Publication Search Results

Now showing 1 - 2 of 2
  • (2022) Sunstrum, Frederique
    Understanding product semantics and affective perceptions of product consumers undoubtedly offer significant value for industrial designers and their design practice. Deconstructing affective perceptions is a methodologically challenging task as it is implicit and subjective and is influenced by an individual’s aesthetic experience. Accordingly, how products are perceived differs among individuals or consumers, particularly in the distinct experiences that contribute to constructing an individual’s sense of perception of self or self-concept. Furthermore, research has shown that individuals are implicitly drawn to products that reaffirm and communicate their self-concept. If an individual’s preferences for products can reflect or enhance their self-concept, this suggests that understanding the underlying perceptual processes between the self-concept and product semantics can productively inform industrial design research. The thesis research develops and adapts methods from the disciplines of psychology, marketing, and industrial design to investigate these underlying perceptual processes of the self-concept and its relationships to product semantics. The thesis research investigates the underlying processes through a study on kettles that discloses the variances in sensory and cognitive evaluation and judgements through the process of aesthetic experience. The thesis further investigates the cognitive influences of the self-concept to reveal the mental models associated with the visual aesthetics of product form and how this influences aesthetic responses through product personality congruence. The thesis argues that the self-concept is a multidimensional construct reflected, in particular, through an individual’s (1) gender identity, (2) personality, (3) aesthetic sensitivity, and (4) interest, taste, and goals, that plays a vital role in the aesthetic experience of products. The thesis’s findings indicate that these individual components of the self-concept are essential in that they interplay in how the symbolic meaning of product semantics is visually perceived. The outcome of this thesis assists in, primarily, revealing the underlying stages of visual aesthetic processing to understand how product semantics is perceived through an individual’s self-concept.

  • (2022) Ayat, Hooman
    Climate change is expected to change the intensity and frequency of heavy storms. Thus, understanding different characteristics of this phenomena (i.e., intensity, size, speed, direction, etc.) is vital for the effective climate adaptation. Many extreme storms have small areas and short lifetimes (sub-daily/hourly) and can have destructive impacts, especially over urban areas. Therefore, it is vital to understand the nature of changes in these extremes to reduce the risk of their destructive impacts on cities. The overarching goal of this thesis is to quantify various storm characteristics, including their changes, using radar and satellite observations. Using an object-based technique, I compare the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and ground radar based Multi-Radar Multi-Sensor Quantitative Precipitation Estimates (MRMS) over the United States and show that the object-based storm properties are not sensitive to the observational platforms. However, there are differences that are statistically significant. Secondly, I investigate the error sources associated with different types of contributing data in the IMERG during the hurricane days occurred in 2016-2018 with MRMS as the reference. The results show that IMERG have better agreement with MRMS during the passive microwave (PMW) observations compared to rainfall estimates come from the combination of the interpolation techniques and infrared observations (morph/IR). Also, the quality of morph/IR estimates deteriorates with the longer absence of PMW observations. Thirdly, I establish an object-based climatology of rain systems using radar data near Sydney, Australia. The results show that rain systems in different seasons have distinct object-based characteristics, and these differences are dependent on their source of origins and also their positions over land and ocean. Using a two-step clustering algorithm, I have found five system types over Sydney peaking in different seasons. While overall rainfall statistics don't show any link to climate modes, links do appear for some system types using a multivariate approach. Finally, I show that there is a robust increasing trend of 20% per decade in sub-hourly extreme rainfall in the Sydney region over 20 years, despite no evidence of trends on hourly or daily scales. I am able to obtain this new result via a novel analysis of long-term radar data, including cross-checking between neighboring radars.