Virtual influencers (VIs), computer-generated characters, can act as a medium to influence followers on social media platforms. This is a relatively novel phenomenon, with popular VIs having over six million followers. This study investigates VIs from the perspective of human-computer interaction. Nine participants from four countries were interviewed about their interactions with a variety of fictional VIs in different settings. The study uncovers new user perceptions and attitudes towards VIs, including pessimism towards VIs, loss of trust and likeability towards virtual characters, and the perception of VIs as being run by artificial intelligence (AI). It was found that content relating to fitness, personal tips, and social activism demands more transparency about the authority and agency of the VI from the users. Finally, this study discusses the ethical implications of VIs, highlights an avenue of research in the AI domain, and makes suggestions for human-computer interaction (HCI) practitioners curating social media experiences. / Virtuella influencers (VI), datorgenererade karaktärer, kan fungera som ett medium för att påverka följare på sociala medieplattformar. Detta är ett relativt nytt fenomen, där populära VI har över sex miljoner följare. Denna studie undersöker fenomenet VI ur människa-datorinteraktions perspektiv. Nio deltagare från fyra länder intervjuades om deras interaktioner med olika fiktiva VI i olika miljöer. Studien visar på nya uppfattningar och attityder från användare gentemot VI, inklusive pessimism gentemot VI, förlust av förtroende och gillande gentemot virtuella karaktärer, samt uppfattningen om att VI drivs av artificiell intelligens (AI). Det visade sig att användarna kräver att innehåll relaterat till träning, personliga tips och social aktivism kräver mer öppenhet om VI:s befogenhet och agenda. Slutligen diskuterar denna studie de etiska konsekvenserna av VI, belyser ett forskningsområde inom AI och ger förslag till utövare inom människa-datorinteraktion (HCI) som kuraterar sociala medieupplevelser

This single-session feasibility trial aimed to examine the effects of Directed-Imaginal Music Psychotherapy (DIMP) on self-awareness in relation to change in adults being treated for substance use disorder. DIMP is a two-part protocol. The first part is a live music, receptive intervention in which a trained music therapist plays a specified harmony sequence on guitar accompanied by verbal guidance to promote imagery and sensory experiences in participants. The verbal guidance is based on participant-defined “Comforts” in each of their five primary senses. The music and imagery component was followed by group verbal processing to discuss physical, emotional, or cognitive changes participant’s experience and gauge an understanding of insights into treatment gained by the participants. Participants completed the Self-Awareness Outcomes Questionnaire (SAOQ; Sutton, 2016) before and after the intervention to measure possible change in self-awareness in relation to change in their recovery. The Wilcoxon signed rank test indicated statically significant improvements in self-awareness scores from 3.37 pre-test to 3.77 post-test. Fieldnotes and transcripts from audio recordings were also used in thematic analysis. Deductive themes of Insight, Mindfulness, Reflection, and Rumination were taken from Sutton’s (2016) SAOQ study. Inductive themes of Disconnection/Connection, Safety & Comfort, Independence/Isolation, and Goal Orientation emerged from the qualitative data. Feasibility for implementation was considered through the lenses of adoption, reach fidelity, and sustainability (Pearson et al., 2020). The study found that DIMP is feasible for implementation (Bowen et al., 2009). Considerations for future research and clinical practice were identified. / Music Therapy

Geoscience applications generate large datasets; thus, compression is necessary to facilitate the storage and transmission of geoscience data. One focus is on the coding of hyperspectral imagery and the prominent JPEG2000 standard. Certain aspects of the encoder, such as rate-allocation between bands and spectral decorrelation, are not covered by the JPEG2000 standard. This thesis investigates the performance of several JPEG2000 encoding strategies. Additionally, a relatively low-complexity 3D embedded wavelet-based coder, 3D-tarp, is proposed for the compression of geoscience data. 3D-tarp employs an explicit estimate of the probability of coefficient significance to drive a nonadaptive arithmetic coder, resulting in a simple implementation suited to vectorized hardware acceleration. Finally, an embedded wavelet-based coder is proposed for the shapeaptive coding of ocean-temperature data. 3D binary set-splitting with $k$-d trees, 3D-BISK, replaces the octree splitting structure of other shapeaptive coders with $k$-d trees, a simpler set partitioning structure that is well-suited to shapeaptive coding.

Because of the vast data volume of hyperspectral imagery, compression becomes a necessary process for hyperspectral data transmission, storage, and analysis. Three-dimensional discrete wavelet transform (DWT) based algorithms are particularly of interest due to their excellent rate-distortion performance. This thesis investigates several issues surrounding efficient compression using JPEG2000. Firstly, the rate-distortion performance is studied when Principal Component Analysis (PCA) replaces DWT for spectral decorrelation with the focus on the use of a subset of principal components (PCs) rather than all the PCs. Secondly, the algorithms are evaluated in terms of data analysis performance, such as anomaly detection and linear unmixing, which is directly related to the useful information preserved. Thirdly, the performance of compressing radiance and reflectance data with or without bad band removal is compared, and instructive suggestions are provided for practical applications. Finally, low-complexity PCA algorithms are presented to reduce the computational complexity and facilitate the future hardware design.

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