It's my pleasure to invite you all to the last Psst seminar this academic year:
Final Psst! 19:
(29 Mar, 1:15 PM, EM 3.06)
Rajiv Murali
The causes of system failure are typically rooted in the complex structures of software systems and their world contexts. An approach to problem analysis is presented in which problems are decomposed into sub problems of recognized classes. These classes can be captured by problem frames, which identify domain structures and interfaces in the problem world. In this presentation, we will investigate this approach using the Avionics Control System (BAE Systems), and we address how Problem Frames can be used to identify potential system failures and mitigate it.
Xinghui Dong: Human Perception Based Computational Texture Similarity Evaluation under a Unified Framework
Texture similarity is very commonplace in the fields of texture classification and retrieval.
In our study, we first compare similarity matrices obtained by a series of either classical or state-of-the-art computational feature extraction algorithms with those acquired in the free grouping and pairs of pairs experiments under a unified evaluation framework. Experimental results show that nearly all these approaches cannot agree on human perceptual similarity matrices well enough. The highest agreement rate obtained by these methods on 5 different resolutions and the combination of all 5 resolutions is 68.2%.
Another human-involved experiment is conducted then in order to investigate what factors will influence human perceptual texture similarity. In this part, 82 texture pairs which are most difficult for most computational approaches to agree on perceptual data are selected to be stimuli. 98 words which are divided into 11 groups are presented to participants and can be chosen at will by them to describe the similarity between each given texture pair. Four groups of words are used most frequently, including regular, lined, netlike and bumpy (in sequence of frequencies). It is obviously that regularity, directionality and bumpiness are very important for human to perceive similarity of textures involved in this study. However, all existed computational algorithms investigated here cannot perform comparatively.
Eshrag Refaee : Knowledge Gathering with Visual Techniques
Recognising the vital role that visualisation plays to capture, represent, and analyse complex data in clear structure has provided a strong foundation towards the information visualisation. Visualisation is a type of the non-verbal communication methods that provide means of retrieving pictures to facilitate wordless communication. Scientifically, the right part of our brains is responsible about the visual type of thinking, and it is also responsible about the emotions and the intuitive thinking. This implies that the visual thinking approach was not recently established, nor at any particular time, but it is built-into our minds to allow human beings interacting with each other and with their environment. The recognition of this remarkable feature has led to a powerful revolution in the visual thinking, which might have great implications in various fields like information gathering, education, and special needs communication languages. Consequently, new concepts have been emerged and seriously considered i.e. rich pictures, visual language, image scheme, concept map, and image streaming.
Addressing the field-related social aspects has become an issue of importance in a variety of domains. The degree of accuracy and completeness of the captured information is significantly important for the field researcher. In this context, questionnaires have been identified as one of the most common methods applied to gather individual responses. popularity of the questionnaires might have a negative impact on the response rate. In addition, the possibility of having responses that might result in inaccurate or inconclusive results is a considerable risk. Such drawbacks have inspired researchers to attempt to evolve more effective research tools. For instance, the use of visualisation could play a major role as a powerful instrument in educational, personal, and commercial uses.
In this research, we aim to employ the features of rich picture(s) (RP) that have been introduced as a visual representation of a complex problem situation. RP is distinguished by its ability to capture detailed cultural and social aspects that represent individual’s view in a more comprehensive pattern than the conventional approaches. We assume that we can emerge the features of questionnaires and RP to develop a visual questionnaire by comparing their key features. We also aim to examine and validate the ability of this approach in capturing as rich and accurate information as possible.
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