Who are Like-minded: Mining User Interest Similarity in Online Social Networks

In this paper, we mine and learn to predict how similar a pair of users' interests towards videos are, based on demographic (age, gender and location) and social (friendship, interaction and group membership) information of these users. We use the video access patterns of active users as ground truth (a form of benchmark). We adopt tag-based user profiling to establish this ground truth, and justify why it is used instead of video-based methods, or many latent topic models such as LDA and Collaborative Filtering approaches. We then show the effectiveness of the different demographic and social features, and their combinations and derivatives, in predicting user interest similarity, based on different machine-learning methods for combining multiple features. We propose a hybrid tree-encoded linear model for combining the features, and show that it out-performs other linear and treebased models. Our methods can be used to predict user interest similarity when the ground-truth is not available, e.g. for new users, or inactive users whose interests may have changed from old access data, and is useful for video recommendation. Our study is based on a rich dataset from Tencent, a popular service provider of social networks, video services, and various other services in China

External modulation method for generating accurate linear optical FMCW

Frequency modulation continuous wave (FMCW) lasers are key components in modern optical imaging. However, current intracavity modulation lasers do not exhibit low-frequency jitter rate and high linearity due to the inherent relaxation oscillations. Although this may be compensated in a direct modulation laser diode using an optoelectronic feedback loop, the available sweep speed is moderately small. In this letter, a special external modulation method is developed to improve the performance of FMCW. Since only the first sideband optical field is used during the entire generation process, phase noise is kept to a minimum and is also independent of the sweep speed. We demonstrate that the linearity and jitter rates do not deteriorate appreciably when the sweep speed is changed over three orders of magnitude, even up to the highest sweep speed of 2.5 GHz/ μs

Ultrafast pump-probe spectroscopic signatures of superconducting and pseudogap phases in YBa2Cu3O7-{\delta} films

Femtosecond pump-probe spectroscopy is applied to identify transient optical signatures of phase transitions in optimally doped YBa2Cu3O7-{\delta} films. To elucidate the dynamics of superconducting and pseudogap phases, the slow thermal component is removed from the time-domain traces of photo-induced reflectivity in a high-flux regime with low frequency pulse rate. The rescaled data exhibit distinct signatures of the phase separation with abrupt changes at the onsets of TSC and TPG in excellent agreement with transport data. Compared to the superconducting phase, the response of the pseudogap phase is characterized by the strongly reduced reflectivity change accompanied by a faster recovery time.Comment: 14 pages, 3 figure

MINDFUL SPACE IN SENTENCES - A DATASET OF VIRTUAL EMOTIONS FOR NATURAL LANGUAGE CLASSIFICATION

Spatial emotions have played a critical role in visual-spatial environmental assessment, which can be assessed using bio-sensors and language description. However, information on virtual spatial emotion assessment with objective emotion labels and natural language processing (NLP) is insufficient in literature. Thus, designers’ ability to assess spatial design quantitatively and cost effectively is limited before the design is finalized. This research measures the emotions expressed using electroencephalograms (EEGs) and descriptions in virtual reality (VR) spaces with different parameters. First, 26 subjects experienced 10 designed virtual spaces with a VR headset (Quest 2 device) corresponding to the different space parameters of shape, height, width, and length. Simultaneously, the EEG measured the emotions of the subjects using four electrodes and the five brain waves. Second, two labels – calm and active – were produced using EEGs to describe these virtual reality spaces. Last, this labeled emotion dataset compared the differences among the virtual spaces, human feelings, and the language description of the participants in the VR spatial experience. Experimental results show that the parameter changes of VR spaces can arouse significant fluctuations in the five brain waves. The EEG brain wave signals, in turn, can label the virtual rooms with calm and active emotions. Specifically, in terms of VR spaces and emotions, the experiments find that more relative spatial height results in less active emotions, while round spaces arouse calmness in the human brain waves. Moreover, the precise connection among VR spaces, brain waves in emotion, and languages still needs further research. This research attempts to offer a useful emotion measurement tool in virtual architectural design and description using EEGs. This research identifies potentials for future applications combining physiological metrics and AI methods, i.e., machine learning for synthetic design generation and evaluation

Detecting information flow direction in multivariate linear and nonlinear models

International audienceIn this paper we present an approach to analyze the direction of information flow between time series involving bidirectional relations. The intuitive idea comes from a first study dedicated to the so-called phase slope index, which is a measure originally developed to detect unidirectional relations and is based on the complex coherence function. In order to detect bidirectional flows, we propose two new causality indices supplying the previous index with two other functions, the directed coherence function and the directed transfer function. Moreover, to cope with the inability of the approaches based on coherence (ordinary or directed) or on directed transfer function to distinguish between direct and indirect relations, we propose another causality index based on the partial directed coherence to identify only direct relations. Experimental results show that some challenges have promising solutions through the use of this new indicator dealing with both linear and nonlinear multivariate models

Effects of Tai Chi on the quality of life, mental wellbeing, and physical function of adults with chronic diseases: Protocol for a single-blind, two-armed, randomised controlled trial

Introduction Quality of life (QoL), mental wellbeing, and physical function are often diminished among people with chronic disease. Tai Chi is a moderate form of exercise that may be effective in improving chronic disease management. This protocol paper outlines a trial to determine the therapeutic effects of a Tai Chi program on chronic disease management. Methods and analysis This study will be a pilot, interventional, single-blind, two-armed, randomised, parallel, and controlled trial involving a 12-week Tai Chi program for Australian adults. Forty people aged 18 years and older, diagnosed with one or more chronic disease from general community will be recruited. All participants will be randomised to either a 12-week Tai Chi program or a waiting list control group. The Tai Chi program will involve 12 weeks of group Tai Chi sessions, with 45 minutes per session, twice a week. The primary outcome will be QoL as measured by mean scores on the 12-item Short Form Health Survey (SF-12v2) and the EuroQoL (EQ-5D). The secondary outcomes will include anxiety as measured by mean score on the generalised anxiety disorder 7 (GAD-7) survey; depression as measured by mean score on the patient health questionnaire (PHQ-9); work productivity and activity assessment (WPAI:SHP); pain (if any) as measured by mean scores on the visual analogue scale (VAS) and the McGill pain questionnaire (MPQ). These primary and secondary outcomes will be self-administered via two online assessments prior to (T0) and post-intervention (T1). Objective measures as additional secondary outcomes, will also be carried out by the research team including flexibility as measured by the finger to floor distance (FFD); obesity as measured by mean scores on body mass index (BMI); vital signs (blood pressure, heart rate, respiratory rate, temperate, and oxygen saturation) as measured by a blood pressure monitor, tympanic, and pulse oximetry device, and these outcomes will be measured at T0 and T1 in the ECU Holistic Health Research Clinic. People diagnosed with pre-diabetes or diabetes, their glycosylated haemoglobin (HbA1C) and fasting (before breakfast) blood glucose level (BGL) will also be measured via test kits at T0 and T1 in the clinic. Linear mixed modelling will be conducted to assess changes in outcomes. Statistical significance will be set at an alpha level of 0.05 with a medium effect size. All analyses will be conducted using R version 4.1. Qualitative data will be analysed using template thematic analysis. Ethics and dissemination Ethical approval has been obtained from the Edith Cowan University (ECU) Human Research Ethics Committee (2021-03042-WANG). Research findings will be disseminated to the public, health professionals, researchers, and healthcare providers through conference presentations, lay summaries, and peer-reviewed publications. This study will provide an updated evidence on a safe, sustainable, and inexpensive non-pharmacological approach in the management of chronic disease, the number one burden of disease in Australia

A new strategy for model order identification and its application to transfer entropy for EEG signals analysis.

International audienceThe background objective of this study is to analyze electrenocephalographic (EEG) signals recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different phases are observed during the seizure evolution, including a fast onset activity. We aim to ascertain how cerebral structures get involved during this phase, in particular whether some structures "drive" other ones. Regarding a recent theoretical information measure, namely the transfer entropy (TE), we propose two criteria, the first one is based on Akaike's information criterion, the second on the Bayesian information criterion, to derive models' orders that constitute crucial parameters in the TE estimation. A normalized index, named partial transfer entropy (PTE), allows for quantifying the contribution or the influence of a signal to the global information flow between a pair of signals. Experiments are first conducted on linear autoregressive models, then on a physiology-based model, and finally on real intracerebral EEG epileptic signals to detect and identify directions of causal interdependence. Results support the relevance of the new measures for characterizing the information flow propagation whatever unidirectional or bidirectional interactions

Interaction-aware Spatio-temporal Pyramid Attention Networks for Action Classification

Local features at neighboring spatial positions in feature maps have high correlation since their receptive fields are often overlapped. Self-attention usually uses the weighted sum (or other functions) with internal elements of each local feature to obtain its weight score, which ignores interactions among local features. To address this, we propose an effective interaction-aware self-attention model inspired by PCA to learn attention maps. Furthermore, since different layers in a deep network capture feature maps of different scales, we use these feature maps to construct a spatial pyramid and then utilize multi-scale information to obtain more accurate attention scores, which are used to weight the local features in all spatial positions of feature maps to calculate attention maps. Moreover, our spatial pyramid attention is unrestricted to the number of its input feature maps so it is easily extended to a spatio-temporal version. Finally, our model is embedded in general CNNs to form end-to-end attention networks for action classification. Experimental results show that our method achieves the state-of-the-art results on the UCF101, HMDB51 and untrimmed Charades.Comment: Accepted by ECCV201