scholarly journals Smelling Sensations: Olfactory Crossmodal Correspondences

2021 ◽  
Author(s):  
Ryan J. Ward ◽  
Sophie M. Wuerger ◽  
Alan Marshall
Keyword(s):  
Quality Of Experience ◽  
Crossmodal Correspondences ◽  
Daily Lives ◽  
Crossmodal Interactions ◽  
Sensory Modalities ◽  
Olfactory Stimuli ◽  
Emotional Dimensions ◽  
Musical Genres ◽  
Sensory Expectations

Olfaction is ingrained into the fabric of our daily lives and constitutes an integral part of our perceptual reality. Within this reality, there are crossmodal interactions and sensory expectations; understanding how olfaction interacts with other sensory modalities is crucial for augmenting interactive experiences with more advanced multisensorial capabilities. This knowledge will eventually lead to better designs, more engaging experiences, and enhancing the perceived quality of experience. Toward this end, the authors investigated a range of crossmodal correspondences between ten olfactory stimuli and different modalities (angularity of shapes, smoothness of texture, pleasantness, pitch, colors, musical genres, and emotional dimensions) using a sample of 68 observers. Consistent crossmodal correspondences were obtained in all cases, including our novel modality (the smoothness of texture). These associations are most likely mediated by both the knowledge of an odor’s identity and the underlying hedonic ratings: the knowledge of an odor’s identity plays a role when judging the emotional and musical dimensions but not for the angularity of shapes, smoothness of texture, perceived pleasantness, or pitch. Overall, hedonics was the most dominant mediator of crossmodal correspondences.

scholarly journals Smelling Sensations: Olfactory Crossmodal Correspondences †

2021 ◽  
Author(s):  
Ryan J. Ward ◽  
Sophie M. Wuerger ◽  
Alan Marshall
Keyword(s):  
Quality Of Experience ◽  
Crossmodal Correspondences ◽  
Daily Lives ◽  
Crossmodal Interactions ◽  
Sensory Modalities ◽  
Olfactory Stimuli ◽  
Emotional Dimensions ◽  
Musical Genres ◽  
Sensory Expectations

Olfaction is ingrained into the fabric of our daily lives and constitutes an integral part of our perceptual reality. Within this reality, there are crossmodal interactions and sensory expectations; understanding how olfaction interacts with other sensory modalities is crucial for augmenting interactive experiences with more advanced multisensorial capabilities. This knowledge will eventually lead to better designs, more engaging experiences, and enhancing the perceived quality of experience. Toward this end, the authors investigated a range of crossmodal correspondences between ten olfactory stimuli and different modalities (angularity of shapes, smoothness of texture, pleasantness, pitch, colors, musical genres, and emotional dimensions) using a sample of 68 observers. Consistent crossmodal correspondences were obtained in all cases, including our novel modality (the smoothness of texture). These associations are most likely mediated by both the knowledge of an odor’s identity and the underlying hedonic ratings: the knowledge of an odor’s identity plays a role when judging the emotional and musical dimensions but not for the angularity of shapes, smoothness of texture, perceived pleasantness, or pitch. Overall, hedonics was the most dominant mediator of crossmodal correspondences.

scholarly journals Smelling sensations: olfactory crossmodal correspondences

2020 ◽  
Author(s):  
Ryan Joseph Ward ◽  
Sophie Wuerger ◽  
Alan Marshall
Keyword(s):  
Aromatic Compounds ◽  
Explicit Knowledge ◽  
Principal Component ◽  
Multisensory Perception ◽  
Crossmodal Correspondences ◽  
Cross Model ◽  
Sensory Modalities ◽  
Olfactory Stimuli ◽  
Emotional Dimensions ◽  
Musical Genres

Crossmodal correspondences are the associations between apparently distinct stimuli in different sensory modalities . These associations, albeit surprising, are generally shared in most of the population. Olfaction is ingrained in the fabric of our daily life and constitutes an integral part of our perceptual reality, with olfaction being more commonly used in the entertainment and analytical domains, it is crucial to uncover the robust correspondences underlying common aromatic compounds. Towards this end, we investigated an aggregate of crossmodal correspondences between ten olfactory stimuli and other modalities ( angularity of shapes, smoothness of texture, pleasantness, pitch, colours, musical genres and emotional dimensions ) using a large sample of 68 observers. We uncover the correspondences between these modalities and extent of these associations with respect to the explicit knowledge of the respective aromatic compound. The results revealed the robustness of prior studies, as well as, contributions towards olfactory integration between an aggregate of other dimensions. The knowledge of an odour's identity coupled with the multisensory perception of the odours indicates that these associations, for the most part, are relatively robust and do not rely on explicit knowledge of the odour. Through principal component analysis of the perceptual ratings, new cross-model mediations have been uncovered between odours and their intercorrelated sensory dimensions. Our results demonstrate a collective of associations between olfaction and other dimensions, potential cross modal mediations via exploratory factor analysis and the robustness of these correspondence with respect to the explicit knowledge of an odour. We anticipate the findings reported in this paper could be used as a psychophysical framework aiding in a collective of applications ranging from olfaction enhanced multimedia to marketing.

UBAR

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
State Of The Art ◽  
State Of Charge ◽  
User Preference ◽  
Management Approach ◽  
High Quality ◽  
Trade Off ◽  
Run Time

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.

scholarly journals Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Sajeeb Saha ◽  
Md. Ahsan Habib ◽  
Tamal Adhikary ◽  
Md. Abdur Razzaque ◽  
Md. Mustafizur Rahman ◽  
...  
Keyword(s):  
Mobile Device ◽  
Quality Of Experience ◽  
Incentive Mechanism ◽  
Mobile Device Cloud

What's my App?

2021 ◽  
Vol 48 (4) ◽  
pp. 41-44
Author(s):  
Dena Markudova ◽  
Martino Trevisan ◽  
Paolo Garza ◽  
Michela Meo ◽  
Maurizio M. Munafo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Real Time ◽  
Language Processing ◽  
Traffic Management ◽  
Quality Of Experience ◽  
Broadband Internet ◽  
Management Policies ◽  
Control Traffic

With the spread of broadband Internet, Real-Time Communication (RTC) platforms have become increasingly popular and have transformed the way people communicate. Thus, it is fundamental that the network adopts traffic management policies that ensure appropriate Quality of Experience to users of RTC applications. A key step for this is the identification of the applications behind RTC traffic, which in turn allows to allocate adequate resources and make decisions based on the specific application's requirements. In this paper, we introduce a machine learning-based system for identifying the traffic of RTC applications. It builds on the domains contacted before starting a call and leverages techniques from Natural Language Processing (NLP) to build meaningful features. Our system works in real-time and is robust to the peculiarities of the RTP implementations of different applications, since it uses only control traffic. Experimental results show that our approach classifies 5 well-known meeting applications with an F1 score of 0.89.

scholarly journals Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling

2021 ◽  
Vol 48 (4) ◽  
pp. 37-40
Author(s):  
Nikolas Wehner ◽  
Michael Seufert ◽  
Joshua Schuler ◽  
Sarah Wassermann ◽  
Pedro Casas ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Recurrent Neural Networks ◽  
Quality Of Experience ◽  
Unique Feature ◽  
Time Series Modeling ◽  
Web Browsing ◽  
Large Dataset ◽  
Efficient Approximation

This paper addresses the problem of Quality of Experience (QoE) monitoring for web browsing. In particular, the inference of common Web QoE metrics such as Speed Index (SI) is investigated. Based on a large dataset collected with open web-measurement platforms on different device-types, a unique feature set is designed and used to estimate the RUMSI - an efficient approximation to SI, with machinelearning based regression and classification approaches. Results indicate that it is possible to estimate the RUMSI accurately, and that in particular, recurrent neural networks are highly suitable for the task, as they capture the network dynamics more precisely.

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