Kolme kaupallista analyysiohjelmaa ekologeille

Tietokoneohjelman arvostelu.

Defense reaction induced by a metabotropic glutamate receptor agonist microinjected into the dorsal periaqueductal gray of rats

The behavioral effects of trans-(±)-1-amino-1,3-cyclopentanedicarboxylic acid (t-ACPD), a metabotropic glutamate receptor (mGluR) agonist, or 0.9% (w/v) saline, injected into the dorsal periaqueductal gray (DPAG), was investigated. Male Wistar rats showed defense reactions characterized by jumps toward the top edges of the cages (saline = 0 vs t-ACPD = 6.0, medians P<0.05) and gallops (saline = 0 vs t-ACPD = 10.0, medians P<0.05) during the 60-s period after the beginning of the injection. In another experiment animals were placed inside an open arena for 5 min immediately after injection. Their behavior was recorded by a video camera and a computer program analyzed the videotapes. Eleven of fifteen rats injected with t-ACPD showed a short-lasting (about 1 min) flight reaction. No saline-treated animal showed this reaction (P<0.0005, chi-square test). The drug induced an increase in turning behavior (P = 0.002, MANOVA) and a decrease in the number of rearings (P<0.001, MANOVA) and grooming episodes (P<0.001, MANOVA). These results suggest that mGluRs play a role in the control of defense reactions in the DPAG.

Generalization of temporal order detection skill learning: two experimental studies of children with dyslexia

The objective of this study was to investigate the phenomenon of learning generalization of a specific skill of auditory temporal processing (temporal order detection) in children with dyslexia. The frequency order discrimination task was applied to children with dyslexia and its effect after training was analyzed in the same trained task and in a different task (duration order discrimination) involving the temporal order discrimination too. During study 1, one group of subjects with dyslexia (N = 12; mean age = 10.9 ± 1.4 years) was trained and compared to a group of untrained dyslexic children (N = 28; mean age = 10.4 ± 2.1 years). In study 2, the performance of a trained dyslexic group (N = 18; mean age = 10.1 ± 2.1 years) was compared at three different times: 2 months before training, at the beginning of training, and at the end of training. Training was carried out for 2 months using a computer program responsible for training frequency ordering skill. In study 1, the trained group showed significant improvement after training only for frequency ordering task compared to the untrained group (P < 0.001). In study 2, the children showed improvement in the last interval in both frequency ordering (P < 0.001) and duration ordering (P = 0.01) tasks. These results showed differences regarding the presence of learning generalization of temporal order detection, since there was generalization of learning in only one of the studies. The presence of methodological differences between the studies, as well as the relationship between trained task and evaluated tasks, are discussed.

Exchange energy calculation of He-He with supermolecular one-matrix

Exch~nge energy of the He-He system is calculated using the one-density matrix which has been modified according to the supermolecular density formula quoted by Kolos. The exchange energy integrals are computed analytically and by the Monte Carlo method. The results obtained from both ways compared favourably,with the results obtained from the SCF program HONDO

Equational Reasoning about Object-Oriented Programs

Formal verification of software can be an enormous task. This fact brought some software engineers to claim that formal verification is not feasible in practice. One possible method of supporting the verification process is a programming language that provides powerful abstraction mechanisms combined with intensive reuse of code. In this thesis we present a strongly typed functional object-oriented programming language. This language features type operators of arbitrary kind corresponding to so-called type protocols. Sub classing and inheritance is based on higher-order matching, i.e., utilizes type protocols as basic tool for reuse of code. We define the operational and axiomatic semantics of this language formally. The latter is the basis of the interactive proof assistant VOOP (Verified Object-Oriented Programs) that allows the user to prove equational properties of programs interactively.

Using HeadSprout Early Reading with a child with Autism Spectrum Disorder: An examination of phonological awareness, participant engagement, and participant enjoyment

This study examined the effectiveness of a 9-week reading program in improving the phonological awareness (PA) skills of a seven year old boy with Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and Oppositional Defiant Disorder (ODD). The study’s secondary goal was to describe how the participant engaged with and enjoyed the HeadSprout computer program. The participant attended a one hour reading program incorporating 30 minutes of HeadSprout Early Reading three days a week for 9 weeks. Results demonstrated that the participant’s PA scores increased from the 16th percentile at pre-test to the 35th percentile post program. Four of five measures of PA increased, segmenting nonwords decreased to the 2nd percentile post program. Momentary time sampling procedures revealed the participant was engaged with the computer program 94.5% of the time. Perceived ratings of enjoyment indicated the participant enjoyed using the program. Specific components of the program which may have influenced participant enjoyment and engagement are discussed. Study limitations and implications of these findings are discussed in reference to future research.

Development of the Physical Activity Interactive Recall (PAIR) for Aboriginal children

Affiliation: Margaret Cargo : Département de médecine sociale et préventive, Faculté de médecine, Université de Montréal

La importancia de las tecnologías de información y comunicación (TIC) en la didáctica del español como lengua extranjera (ELE)

La bibliographie comprends des adresses web consultables en ligne

Temporalité et surveillance dans l'art de David Rokeby

Pour respecter les droits d'auteur, la version électronique de ce mémoire à été dépouillée de ses documents visuels et audio-visuels. La version intégrale du mémoire a été déposée au Service de la gestion des documents et des archives de l'Université de Montréal.

Réseaux de neurones à relaxation entraînés par critère d'autoencodeur débruitant

L’apprentissage machine est un vaste domaine où l’on cherche à apprendre les paramètres de modèles à partir de données concrètes. Ce sera pour effectuer des tâches demandant des aptitudes attribuées à l’intelligence humaine, comme la capacité à traiter des don- nées de haute dimensionnalité présentant beaucoup de variations. Les réseaux de neu- rones artificiels sont un exemple de tels modèles. Dans certains réseaux de neurones dits profonds, des concepts "abstraits" sont appris automatiquement. Les travaux présentés ici prennent leur inspiration de réseaux de neurones profonds, de réseaux récurrents et de neuroscience du système visuel. Nos tâches de test sont la classification et le débruitement d’images quasi binaires. On permettra une rétroac- tion où des représentations de haut niveau (plus "abstraites") influencent des représentations à bas niveau. Cette influence s’effectuera au cours de ce qu’on nomme relaxation, des itérations où les différents niveaux (ou couches) du modèle s’interinfluencent. Nous présentons deux familles d’architectures, l’une, l’architecture complètement connectée, pouvant en principe traiter des données générales et une autre, l’architecture convolutionnelle, plus spécifiquement adaptée aux images. Dans tous les cas, les données utilisées sont des images, principalement des images de chiffres manuscrits. Dans un type d’expérience, nous cherchons à reconstruire des données qui ont été corrompues. On a pu y observer le phénomène d’influence décrit précédemment en comparant le résultat avec et sans la relaxation. On note aussi certains gains numériques et visuels en terme de performance de reconstruction en ajoutant l’influence des couches supérieures. Dans un autre type de tâche, la classification, peu de gains ont été observés. On a tout de même pu constater que dans certains cas la relaxation aiderait à apprendre des représentations utiles pour classifier des images corrompues. L’architecture convolutionnelle développée, plus incertaine au départ, permet malgré tout d’obtenir des reconstructions numériquement et visuellement semblables à celles obtenues avec l’autre architecture, même si sa connectivité est contrainte.

Circulation in the indian ocean in relation to the monsoon circulation of the atmosphere

The present thesis is an attempt by the researcher to Investigate the surface circulation of the Indian Ocean, north of 2095 in relation to the atmospheric circulation over the ocean. The aim is achieved by working out the circu1ation pattern and correlating it with the computed wind stress and its vorticity. The month wise surface circulation is arrived by drawing the streamlines, using freshand method with superimposed isotache. The zonal ad meridional componance of the wind stress and the curl of the wind stress are computed for each month over 2° latitude longitude quadrangle from the bulk aerodynamic formula, using a computer program. The data for drawing the surface circu1ation and for computing the wind stress and its curl have come from the Dutch Atlas.

KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods

KAM is a computer program that can automatically plan, monitor, and interpret numerical experiments with Hamiltonian systems with two degrees of freedom. The program has recently helped solve an open problem in hydrodynamics. Unlike other approaches to qualitative reasoning about physical system dynamics, KAM embodies a significant amount of knowledge about nonlinear dynamics. KAM's ability to control numerical experiments arises from the fact that it not only produces pictures for us to see, but also looks at (sic---in its mind's eye) the pictures it draws to guide its own actions. KAM is organized in three semantic levels: orbit recognition, phase space searching, and parameter space searching. Within each level spatial properties and relationships that are not explicitly represented in the initial representation are extracted by applying three operations ---(1) aggregation, (2) partition, and (3) classification--- iteratively.

Predicting sense of community and participation by applying machine learning to open government data

Community capacity is used to monitor socio-economic development. It is composed of a number of dimensions, which can be measured to understand the possible issues in the implementation of a policy or the outcome of a project targeting a community. Measuring community capacity dimensions is usually expensive and time consuming, requiring locally organised surveys. Therefore, we investigate a technique to estimate them by applying the Random Forests algorithm on secondary open government data. This research focuses on the prediction of measures for two dimensions: sense of community and participation. The most important variables for this prediction were determined. The variables included in the datasets used to train the predictive models complied with two criteria: nationwide availability; sufficiently fine-grained geographic breakdown, i.e. neighbourhood level. The models explained 77% of the sense of community measures and 63% of participation. Due to the low geographic detail of the outcome measures available, further research is required to apply the predictive models to a neighbourhood level. The variables that were found to be more determinant for prediction were only partially in agreement with the factors that, according to the social science literature consulted, are the most influential for sense of community and participation. This finding should be further investigated from a social science perspective, in order to be understood in depth.

Can you tell if they're learning?

The proliferation of Web-based learning objects makes finding and evaluating online resources problematic. While established Learning Analytics methods use Web interaction to evaluate learner engagement, there is uncertainty regarding the appropriateness of these measures. In this paper we propose a method for evaluating pedagogical activity in Web-based comments using a pedagogical framework, and present a preliminary study that assigns a Pedagogical Value (PV) to comments. This has value as it categorises discussion in terms of pedagogical activity rather than Web interaction. Results show that PV is distinct from typical interactional measures; there are negative or insignificant correlations with established Learning Analytics methods, but strong correlations with relevant linguistic indicators of learning, suggesting that the use of pedagogical frameworks may produce more accurate indicators than interaction analysis, and that linguistic rather than interaction analysis has the potential to automatically identify learning behaviour.

On lions, impala, and bigraphs: modelling interactions in Ubiquitous Computing

As ubiquitous systems have moved out of the lab and into the world the need to think more systematically about how there are realised has grown. This talk will present intradisciplinary work I have been engaged in with other computing colleagues on how we might develop more formal models and understanding of ubiquitous computing systems. The formal modelling of computing systems has proved valuable in areas as diverse as reliability, security and robustness. However, the emergence of ubiquitous computing raises new challenges for formal modelling due to their contextual nature and dependence on unreliable sensing systems. In this work we undertook an exploration of modelling an example ubiquitous system called the Savannah game using the approach of bigraphical rewriting systems. This required an unusual intra-disciplinary dialogue between formal computing and human- computer interaction researchers to model systematically four perspectives on Savannah: computational, physical, human and technical. Each perspective in turn drew upon a range of different modelling traditions. For example, the human perspective built upon previous work on proxemics, which uses physical distance as a means to understand interaction. In this talk I hope to show how our model explains observed inconsistencies in Savannah and ex- tend it to resolve these. I will then reflect on the need for intradisciplinary work of this form and the importance of the bigraph diagrammatic form to support this form of engagement. Speaker Biography Tom Rodden Tom Rodden (rodden.info) is a Professor of Interactive Computing at the University of Nottingham. His research brings together a range of human and technical disciplines, technologies and techniques to tackle the human, social, ethical and technical challenges involved in ubiquitous computing and the increasing used of personal data. He leads the Mixed Reality Laboratory (www.mrl.nott.ac.uk) an interdisciplinary research facility that is home of a team of over 40 researchers. He founded and currently co-directs the Horizon Digital Economy Research Institute (www.horizon.ac.uk), a university wide interdisciplinary research centre focusing on ethical use of our growing digital footprint. He has previously directed the EPSRC Equator IRC (www.equator.ac.uk) a national interdisciplinary research collaboration exploring the place of digital interaction in our everyday world. He is a fellow of the British Computer Society and the ACM and was elected to the ACM SIGCHI Academy in 2009 (http://www.sigchi.org/about/awards/).