The news cultures, productions and dissemination channels in the digital age are already different from the traditional times. The challenges which the reporters face also differ from the pasts. Taiwan media studies analyze the audience and media through the ways of qualification but neglects that they are also the audience, disseminators, gatekeepers and real constructional signs as the reporters in the meantime to go on the qualitative analysis. There are few studies about the press photographers and mostly the analyses of qualification and qualitative are based on the characters thinking. The study target is focused on newspaper photographers which basis is visual culture studies and uses it to the well-established Zaltman Metaphor Elicitation Technique (ZMET) from overseas. It uses the images as the media and brings out the deep thoughts and feelings of the interviewees to analyze the mental map of the press photographers and create a common map. Then, it carries out the pre-tests of the qualitative studies of the mental maps of the press photographers and builds up the role models from them in the digital age. Finally, it indicates the current media surroundings and the circumstances of the press photographers to seek the possibilities of media reformation. From the studies, we can know that there are six values of the press photographers through observing their mental and common maps: ¡§the values of existence,¡¨ ¡§news ethicalities,¡¨ ¡§respects,¡¨ ¡§the sense of achievements,¡¨ ¡§entertainment,¡¨ and ¡§arts.¡¨ Among which the press photographers cares about most is ¡§the values of existence.¡¨ However, the value of existence relies on the professional dimensions which lower the standard techniques of photo shooting due to the speed of the digital technology and the evolutions of the mechanical functions. Moreover, the images are rampant in the age of map reading and the publishers demand a big number of images, and therefore, the requests of the image contents only focus on the evidences but overlook the visual images. It not only leads the press photographers to have the insecurity of being replaced but also increases the stresses to them in the digital age of speed demanding and keen competitiveness. On the other hand, it is necessary to record dynamic images to put in e-papers, so the publishers ask the press photographers to do static photography and record dynamic images simultaneously which result in a working disaster from technology. Under this circumstance, the press photographers have to create their own values of existence beyond their photography technology to enhance their irreplaceability. They have to maintain their competitiveness in the working field to keep themselves from being eliminated. Also, the publishers shall promote the demands of the image contents instead of asking the press photographers to film many photos without visual effects. The publishers should establish new departments for the demands of static photos and recordings from e-papers to filter the adequate videos for broadcasting. Besides, send the professional DV photographers to interview and film by professional HDV in order to promote the professional dimension to reach the targets of operating diversified media.

La mise à disposition d'information et de services spatiaux a récemment proliféré sur le web dans la mesure où la plupart de nos activités quotidiennes sont géo-réferencées. Les communautés d'utilisateurs de services spatiaux sur le web sont de plus larges et variées, en constante expansion et transformation avec une augmentation constante des gammes d'applications proposées. Cette profusion d'applications entraîne un nombre important de problématiques de recherche, et notamment celles liées à l'identification des intérêts et des préférences de l'utilisateur, afin d'adapter les services délivrés aux besoins du client. Cette recherche propose une architecture intégrée de modélisation de profils d'utilisateur et d'approximation de leurs préférences, et de mise à disposition de services personnalisés orientés vers l'information spatiale. L'architecture proposée se compose d'un service de personnalisation et d'un modèle sémantique orienté utilisateur. Ces deux composants communiquent des informations sur l'utilisateur par des processus interactifs. Ce service de personalisation est basé sur trois principes : la mémoire associative neurale bi-directionnelle, des mesures contextuelles et spatiales orientées-utilisateur de proximité et de similarité, des schémas d'image et des concepts d'affordance. Ces concepts sont implémentés à partir d'une interface utilisateur qui intègre les différents composants identifiés, et offre un éventail de stratégies personnalisées de recherche, et un moteur hybride de personnalisation. Le modèle d'utilisateur utilise des logiques expressives de description pour caractériser les différentes catégories d'utilisateur, afin d'adapter les besoins d'utilisateur aux exigences d'une application. Un scénario dans le domaine du tourisme et un prototype Java réalisent une validation expérimentale de notre recherche à partir de techniques de personnalisation.

Actualmente existe un gran número de técnicas y herramientas para realizar estimaciones en los procesos de software, pero muchas de ellas requieren de gran volumen de información del proyecto que se está analizando, dificultando una estimación temprana del esfuerzo requerido para desarrollar dicho proyecto. Aquellos analistas que trabajan con el Léxico Extendido del Lenguaje, al contar con este modelo en etapas tempranas del software, pueden inferir ciertas características del proyecto, como pueden ser los Casos de Uso, las clases y entidades de base de datos que formaran parte del diseño del proyecto. Por otro lado, existen técnicas de estimación de esfuerzo ampliamente utilizadas y estandarizadas que se valen de estas características, como por ejemplo Puntos Caso de Uso, pero que en una etapa temprana de elicitación de requerimientos no son aplicables por falta de información. Este trabajo pretende brindar a los usuarios que utilizan Léxico Extendido del Lenguaje en su proceso de elicitación de requerimientos, una herramienta que, a partir de la información recabada en las etapas tempranas de dicho proceso, proporcione una estimación del esfuerzo necesario para realizar el proyecto, basada en un método ampliamente utilizado y estandarizado.

How do mathematics teachers present themselves? The construct of identity–the stories mathematics teachers tell about themselves and their practice–is an important and understudied construct in understanding mathematics teaching. This study investigates the use of photo-elicitation/photovoice interviews with six high school algebra teachers. Each teacher captured or chose photographs of their “world”, then presented them during a formal interview. The teachers framed their mathematics teacher identity through three connected story types: Public Stories, the stories a teacher presents about their practice within a professional register, Private Stories, the stories about personal connections to practice shared only in closed spaces, and Touchstone Stories, the important stories a teacher constantly references but rarely shares. I found these teachers’ stories contained little about mathematics content or actual classroom practice. Rather, they positioned the teachers as isolated in their profession; the themes were about pain, being “othered”, or feeling powerless. Framing the identities of these six mathematics teachers through visual stories presented them as real, struggling humans. I posit this process of eliciting mathematics teaching identity through visual narrative is important to the field of mathematics education for three reasons: framing their identities helps mathematics teachers understand the complex lives of their own students, these narratives showcase the uniqueness of each mathematics teacher as an individual, and this process of telling stories is an empowering form of reflection. / text

In the modern world, making informed decisions requires obtaining and aggregating relevant information about events of interest. For many political, business, and entertainment events, the information of interest only exists as opinions, beliefs, and judgments of dispersed individuals, and we can only get a complete picture by putting the separate pieces of information together. Thus, an important first step towards decision making is motivating the individuals to reveal their private information and coalescing the separate pieces of information together. In this dissertation, I study three information elicitation and aggregation methods, prediction markets, peer prediction mechanisms, and adaptive polling, using both theoretical and applied approaches. These methods mainly differ by their assumptions on the participants' behavior, namely whether the participants possess noisy or perfect information and whether they strategically decide on what information to reveal. The first two methods, prediction markets and peer prediction mechanisms, assume that the participants are strategic and have perfect information. Their primary goal is to use carefully designed monetary rewards to incentivize the participants to truthfully reveal their private information. As a result, my studies of these methods focus on understanding to what extent are these methods incentive compatible in theory and in practice. The last method, adaptive polling, assumes that the participants are not strategic and have noisy information. In this case, our goal is to accurately and efficiently estimate the latent ground truth given the noisy information, and we aim to evaluate whether this goal can be achieved by using this method experimentally. I make four main contributions in this dissertation. First, I theoretically analyze how the participants' knowledge of one another's private information affects their strategic behavior when trading in a prediction market with a finite number of participants. Each participant may trade multiple times in the market, and hence may have an incentive to withhold or misreport his information in order to mislead other participants and capitalize on their mistakes. When the participants' private information is unconditionally independent, we show that the participants reveal their information as late as possible at any equilibrium, which is arguably the worse outcome for the purpose of information aggregation. We also provide insights on the equilibria of such prediction markets when the participants' private information is both conditionally and unconditionally dependent given the outcome of the event. Second, I theoretically analyze the participants' strategic behavior in a prediction market when a participant has outside incentives to manipulate the market probability. The presence of such outside incentives would seem to damage the information aggregation in the market. Surprisingly, when the existence of such incentives is certain and common knowledge, we show that there exist separating equilibria where all the participants' private information is revealed and fully aggregated into the market probability. Although there also exist pooling equilibria with information loss, we prove that certain separating equilibria are more desirable than many pooling equilibria because the separating equilibria satisfy domination based belief refinements, maximize the social welfare of the setting, or maximize either participant's total expected payoff. When the existence of the outside incentives is uncertain, trust cannot be established and the separating equilibria no longer exist. Third, I experimentally investigate participants' behavior towards the peer prediction mechanisms, which were proposed to elicit information without observable ground truth. While peer prediction mechanisms promise to elicit truthful information by rewarding participants with carefully constructed payments, they also admit uninformative equilibria where coordinating participants provide no useful information. We conduct the first controlled online experiment of the Jurca and Faltings peer prediction mechanism, engaging the participants in a multiplayer, real-time and repeated game. Using a hidden Markov model to capture players' strategies from their actions, our results show that participants successfully coordinate on uninformative equilibria and the truthful equilibrium is not focal, even when some uninformative equilibria do not exist or result in lower payoffs. In contrast, most players are consistently truthful in the absence of peer prediction, suggesting that these mechanisms may be harmful when truthful reporting has similar cost to strategic behavior. Finally, I design and experimentally evaluate an adaptive polling method for aggregating small pieces of imprecise information together to produce an accurate estimate of a latent ground truth. In designing this method, we make two main contributions: (1) Our method aggregates the participants' noisy information by using a theoretical model to account for the noise in the participants' contributed information. (2) Our method uses an active learning inspired approach to adaptively choose the query for each participant. We apply this method to the problem of ranking a set of alternatives, each of which is characterized by a latent strength parameter. At each step, adaptive polling collects the result of a pairwise comparison, estimates the strength parameters from the pairwise comparison data, and adaptively chooses the next pairwise comparison question to maximize expected information gain. Our MTurk experiment shows that our adaptive polling method can effectively incorporate noisy information and improve the estimate accuracy over time. Compared to a baseline method, which chooses a random pairwise comparison question at each step, our adaptive method can generate more accurate estimates with less cost. / Engineering and Applied Sciences

Constructing a Bayesian Network requires the conditional probabilities table (CPT) to be acquired, one for each variable or node in the network. When data mining is not available, CPTs must be acquired from the domain experts. The complexity of the direct elicitation is exponential on the number of parents of a variable, making direct elicitation from human experts impractical for a large number of causes. Causal models such as Noisy-OR, Noisy-AND, Noisy-MIN, Noisy-MAX and Recursive Noisy-OR have been developed that allow CPTs acquisition to be achieved with linear complexity on the number of causes. Their representation power is measured by their ability to encode the causal interactions. Causal interactions can be categorized into two types: reinforcing and undermining. The Non-Impeding Noisy-AND or NIN-AND tree causal model, developed by Xiang and Jia, is capable of modeling both types of interaction while retaining the linear complexity. The main challenge in utilizing the NIN-AND tree model to generate a CPT is that it requires its tree topology to be elicited. A NIN-AND tree topology is an encoding of the causal interactions between the causes. In this work we present two methods, Structure Elimination (SE) and Pairwise Causal Interaction (PCI), that allow indirect elicitations of the NIN-AND tree topology using some additional probabilities elicited from experts. We conduct human-based experiment to investigate the e ectiveness of the two methods in terms of accuracy by comparing them to the Direct Numerical (DN) elicitation method. We recruit participants from second year Computer Science students at the University of Guelph. The process involves training a participant into domain expert using a known NIN-AND tree model then acquire another NIN-AND tree model by applying the SE and PCI methods. The CPTs produced by the acquired NIN-AND tree models are then compared to the one obtained by using the DN method. Comparable CPT accuracies are obtained among models generated by di erent methods, even though SE and PCI requires a much smaller number of parameters in comparison to DN.

No description available.

Second home use or cottaging is an increasingly desirable practice across Canada. In Manitoba, cottaging sub-divisions are generally situated along lakes and rivers in the province, many of which are situated on Crown land or in provincial parks. This study explored what is meaningful about cottaging to bring about a better understanding of the importance of cottaging as a culturally meaningful social practice. The objectives of the research were to identify what makes Flanders Lake and surrounding area of Nopiming Provincial Park a meaningful place for cottagers; determine if there are shared meanings among cottagers; and consider the implications of the cultural landscape of cottagers for natural resource management. The case study research considered the sense of place that is derived from cottagers’ experiences and what specifically contributes to the significance of cottage culture in the cottaging sub-division of Flanders Lake, Manitoba. A qualitative, interpretive research design was used for data collection. Photo-elicitation also known as resident employed photography was used, whereby cottagers were asked to photograph things, places or people that represented meaningful aspects about cottaging and the surrounding area. Semi-structured interviews were conducted with individual participants to validate and triangulate perspectives. Using NVivo 7 qualitative software to manage data and elicit themes, a cultural landscape framework of cottagers was developed. Cottagers cited recreational activities, connections with people, interactions with nature and the tonic-like effects of cottaging experiences, as the most meaningful aspects of cottaging. The study showed that it is possible to determine the most meaningful aspects of a place, and that many of those attributes are shared between community members. However, dissecting those meanings into constituent parts of a collective body of shared, interrelated and sometimes dependent meanings is complex, and not always possible. Further study on the cultural landscape of additional cottaging communities and of other area stakeholders is recommended given the increasing desirability and interest in cottaging, and potential for negotiating place meanings in multiple land use areas.

Data about the spatial variation of soil attributes is required to address a great number of environmental issues, such as improving water quality, flood mitigation, and determining the effects of the terrestrial carbon cycle. The need for a continuum of soils data is problematic, as it is only possible to observe soil attributes at a limited number of locations, beyond which, prediction is required. There is, however, disparity between the way in which much of the existing information about soil is recorded and the format in which the data is required. There are two primary methods of representing the variation in soil properties, as a set of distinct classes or as a continuum. The former is how the variation in soils has been recorded historically by the soil survey, whereas the latter is how soils data is typically required. One solution to this issue is to use a soil-landscape modelling approach which relates the soil to the wider landscape (including topography, land-use, geology and climatic conditions) using a statistical model. In this study, the soil-landscape modelling approach has been applied to the prediction of soil bulk density (Db). The original contribution to knowledge of the study is demonstrating that producing a continuous surface of Db using a soil-landscape modelling approach is that a viable alternative to the ‘classification’ approach which is most frequently used. The benefit of this method is shown in relation to the prediction of soil carbon stocks, which can be predicted more accurately and with less uncertainty. The second part of this study concerns the inclusion of expert knowledge within the soil-landscape modelling approach. The statistical modelling approaches used to predict Db are data driven, hence it is difficult to interpret the processes which the model represents. In this study, expert knowledge is used to predict Db within a Bayesian network modelling framework, which structures knowledge in terms of probability. This approach creates models which can be more easily interpreted and consequently facilitate knowledge discovery, it also provides a method for expert knowledge to be used as a proxy for empirical data. The contribution to knowledge of this section of the study is twofold, firstly, that Bayesian networks can be used as tools for data-mining to predict a continuous soil attribute such as Db and that in lieu of data, expert knowledge can be used to accurately predict landscape-scale trends in the variation of Db using a Bayesian modelling approach.

The purpose of this study was to evaluate the performance of adults with traumatic brain injury (TBI) on a spoken persuasive discourse task and to evaluate the affects of eliciting this language sample. Ten adults with TBI (mean age = 51 years and 5 months) and ten adults matched by age and gender completed two spoken language tasks. These tasks required them to verbally provide their opinion of whether trained animals in circuses should be allowed to perform for the public and also whether public transport should be encouraged for everyone to use. One of the tasks was provided with examples for and against the topic within the instructions whereas the other task instructions provided no examples. The presentation of these tasks was alternated within the groups so as not to assist with task practice. Language measures included productivity (total number of words, mean length of T-units, T-units per minute and percentage of T-units with mazes) and complexity (total number of clauses, clause density and clause type). Pragmatic measures included the essential features of argument as identified in the developmental literature (number of claims, reasons, elaborations, repetitions, irrelevancies, and presence of an introduction and conclusion). The TBI group out-performed their age-matched peers on language complexity measures of total number of clauses and independent clauses used, however used significantly more adverbial clauses. On comparison of the elicitation technique, the instructions with examples elicited a significantly greater number of reasons than that of the basic instructions. The results are discussed alongside current literature in the field of discourse production and persuasion. Implications for clinical practice and future directions for research in this area are also suggested.