Aging-in-place: Perspectives from the construction industry

Older adults report a desire to remain within the preferred environment for as long as possible. This desire is referred to as aging-in-place. Aging-in-place integrates housing and care options. Factors affecting the ability to remain within the preferred environment include current home designs, access to housing choices, social support networks, and community services, to name a few. Research supports physical and psychosocial benefits of aging-in-place for the individual. Home modifications have the potential to influence the quality of life in a number of positive directions that range from personal mobility to community engagement. Modifications range from minor to significant. Financial resources, contractor interest and expertise, consumer awareness and consumer opportunity affect the degree of change. Increasingly, construction professionals express an interest in learning more about aging-in place. Queries ranged from obtaining a greater understanding of the meaning of the concept, impact of demographic change on housing stock, and increased awareness of universal design features. This paper presents findings from a survey administered to current members of the Canadian Home Builders’ Association – Calgary Regional Office. Within this presentation, we report findings on members understanding of demographic change and the effect of this change on the current and future housing stock. We discuss perceived barriers and benefits of the development of business models to support aging-in-place. Finally, we conclude with discussion of educational support to enhance the understanding of aging-in-place.

An Adaptive Scheme for Learning the Probability Threshold in Pattern Recognition

The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.

Future learning landscapes for architectural education: Linking space, place, pedagogy, technology + context

Diversification and expansion of global higher education in the 21st century, has resulted in Learning Landscapes for architectural education that can no longer be sustained by the traditional model. Changes have resulted because of surging student numbers, extensions to traditional curricula, evolving competency standards and accreditation requirements, and modified geographical and pedagogical boundaries. The influx of available new technology has helped to democratise knowledge, transforming when, where and how learning takes place. Pressures on government funded higher education budgets highlight the need for a critical review of the current approach to the design and use of learning environments. Efficient design of physical space contributes significantly to savings in provision, management and use of facilities, while also potentially improving pedagogical quality. The purpose of this research is to identify emerging trends in the design of future Learning Landscapes for architectural education in Australasia; to understand where and how students of architecture are likely to learn, in the future context. It explores the important linkages between space, place, pedagogy, technology and context, using a multi methodological qualitative research approach. An Australasian context study will explore the Learning Landscapes of 23 Schools of Architecture across Australia, New Zealand and Papua New Guinea. The focus of this paper is on the methodology which is being employed to undertake dynamic data collection for the study. The research will be determined through mapping all forms of architectural learning environments, pedagogical approaches and contextual issues, to bridge the gap between academic theory, and architectural design practice. An initial understanding that pedagogy is an intrinsic component imbedded within the design of learning environments, will play an important role. Active learning environments which are exemplified by the architectural design studio, support dynamic project based and collaborative connected learning models. These have recently become a lot more common in disciplines outside of design and the arts. It is anticipated, therefore, that the implications for this research may well have a positive impact far beyond the confines of the architectural studio learning environment.

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint-Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Timing of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms.

Odour emissions from anaerobic piggery ponds. 2: Improving estimates of emission rate through recognition of spatial variability

Odour emission rates were measured for seven different anaerobic ponds treating piggery wastes at six to nine discrete locations across the surface of each pond on each sampling occasion over a thirteen month period. Significant variability in emission rates were observed for each pond. Measurement of a number of water quality variables in pond liquor samples collected at the same time and from the same locations as the odour samples indicated that the composition of the pond liquor was also variable. The results indicated that spatial variability was a real phenomenon and could have a significant impact on odour assessment practices. Considerably more odour samples would be required to characterise pond emissions than currently recommended by most practitioners, or regulatory agencies.

Differential expression profiling of components associated with exoskeletal hardening in crustaceans

Background: Exoskeletal hardening in crustaceans can be attributed to mineralization and sclerotization of the organic matrix. Glycoproteins have been implicated in the calcification process of many matrices. Sclerotization, on the other hand, is catalysed by phenoloxidases, which also play a role in melanization and the immunological response in arthropods. Custom cDNA microarrays from Portunus pelagicus were used to identify genes possibly associated with the activation pathways involved in these processes. Results: Two genes potentially involved in the recognition of glycosylation, the C-type lectin receptor and the mannose-binding protein, were found to display molt cycle-related differential expression profiles. C-type lectin receptor up-regulation was found to coincide with periods associated with new uncalcified cuticle formation, while the up-regulation of mannose-binding protein occurred only in the post-molt stage, during which calcification takes place, implicating both in the regulation of calcification. Genes presumed to be involved in the phenoloxidase activation pathway that facilitates sclerotization also displayed molt cycle-related differential expression profiles. Members of the serine protease superfamily, trypsin-like and chymotrypsin-like, were up-regulated in the intermolt stage when compared to post-molt, while trypsin-like was also up-regulated in pre-molt compared to ecdysis. Additionally, up-regulation in pre- and intermolt stages was observed by transcripts encoding other phenoloxidase activators including the putative antibacterial protein carcinin-like, and clotting protein precursor-like. Furthermore, hemocyanin, itself with phenoloxidase activity, displayed an identical expression pattern to that of the phenoloxidase activators, i.e. up-regulation in pre- and intermolt. Conclusion: Cuticle hardening in crustaceans is a complex process that is precisely timed to occur in the post-molt stage of the molt cycle. We have identified differential expression patterns of several genes that are believed to be involved in biomineralization and sclerotization and propose possible regulatory mechanisms for these processes based on their expression profiles, such as the potential involvement of C-type lectin receptors and mannose binding protein in the regulation of calcification.

A computational algorithm for the verification of tautologies in propositional calculus

A computational algorithm (based on Smullyan's analytic tableau method) that varifies whether a given well-formed formula in propositional calculus is a tautology or not has been implemented on a DEC system 10. The stepwise refinement approch of program development used for this implementation forms the subject matter of this paper. The top-down design has resulted in a modular and reliable program package. This computational algoritlhm compares favourably with the algorithm based on the well-known resolution principle used in theorem provers.

A new algorithm for parallel solution of linear equations

Abstract is not available.

Enhancing human action recognition with region proposals

Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.

An On-Line Algorithm for the Location of Cross Point Faults in Programmable Logic Arrays

An on-line algorithm is developed for the location of single cross point faults in a PLA (FPLA). The main feature of the valgorithm is the determination of a fault set corresponding to the response obtained for a failed test. For the apparently small number of faults in this set, all other tests are generated and a fault table is formed. Subsequently, an adaptive procedure is used to diagnose the fault. Functional equivalence test is carried out to determine the actual fault class if the adaptive testing results in a set of faults with identical tests. The large amount of computation time and storage required in the determination, a priori, of all the fault equivalence classes or in the construction of a fault dictionary are not needed here. A brief study of functional equivalence among the cross point faults is also made.

An (O)over-tilde(mn) Gomory-Hu Tree Construction Algorithm for Unweighted Graphs

We present a fast algorithm for computing a Gomory-Hu tree or cut tree for an unweighted undirected graph G = (V, E). The expected running time of our algorithm is (O) over tilde (mc) where vertical bar E vertical bar = m and c is the maximum u-v edge connectivity, where u, v is an element of V. When the input graph is also simple (i.e., it has no parallel edges), then the u-v edge connectivity for each pair of vertices u and v is at most n - 1; so the expected run-ning time of our algorithm for simple unweighted graphs is (O) over tilde (mn). All the algorithms currently known for constructing a Gomory-Hu tree [8, 9] use n - 1 minimum s-t cut (i.e., max flow) subroutines. This in conjunction with the current fastest (O) over tilde (n(20/9)) max flow algorithm due to Karger and Levine[11] yields the current best running time of (O) over tilde (n(20/9)n) for Gomory-Hu tree construction on simple unweighted graphs with m edges and n vertices. Thus we present the first (O) over tilde (mn) algorithm for constructing a Gomory-Hu tree for simple unweighted graphs. We do not use a max flow subroutine here; we present an efficient tree packing algorithm for computing Steiner edge connectivity and use this algorithm as our main subroutine. The advantage in using a tree packing algorithm for constructing a Gomory-Hu tree is that the work done in computing a minimum Steiner cut for a Steiner set S subset of V can be reused for computing a minimum Steiner cut for certain Steiner sets S' subset of S.

Learning Optimal Discriminant Functions through a Cooperative Game of Automata

The problem of learning correct decision rules to minimize the probability of misclassification is a long-standing problem of supervised learning in pattern recognition. The problem of learning such optimal discriminant functions is considered for the class of problems where the statistical properties of the pattern classes are completely unknown. The problem is posed as a game with common payoff played by a team of mutually cooperating learning automata. This essentially results in a probabilistic search through the space of classifiers. The approach is inherently capable of learning discriminant functions that are nonlinear in their parameters also. A learning algorithm is presented for the team and convergence is established. It is proved that the team can obtain the optimal classifier to an arbitrary approximation. Simulation results with a few examples are presented where the team learns the optimal classifier.

The con-stitutional re-cognition (s)cam-pain: The campaign for the hidden recognition of first nations peoples' racial inferiority

The constitutional recognition campaign has received party-wide support and its efforts have been promoted by Prime Minister Tony Abbott as being something that would ‘complete our Constitution.’ The broader rhetoric surrounding this campaign suggests that it will result in a just, albeit delayed, recognition of indigenous peoples in the Australian legal system. However, beneath the surface of this seemingly benevolent gesture, is a reaffirmation of the colonial subordination and erasure of the several hundred original nations’ peoples and ways of being.

Kasvilajien tunnistaminen, oppiminen ja opettaminen yleissivistävän koulutuksen näkökulmasta

The purpose of the research was to determine how well Finnish pupils and students of different ages recognize plant species, which variables explain recognition of plant species, what plants and nature mean to the subjects and how plant species identification should be taught in general education in Finland. The subjects were pupils from: every class level of the primary schools (grades 1 6); lower- secondary school (grades 7 9); high school (grades I II); university departments of teacher education and classroom teachers and teachers from university involved with environmental teaching and also experts from education and botany. A total of 883 people took part in the research. Both quantitative and qualitative research methods were used. The quantitative methods were: a) plant species recognition test, where 70 plant species photos were shown to subjects and b) an experiment in which three experimental groups had a plant recognition test on the nature trail and the three comparison groups were tested on recognition of the same species in classroom. The testing materials consisted of 31 real plants outdoors and 31 photos taken of these real plant species that were shown to pupils from fourth, fifth and sixth classes (grade levels) from primary school. The qualitative methods were a questionnaire administered to pupils from elementary school and high school and students from the department of teacher education, to teachers from university and interviews, where 3 5 pupils and students who recognized the plant species best or worst in the recognition test were selected to be interviewed. Furthermore, classroom teachers from primary school and experts were interviewed. The research results showed that on average plant species were recognized insufficiently on every level of education. There was also variation between answers from primary school to university teachers. However, species recognition skills improved from primary school to university teachers. Among other things, sex and place of residence explained species recognition skills, because girls and pupils from rural areas knew plant species statistically significantly better than boys or pupil from cities. Almost every pupil, student and all classroom teachers wanted to recognize plant species better. Many pupils mentioned that a motivating teaching method would be to go outdoors and investigate the plant species themselves. University teachers and experts also mentioned that the best and most efficient learning and teaching method for species recognition skills, is to practice in nature. We should teach plant species in nature, using many senses and teaching methods. Also new technology could be used in teaching species recognition skills. Keywords: plant species recognition, plant species education, general education