615 research outputs found
Moiré flat bands in strongly coupled atomic arrays
Moiré effects arise from stacking periodic structures with a specific geometrical mismatch and promise unique possibilities. However, their full potential for photonic applications has yet to be explored. Here, we investigate the photonic band structure for an atomic stack of strongly coupled linear arrays in the dipolar regime. A moiré parameter θ is used to parameterize a relative lattice constant mismatch between the two arrays that plays the role of a 1D twist angle. The system’s interaction matrix is analytically diagonalized and reveals the presence of localized excitations which strongly enhance the density of optical states in spectral regions that can be controlled via the moiré parameter. We also confirm our findings by numerical simulations of finite systems. Our work provides a better understanding of photonic moiré effects and their potential use in photonic devices such as optical sensors and light traps
Role of geometric shape in chiral optics
The distinction of chiral and mirror symmetric objects is straightforward from a geometrical point of view. Since the biological as well as the optical activity of molecules strongly depend on their handedness, chirality has recently attracted high interest in the field of nano-optics. Various aspects of associated phenomena including the influences of internal and external degrees of freedom on the optical response have been discussed. Here, we propose a constructive method to evaluate the possibility of observing any chiral response from an optical scatterer. Based on solely the T-matrix of one enantiomer, planes of minimal chiral response are located and compared to geometric mirror planes. This provides insights into the relation of geometric and optical properties and enables identifying the potential of chiral scatterers for nano-optical experiments
CorrFeat: Correlation-based feature extraction algorithm using skin conductance and pupil diameter for emotion recognition
To recognize emotions using less obtrusive wearable sensors, we present a novel emotion recognition method that uses only pupil diameter (PD) and skin conductance (SC). Psychological studies show that these two signals are related to the attention level of humans exposed to visual stimuli. Based on this, we propose a feature extraction algorithm that extract correlation-based features for participants watching the same video clip. To boost performance given limited data, we implement a learning system without a deep architecture to classify arousal and valence. Our method outperforms not only state-of-art approaches, but also widely-used traditional and deep learning methods
How are we connected?
Accurately measuring the audience response during a performance is a difficult task. This is particularly the
case for connected performances. In this paper, we staged a connected performance in which a remote
audience enjoyed the performance in real-time. Both objective (galvanic skin response and behaviours) and
subjective (interviews) responses from the live and remote audience members were recorded. To capture
galvanic skin response, a group of self-built sensors was used to record the electrical conductance of the skin.
The results of the measurements showed that both the live and the remote audience members had a similar
response to the connected performance even though more vivid artistic artefacts had a stronger effect on the
live audience. Some technical issues also influenced the experience of the remote audience. In conclusion we
found that the remoteness had little influence on the connected performance
Quantifying audience experience in the wild
Measuring the experience of audience of arts events is essential in the “experience economy” of this day and age, but it is a difficult task. The value of such information goes beyond evaluating the impact of the arts, as it can provide insights and feedback to enhance the work of artists and the experiences of other audience members. Through in-depth understanding of the needs of the providers and consumers of the arts, we progressively developed a biosensor infrastructure that was deployed in theaters. Over the years, we identified the challenges and issues related to developing and deploying a biosensor infrastructure in theaters. These collective experiences and identified issues were categorized into three main areas: processes, data, and system. A total of seven heuristics are developed across the three main areas. Processes place the stakeholders and audiences at the core of the research; data provides guidelines for data validity, collecting a variety of data, and supporting real-time data gathering; and systems covers the concurrency, scalability, deployment and feedback of the infrastructure. We believe that this set of heuristics forms the foundation for an adequate infrastructure to measure audience experience in the wild and it is a valuable source of guideline for future work
Investigating the relationship between momentary emotion self-reports and Head and Eye Movements in HMD-based 360 VR video watching
Inferring emotions from Head Movement (HM) and Eye Movement (EM) data in 360â—¦ Virtual Reality (VR) can enable a low-cost means of improving users' Quality of Experience. Correlations have been shown between retrospective emotions and HM, as well as EM when tested with static 360â—¦ images. In this early work, we investigate the relationship between momentary emotion self-reports and HM/EM in HMD-based 360â—¦ VR video watching. We draw on HM/EM data from a controlled study (N=32) where participants watched eight 1-minute 360â—¦ emotion-inducing video clips, and annotated their valence and arousal levels continuously in real-time. We analyzed HM/EM features across fine-grained emotion labels from video segments with varying lengths (5-60s), and found significant correlations between HM rotation data, as well as some EM features, with valence and arousal ratings. We show that fine-grained emotion labels provide greater insight into how HM/EM relate to emotions during HMD-based 360â—¦ VR video watching
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