36 resultados para Meaning Construction. Cognitive Domains. Discourse Pattern
Resumo:
There has been increasing interest in the discursive aspects of strategy over the last two decades. In this editorial we review the existing literature, focusing on six major bodies of discursive scholarship: post-structural, critical discourse analysis, narrative, rhetoric, conversation analysis and metaphor. Our review reveals the significant contributions of research on strategy and discourse, but also the potential to advance research in this area by bringing together research on discursive practices and research on other practices we know to be important in strategy work. We explore the potential of discursive scholarship in integrating between significant theoretical domains (sensemaking, power and sociomateriality), and realms of analysis (institutional, organizational and the episodic), relevant to strategy scholarship. This allows us to place the papers published in the special issue Strategy as Discourse: Its Significance, Challenges and Future Directions among the body of knowledge accumulated thus far, and to suggest a way forward for future scholarship.
Resumo:
I argue that the communication of given information is part of the procedural instructions conveyed by some connectives like the French puisque. I submit in addition that the encoding of givenness has cognitive implications that are visible during online processing. I assess this hypothesis empirically by comparing the way the clauses introduced by two French causal connectives, puisque and parce que, are processed during online reading when the following segment is ‘given’ or ‘new’. I complement these results by an acceptability judgement task using the same sentences. These experiments confirm that introducing a clause conveying given information is a core feature characterizing puisque, as the segment following it is read faster when it contains given rather than new information, and puisque is rated as more acceptable than parce que in such contexts. I discuss the implications of these results for future research on the description of the meaning of connectives.
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
Resumo:
Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied in other domains, such as medical image analysis. In this paper, we propose and evaluate a convolutional neural network (CNN), designed for the classification of ILD patterns. The proposed network consists of 5 convolutional layers with 2×2 kernels and LeakyReLU activations, followed by average pooling with size equal to the size of the final feature maps and three dense layers. The last dense layer has 7 outputs, equivalent to the classes considered: healthy, ground glass opacity (GGO), micronodules, consolidation, reticulation, honeycombing and a combination of GGO/reticulation. To train and evaluate the CNN, we used a dataset of 14696 image patches, derived by 120 CT scans from different scanners and hospitals. To the best of our knowledge, this is the first deep CNN designed for the specific problem. A comparative analysis proved the effectiveness of the proposed CNN against previous methods in a challenging dataset. The classification performance (~85.5%) demonstrated the potential of CNNs in analyzing lung patterns. Future work includes, extending the CNN to three-dimensional data provided by CT volume scans and integrating the proposed method into a CAD system that aims to provide differential diagnosis for ILDs as a supportive tool for radiologists.
Resumo:
Behavioural tests to assess affective states are widely used in human research and have recently been extended to animals. These tests assume that affective state influences cognitive processing, and that animals in a negative affective state interpret ambiguous information as expecting a negative outcome (displaying a negative cognitive bias). Most of these tests however, require long discrimination training. The aim of the study was to validate an exploration based cognitive bias test, using two different handling methods, as previous studies have shown that standard tail handling of mice increases physiological and behavioural measures of anxiety compared to cupped handling. Therefore, we hypothesised that tail handled mice would display a negative cognitive bias. We handled 28 female CD-1 mice for 16 weeks using either tail handling or cupped handling. The mice were then trained in an eight arm radial maze, where two adjacent arms predicted a positive outcome (darkness and food), while the two opposite arms predicted a negative outcome (no food, white noise and light). After six days of training, the mice were also given access to the four previously unavailable intermediate ambiguous arms of the radial maze and tested for cognitive bias. We were unable to validate this test, as mice from both handling groups displayed a similar pattern of exploration. Furthermore, we examined whether maze exploration is affected by the expression of stereotypic behaviour in the home cage. Mice with higher levels of stereotypic behaviour spent more time in positive arms and avoided ambiguous arms, displaying a negative cognitive bias. While this test needs further validation, our results indicate that it may allow the assessment of affective state in mice with minimal training— a major confound in current cognitive bias paradigms.
Resumo:
Identity is a recurrent research interest in current sociolinguistics and it is also of primary interest in digital discourse studies. Identity construction is closely related to stance and style (Eckert 2008; Jaffe 2009), which are fundamental concepts for understanding the language use and its social meanings in the case of social media users from Malaga. As the specific social meanings of a set of dialect features constitute a style, this style and the social (and technological) context in which the variants are used determine the meanings that are actually associated with each variant. Hence, every variant has its own indexical field covering any number of potential meanings. The Spanish spoken in Malaga, as Andalusian Spanish in general, was in the past often times considered an incorrect, low prestige variety of Spanish which was strongly associated with the poor, rural, backward South of Spain. This southern Spanish variety is easily recognised because of its innovative phonetic features that diverge from the national standard. In this study several of these phonetic dialect features are looked at, which users from Malaga purposefully employ (in a textualised form) on social media for identity construction. This identity construction is analysed through interactional and ethnographic methods: A perception and an imitation task served as key data and were supplemented by answers to a series of open questions. Further data stems from visual, multimodal elements (e.g. images, photos, videos) posted by users from the city of Malaga. The program TAMS Analyzer was used for data codification and analysis. Results show that certain features that in spoken language are considered rural and old-fashioned, acquire new meaning on social media, namely of urbanity and fashion. Moreover, these features, if used online, are associated with hipsters. That is, the “cool” social media index the “coolness” of the dialect features in question and, thus, the mediatisation makes their indexical fields even more multi-layered and dynamic. Social media users from Malaga performatively employ these stylised dialect features to project a hipster identity and certain related stances.