters Abstracts International, Volume: 40-03, page: 0766. Adviser: Fillippo A. Saluseri. Thesis (M.A.Sc.)--University of Windsor (Canada), 2001

Development of a knowledge-based system for the control of 319-aluminum melt quality and prediction of casting characteristics.

Knowledge Based Systems are computer programs used in situations where the use of heuristic knowledge and reasoning offers the only possibility of a solution mainly because the problem being studied is too complex to be represented in an algorithmic form. In general terms, such systems address and solve knowledge-intensive problems that can have many acceptable answers. The interpretation of Thermal Analysis results is a suitable task for artificial intelligence technology since it is a knowledge intensive activity in which several factors interact and modify the characteristics of the cooling curves. In the present work, an Aluminum Thermal Analysis System (AlTAS) developed at the University of Windsor was implemented at a casting plant and after verification of its performance in an industrial scenario a Case-Based Reasoning System coupled with a Statistical Process Control module were developed to upgrade the capabilities of the AlTAS. The system will be used to control, on-line and prior to casting, the quality of the W319-Al melt used to produce aluminum engine blocks under the Cosworth casting process, and predict their tensile properties and microstructure.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .P45. Source: Masters Abstracts International, Volume: 40-03, page: 0777. Advisers: Reza Lashkari; Jerry Sokolowski. Thesis (M.A.Sc.)--University of Windsor (Canada), 2001

IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

The Challenges of Integrating Instrumentation with Inflatable Aerodynamic Decelerators

To realize the National Aeronautics and Space Administration s (NASA) goal of landing humans on Mars, development of technologies to facilitate the landing of heavy payloads are being explored. Current entry, decent, and landing technologies are not practical when utilizing these heavy payloads due to mass and volume constraints dictated by limitations imposed by current launch vehicle fairings. Therefore, past and present technologies are now being considered to provide a mass and volume efficient solution, including Inflatable Aerodynamic Decelerators (IADs) [1]. IAD ground and flight tests are currently being conducted to develop and characterize their performance under flight-like conditions. The integrated instrumentation systems, which are key to the performance characterization in each of these tests, have proven to be a challenge compared to the instrumentation of traditional rigid aeroshells. To overcome these challenges, flexible and embedded sensing systems have been developed, along with improved instrumenting techniques. This development opportunity faces many difficult aspects specific to inflatable structures in extreme environments. These include but are not limited to: physical flexibility, packaging, temperature, structural integration and data acquisition [2]. To better define the instrumentation challenges posed by IAD technology development, a survey was conducted to identify valuable measurements for ground and flight testing. From this survey many sensing technologies were explored, resulting in a down-selection to the most viable prospects. These systems were then iterated upon in design to determine the best integration techniques specific to a 3m and 6m stacked torus IAD. Each sensing system was then integrated and employed to support the IAD testing in the National Full-Scale Aerodynamics Complex 40 x 80 wind tunnel at NASA Ames Research Center in the summer of 2012. Another challenge that has been explored is the data acquisition of IAD sensing technologies. Traditionally all space based sensing systems transmit their data through a wired interface. This limits the amount of sensors able to be integrated within the IAD due to volume and routing restrictions of the supporting signal and excitation wires. To alleviate this situation, multiple wireless data acquisition technologies have been researched and developed through rapid prototyping efforts. The final custom multi-nodal wireless system utilized during the summer 2012 IAD test series consisted of four remote nodes and one receiving base station. The system reliably conditioned and acquired 20+ sensors over the course of the wind tunnel test series. These developments in wireless data acquisition techniques can eliminate the need for structural feedthroughs and reduce system mass associated with wiring and wire harnesses. This makes the utilization of flight instrumentation more attractive to future missions, which would result in further improved characterization of IAD technology, and overall, increased scientific knowledge regarding the response of inflatable structures to extreme entry environments.

Knowledge Base Population using Semantic Label Propagation

A crucial aspect of a knowledge base population system that extracts new facts from text corpora, is the generation of training data for its relation extractors. In this paper, we present a method that maximizes the effectiveness of newly trained relation extractors at a minimal annotation cost. Manual labeling can be significantly reduced by Distant Supervision, which is a method to construct training data automatically by aligning a large text corpus with an existing knowledge base of known facts. For example, all sentences mentioning both 'Barack Obama' and 'US' may serve as positive training instances for the relation born_in(subject,object). However, distant supervision typically results in a highly noisy training set: many training sentences do not really express the intended relation. We propose to combine distant supervision with minimal manual supervision in a technique called feature labeling, to eliminate noise from the large and noisy initial training set, resulting in a significant increase of precision. We further improve on this approach by introducing the Semantic Label Propagation method, which uses the similarity between low-dimensional representations of candidate training instances, to extend the training set in order to increase recall while maintaining high precision. Our proposed strategy for generating training data is studied and evaluated on an established test collection designed for knowledge base population tasks. The experimental results show that the Semantic Label Propagation strategy leads to substantial performance gains when compared to existing approaches, while requiring an almost negligible manual annotation effort.Comment: Submitted to Knowledge Based Systems, special issue on Knowledge Bases for Natural Language Processin

Design thinking support: information systems versus reasoning

Numerous attempts have been made to conceive and implement appropriate information systems to support architectural designers in their creative design thinking processes. These information systems aim at providing support in very diverse ways: enabling designers to make diverse kinds of visual representations of a design, enabling them to make complex calculations and simulations which take into account numerous relevant parameters in the design context, providing them with loads of information and knowledge from all over the world, and so forth. Notwithstanding the continued efforts to develop these information systems, they still fail to provide essential support in the core creative activities of architectural designers. In order to understand why an appropriately effective support from information systems is so hard to realize, we started to look into the nature of design thinking and on how reasoning processes are at play in this design thinking. This investigation suggests that creative designing rests on a cyclic combination of abductive, deductive and inductive reasoning processes. Because traditional information systems typically target only one of these reasoning processes at a time, this could explain the limited applicability and usefulness of these systems. As research in information technology is increasingly targeting the combination of these reasoning modes, improvements may be within reach for design thinking support by information systems