University of Winnipeg

About: University of Winnipeg is a education organization based out in Winnipeg, Manitoba, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 3235 authors who have published 6413 publications receiving 150564 citations. The organization is also known as: U of W.

Anticodes for the Grassman and bilinear forms graphs

Abstract: In [2], L. Chihara proved that many infinite families of classical distance-regular graphs have no nontrivial perfect codes, including the Grassman graphs and the bilinear forms graphs. Here, we present a new proof of her result for these two families using Delsarte's anticode condition[3]. The technique is an extension of an approach taken by C. Roos [6] in the study of perfect codes in the Johnson graphs.

Parametric fault diagnosis for electrohydraulic cylinder drive units

Abstract: A novel model-based methodology for fault diagnosis (FD) of nonlinear hydraulic drive systems is presented in this paper. Due to its linear dependence upon parameters, a second-truncated Volterra nonlinear model is first used to characterize such systems. The versatile order-recursive estimation scheme is employed to determine the values of parameters in the Volterra model. The scheme also avoids separate determination of the model order; thus, the complexity of the search process is reduced. Next, it is shown that the estimated parameters, representing different states of the system, normal as well as faulty conditions, can be used to detect and isolate system faults in a geometric domain. Very promising results are exhibited via simulations as well as laboratory experiments. It is concluded that the developed parametric FD technique has potential to provide efficient condition monitoring and/or preventive maintenance in hydraulic actuator circuits.

The evolution and changing ecology of the African hominid oral microbiome

Abstract: The oral microbiome plays key roles in human biology, health, and disease, but little is known about the global diversity, variation, or evolution of this microbial community. To better understand the evolution and changing ecology of the human oral microbiome, we analyzed 124 dental biofilm metagenomes from humans, including Neanderthals and Late Pleistocene to present-day modern humans, chimpanzees, and gorillas, as well as New World howler monkeys for comparison. We find that a core microbiome of primarily biofilm structural taxa has been maintained throughout African hominid evolution, and these microbial groups are also shared with howler monkeys, suggesting that they have been important oral members since before the catarrhine-platyrrhine split ca. 40 Mya. However, community structure and individual microbial phylogenies do not closely reflect host relationships, and the dental biofilms of Homo and chimpanzees are distinguished by major taxonomic and functional differences. Reconstructing oral metagenomes from up to 100 thousand years ago, we show that the microbial profiles of both Neanderthals and modern humans are highly similar, sharing functional adaptations in nutrient metabolism. These include an apparent Homo-specific acquisition of salivary amylase-binding capability by oral streptococci, suggesting microbial coadaptation with host diet. We additionally find evidence of shared genetic diversity in the oral bacteria of Neanderthal and Upper Paleolithic modern humans that is not observed in later modern human populations. Differences in the oral microbiomes of African hominids provide insights into human evolution, the ancestral state of the human microbiome, and a temporal framework for understanding microbial health and disease.

Artificial neural network for forecasting daily loads of a Canadian electric utility

Abstract: This paper describes the application of an artificial neural network to short term load forecasting. One of the most popular artificial neural network models, the 3-layer backpropagation model, is used to learn the relationship between 86 inputs, which are believed to have significant effects on the loads, and 24 outputs: one for each hourly load of the day. Historical data collected over a period of 2 years (e.g. calendar years 1989 and 1990) is used to train the proposed ANN network. The results of the proposed ANN networks have been compared to those of the present system (multiple linear regression) and show an improved forecast capability. >

Approaching Etuaptmumk - introducing a consensus-based mixed method for health services research.

Abstract: With the recognized need for health systems' improvements in the circumpolar and indigenous context, there has been a call to expand the research agenda across all sectors influencing wellness and to recognize academic and indigenous knowledge through the research process. Despite being recognized as a distinct body of knowledge in international forums and across indigenous groups, examples of methods and theories based on indigenous knowledge are not well documented in academic texts or peer-reviewed literature on health systems. This paper describes the use of a consensus-based, mixed method with indigenous knowledge by an experienced group of researchers and indigenous knowledge holders who collaborated on a study that explored indigenous values underlying health systems stewardship. The method is built on the principles of Etuaptmumk or two-eyed seeing, which aim to respond to and resolve the inherent conflicts between indigenous ways of knowing and the scientific inquiry that informs the evidence base in health care. Mixed methods' frameworks appear to provide a framing suitable for research questions that require data from indigenous knowledge sources and western knowledge. The nominal consensus method, as a western paradigm, was found to be responsive to embedding of indigenous knowledge and allowed space to express multiple perspectives and reach consensus on the question at hand. Further utilization and critical evaluation of this mixed methodology with indigenous knowledge are required.