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Exploring the impact of digital humans on customer experience
Get PDFThis ongoing work focuses on the virtual technology of digital humans, specifically on the potential impacts on customer experience. It starts by introducing the development of a believability framework for digital humans, emphasizing the interactions between behaviour, personality, appearance, and environment to enhance their realism. The framework aims to alleviate the "uncanny valley" effect and improve consumer interaction by making digital humans more lifelike and emotionally intelligent. The study employs a design science research approach, creating digital humans as student ambassadors in a university scenario, and has undergone three iterations, including interviews with university faculty and staff, co-creative workshops with students, and field experiments. The goal is to conduct empirical tests to refine the framework, thus enhancing customer experience in a virtual world environment.<br/
Final report for Solicitors Regulation Authority on the potential causes of differential outcomes in legal professional assessments
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Application of artificial intelligence in cognitive load analysis using functional near-infrared spectroscopy:A systematic review
Get PDFCognitive load theory suggests that overloading of working memory may negatively affect the performance of human in cognitively demanding tasks. Evaluation of cognitive load is a difficult task; it is often assessed through feedback and evaluation from experts. Cognitive load classification based on Functional Near-InfraRed Spectroscopy (fNIRS) is now one of the key research areas in recent years, due to its resistance of artefacts, cost-effectiveness, and portability. To make fNIRS more practical in various applications, it is necessary to develop robust algorithms that can automatically classify fNIRS signals and less reliant on trained signals. Many of the analytical tools used in cognitive sciences have used Deep Learning (DL) modalities to uncover relevant information for mental workload classification. This review investigates the research questions on the design and overall effectiveness of DL as well as its key characteristics. We have identified 45 studies published between 2011 and 2023, that specifically proposed Machine Learning (ML) models for classifying cognitive load using data obtained from fNIRS devices. Those studies were analyzed based on type of feature selection methods, input, and DL model architectures. Most of the existing cognitive load studies are based on ML algorithms, which follow signal filtration and hand-crafted features. It is observed that hybrid DL architectures that integrate convolution and LSTM operators performed significantly better in comparison with other models. However, DL models especially hybrid models have not been extensively investigated for the classification of cognitive load captured by fNIRS devices. The current trends and challenges are highlighted to provide directions for the development of DL models pertaining to fNIRS research
Interaction between active tectonics, bottom-current processes and coral mounds:A unique example in the NW Moroccan Margin, southern Gulf of Cadiz
Get PDFReconcilable differences:Using retrospective photogrammetry to bridge the divide between analogue and digital site data collected during long-term excavation projects
Get PDFOver the last 30 years, high-resolution site documentation has rapidly developed, with analogue drawings and film photography being replaced with high-precision digital recordings. Today, most archaeological field data sets are produced using digital tools that store spatial and visual information in various digital formats directly, i.e., born-digital. A fully digital workflow makes the process of combining, comparing, and integrating field datasets quicker, easier, and potentially more analytically powerful. However, at sites where both analogue and born-digital data sets have been produced, additional procedural digitization steps are required before full data interoperability is achieved. In cases where the archaeological sites have a long excavation history, multiple generations of analogue and digital site documentation techniques have often been used, making it particularly challenging to physically reconstruct an excavated site based on its archival material. The Middle Stone Age site of Blombos Cave, South Africa, is a prime example of this type of challenging situation. This site features a more than 3-meter-deep and well-preserved archaeological sequence dated to between 300 and 100 000 years ago. Since it was initially excavated in 1991, multiple archaeological campaigns have been carried out (>15), and the excavations are still ongoing. The field documentation from Blombos Cave has, over the years, produced varied but rich datasets that have never been integrated into a single, coherent, and accessible archive. In this paper we evaluate the changes in excavation protocol at Blombos Cave over time, and we use this knowledge to digitally integrate and map the various stages of excavation within a three-dimensional framework using digital photogrammetry and archival photographs. The archaeological and analytical value of this approach is exemplified through multiple case studies, in which we demonstrate how and why the merging of old and new archaeological field data can lead to new results, specifically by offering more complete mapping and more accurate and analytically dynamic visualisations. The research history at Blombos Cave is not unique or site-specific. Our approach would be applicable to a wide variety of sites and contexts where long-running excavations have produced a mix of analogue and digital field data
Steady State – co-created by Alexander Schubert, Zubin Kanga, Felina Levits, Alexander Trattler and Serafeim Perdikis
Get PDFSteady State is a performative piece that integrates neuroscience and technology to create a feedback loop between the performer’s brain activity and computer-generated stimuli. Using an EEG cap, the performer’s dominant brain frequencies are measured as they interact with strobing video projections. The performer’s gaze and brain activity influence the visuals, creating a continuous loop. The piece blurs the lines between installation and performance, with the performer turning into a transhuman processing unit, revolving around the body, computation, hallucination, and transcendence.It is a collaboration between: Alexander Schubert: composerZubin Kanga: project manager and lead performerSerafeim Perdikis: neuro-programmingAlexander Trattler: video designFelina Levits: costumesANT Neuro: brain sensorsNote that the score, tech rider and brain-computer interaction software are provided in links below. Further materials for the work are available on request. <br/
The Effect of Seeing Paintings or Photojournalistic Images Depicting Refugees on Their Infrahumanisation
Get PDFSOFRA: A Journey Through Manisa from Seed to Plate
Get PDFThis is a book about and for the people, communities, and food of Manisa province, Türkiye. From the Bronze Age to the present, it is a story about the food traditions that individuals, especially women, chose to prioritise and therefore keep alive, sometimes for millennia. Yet as food priorities shift in response to our rapidly changing world, more and more decision making is required. Consequently, this is both a cookbook and a guidebook for those wishing to find balance in their own food priorities, as well as a permanent record of these recipes and activities.<br/
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