Multimodal textbook design : analyzing the construction of the discourses of pharmacology

Includes bibliographical references.The aim of the research is to contribute to a pedagogy of Multiliteracies in the context of Health Sciences. A Multiliteracies approach sees text in terms of a process of 'redesigning' meaning from a range of available resources. These include multimodal semiotic resources such as visual and verbal modes, as well as particular discursive and social practices that the text draws upon. The study originates from a disagreement over which Pharmacology textbook fourth year medical students should use. The founding argument is that a Pharmacology textbook can be seen as constructing the discourses of the 'prescribing physician' As such, it simultaneously constructs and bears imprints of particular ideologies, discursive formations and social relations which are relevant in the field of medicine and science, as well as those from private and public life-worlds. As a teacher, I am interested in how the textbooks' ideologies contribute to or contest that of the new problem-based medical curriculum. I also analyze the respective designs in terms of their accessibility and suitability specifically for undergraduate medical students. The theoretical framework is provided by Fairclough's notion of 'orders of discourse' together with Halliday's metafunctional view of text, and is operationalized through a social semiotic analysis of sections of two textbooks. The textbooks analyzed are 'Pharmacology' by Rang et al ('Rang'), and 'the Oxford Textbook of Clinical Pharmacology and Drug therapy' ('Oxford'). I focus on the grammatical system of transitivity to construct the respective textbooks' views of social reality, and I use an analysis of modality in the texts to construct the social relations between writers, readers and the subject of Pharmacology. The analytical 'toolkit' includes verbal as well as visual semiotic resources within a framework of textual coherence. The study concludes that while Rang constructs social relations and identities that resonate with a contemporary society, its interest in Pharmacology is scientific rather than clinical. Furthermore, its design features may limit access specifically for undergraduate medical students. Oxford, on the other hand, is dominated by the discourses of clinical medicine and medical education. It constructs the subject of Pharmacology in terms of therapy or 'process', rather than in terms of drugs or 'products', and in this sense may be more suitable as a 'tutor'. However, it does not prepare the student for critical engagement with the changing social realities and relations of power in a post-Fordist society. The value of the study is two-fold. Firstly, it reiterates the importance of critical reflection on the various aspects of a curriculum. This includes reflection on alignment between the ideologies of textbooks and that of the new curriculum, and between curricular objectives, activities and assessment practices. Secondly, it has led to the operationalizing of a metalanguage of design, specifically in a Health Sciences context. This metalanguage may be used not l ' only for improving the communicative value of students' assignments, but also to expand their cultural perspectives through critical engagement with aspects of social identities and relations

Composition-guided image acquisition

textTo make a picture more appealing, professional photographers apply a wealth of photographic composition rules, of which amateur photographers are of- ten unaware. This dissertation aims at providing in-camera feedback to the amateur photographer while taking pictures. The proposed algorithms do not depend on prior knowledge of the indoor/outdoor setting or scene, and are amenable to software implementation on fixed-point programmable digital signal processors available in digital still cameras. The key enabling step in automating photographic composition rules is to locate the main subject. Digital still image acquisition maps the 3-D world onto a 2-D picture. By using the 2-D picture alone, segmenting the main subject without prior knowledge of the scene is ill-posed. Even with prior knowledge, segmentation is often computationally intensive and error prone. This dissertation defends the idea that reliable main subject segmenta- tion without prior knowledge of scene and setting may be achieved by acquiring a single picture, in which the optical system blurs objects not in the plane of focus. After segmentation, photographic composition rules may be automated. In this context, segmentation only needs to approximately and not precisely locate the main subject. In this dissertation, I combine optical and digital image processing to perform the segmentation of the main subject without prior knowledge of the scene. In particular, I propose to acquire a picture in which the main subject is in focus, and the shutter aperture is fully open. The lens optics will blur any object not in the plane of focus. For the acquired picture, I develop a computationally simple one-pass algorithm to segment the main subject. The post segmentation objective is to automate selected photographic composition rules. The algorithms can either be applied on the picture taken with the objects not in the plane of focus blurred, or on a user-intended picture with the same focal length settings. This way, in-camera feedback can be provided to the amateur photographer, in the form of alternate compositions of the same scene. I automate three photographic composition rules: (1) placement of the main subject obeying the rule-of-thirds, (2) background blurring to simulate the main subject being in motion or decrease the depth-of-field of the picture, and (3) merger detection and mitigation when equally focused main subject and background objects merge as one object. The primary contributions of the dissertation are in digital still image processing. The first is the automation of segmentation of the main subject in a single still picture assisted by optical pre-processing. The second is the automation of main subject placement, artistic background blur, and merger detection and mitigation to try to improve photographic composition.Electrical and Computer Engineerin

Hierarchical Structuring of Video Previews by Leading-Cluster-Analysis

3noClustering of shots is frequently used for accessing video data and enabling quick grasping of the associated content. In this work we first group video shots by a classic hierarchical algorithm, where shot content is described by a codebook of visual words and different codebooks are compared by a suitable measure of distortion. To deal with the high number of levels in a hierarchical tree, a novel procedure of Leading-Cluster-Analysis is then proposed to extract a reduced set of hierarchically arranged previews. The depth of the obtained structure is driven both from the nature of the visual content information, and by the user needs, who can navigate the obtained video previews at various levels of representation. The effectiveness of the proposed method is demonstrated by extensive tests and comparisons carried out on a large collection of video data. of digital videos has not been accompanied by a parallel increase in its accessibility. In this context, video abstraction techniques may represent a key components of a practical video management system: indeed a condensed video may be effective for a quick browsing or retrieval tasks. A commonly accepted type of abstract for generic videos does not exist yet, and the solutions investigated so far depend usually on the nature and the genre of video data.openopenBenini, Sergio; Migliorati, Pierangelo; Leonardi, RiccardoBenini, Sergio; Migliorati, Pierangelo; Leonardi, Riccard

Edge-enhancing image smoothing.

Xu, Yi.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (p. 62-69).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Organization --- p.4Chapter 2 --- Background and Motivation --- p.7Chapter 2.1 --- ID Mondrian Smoothing --- p.9Chapter 2.2 --- 2D Formulation --- p.13Chapter 3 --- Solver --- p.16Chapter 3.1 --- More Analysis --- p.20Chapter 4 --- Edge Extraction --- p.26Chapter 4.1 --- Related work --- p.26Chapter 4.2 --- Method and Results --- p.28Chapter 4.3 --- Summary --- p.32Chapter 5 --- Image Abstraction and Pencil Sketching --- p.35Chapter 5.1 --- Related Work --- p.35Chapter 5.2 --- Method and Results --- p.36Chapter 5.3 --- Summary --- p.40Chapter 6 --- Clip-Art Compression Artifact Removal --- p.41Chapter 6.1 --- Related work --- p.41Chapter 6.2 --- Method and Results --- p.43Chapter 6.3 --- Summary --- p.46Chapter 7 --- Layer-Based Contrast Manipulation --- p.49Chapter 7.1 --- Related Work --- p.49Chapter 7.2 --- Method and Results --- p.50Chapter 7.2.1 --- Edge Adjustment --- p.51Chapter 7.2.2 --- Detail Magnification --- p.54Chapter 7.2.3 --- Tone Mapping --- p.55Chapter 7.3 --- Summary --- p.56Chapter 8 --- Conclusion and Discussion --- p.59Bibliography --- p.6

Proof of Concept For the Use of Motion Capture Technology In Athletic Pedagogy

Visualization has long been an important method for conveying complex information. Where information transfer using written and spoken means might amount to 200-250 words per minute, visual media can often convey information at many times this rate. This makes visualization a potentially important tool for education. Athletic instruction, particularly, can involve communication about complex human movement that is not easily conveyed with written or spoken descriptions. Video based instruction can be problematic since video data can contain too much information, thereby making it more difficult for a student to absorb what is cognitively necessary. The lesson is to present the learner what is needed and not more. We present a novel use of motion capture animation as an educational tool for teaching athletic movements. The advantage of motion capture is its ability to accurately represent real human motion in a minimalist context which removes extraneous information normally found in video. Motion capture animation only displays motion information, not additional information regarding the motion context. Producing an “automated coach” would be too large and difficult a problem to solve within the scope of a Master's thesis but we can perform initial steps including producing a useful software tool which performs data analysis on two motion datasets. We believe such a tool would be beneficial to a human coach as an analysis tool and the work would provide some useful understanding of next important steps towards perhaps someday producing an automated coach

Higher level techniques for the artistic rendering of images and video

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Learning visual concepts for image classification

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (leaves 166-174).by Aparna Lakshmi Ratan.Ph.D

IST Austria Thesis

Deep neural networks have established a new standard for data-dependent feature extraction pipelines in the Computer Vision literature. Despite their remarkable performance in the standard supervised learning scenario, i.e. when models are trained with labeled data and tested on samples that follow a similar distribution, neural networks have been shown to struggle with more advanced generalization abilities, such as transferring knowledge across visually different domains, or generalizing to new unseen combinations of known concepts. In this thesis we argue that, in contrast to the usual black-box behavior of neural networks, leveraging more structured internal representations is a promising direction for tackling such problems. In particular, we focus on two forms of structure. First, we tackle modularity: We show that (i) compositional architectures are a natural tool for modeling reasoning tasks, in that they efficiently capture their combinatorial nature, which is key for generalizing beyond the compositions seen during training. We investigate how to to learn such models, both formally and experimentally, for the task of abstract visual reasoning. Then, we show that (ii) in some settings, modularity allows us to efficiently break down complex tasks into smaller, easier, modules, thereby improving computational efficiency; We study this behavior in the context of generative models for colorization, as well as for small objects detection. Secondly, we investigate the inherently layered structure of representations learned by neural networks, and analyze its role in the context of transfer learning and domain adaptation across visually dissimilar domains