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Speech anxiety, or Glossophobia, currently affects approximately 75% of the population with potentially severe negative effects on those with this condition. There are several treatments currently available with research showing that the use of Virtual Reality (VR) as a non-pharmacologic treatment can have positive effects on individuals suffering from such social phobias. However, there is a significant lack of treatments currently available for speech anxiety, even though such a large number of the population are affected by it. In this paper, we aim to contribute to efforts to improve the effects of speech anxiety through a VR intervention. Our VR solution was designed following the Exposure Therapy approach for treating social anxiety disorders. The evaluation of this work was twofold: A. to assess the ability of our solution to positively change participants’ perception of factors related to non-verbal communication contributing to anxiety toward public speaking, and B. to determine whether it is able to induce a sense of presence. We carried out an empirical evaluation study that measured participants’ self-reported anxiety level towards public speaking using the Personal Report of Public Speaking Anxiety and their perceived sense of presence using the iGroup Presence Questionnaire. Our results demonstrate the potential of VR Exposure Therapy solutions to assist towards positively changing perception of factors related to non-verbal communication skills that contribute to increasing public speaking anxiety for participants suffering from self-reported speech anxiety symptoms. Our findings are of wider importance as they contribute to ongoing efforts to improve social anxiety-related phobias. [ABSTRACT FROM AUTHOR]

Technological advancements have enabled emerging multimedia applications, which require massive devices with real-time communication, computation, and control. Some of these challenges include: how to design an efficient fog/edge Networking based multimedia Networking framework, how to make multimedia systems more intelligent, how to achieve the efficient multimedia data processing and distribution with edge/fog Networking, and how to design an efficient incentive mechanism for performance enhancement. The thirteenth paper by I Suqin Wu i on "Communication Modulation Recognition Algorithm based on STFT Mechanism in Combination with Unsupervised Feature-learning Network" proposed a novel recognition algorithm based on deep learning network far communication signal features for dealing with the limitations of traditional communication modulation recognition algorithms. [Extracted from the article]

Nomadic users of streamed multimedia content in mobile networks are often faced with resource-constrained network paths that suffer from low bandwidth. Streaming high-quality video in such a challenging scenario demands a set of highly adaptive schemes, which have not been sufficiently explored in particular for the emerging H.264 Scalable Video Coding (H.264/SVC) standard. In this paper, we empirically investigate the performance of streaming H.264/SVC scalable video streams to users in multihomed mobile networks containing multiple available transmission paths. Previous work has demonstrated the feasibility of aggregating bandwidth of multiple paths to deliver video streams when no single, sufficiently high bandwidth path is available. We focus on evaluating the enhanced performance of multipath bandwidth-aggregation streaming by exploiting a quality-layers based, H.264/SVC-specific packet prioritisation scheme for quality-aware multipath packet scheduling and selective packet dropping in case of bandwidth shortage even after aggregation. Additionally, we explore a base-layer rate control scheme for H.264/SVC delivery in ultra-low bandwidth environments. Through extensive experimentation on a realistic hardware-based testbed, we obtain a comprehensive and insightful understanding of the behaviour of H.264/SVC streams when transmitted across multiple paths in mobile networks. We quantify the improvements offered by the use of H.264/SVC-specific packet prioritisation schemes compared with an existing generic scalable video prioritisation scheme, and the benefits by the use of base-layer rate control in ultra-low bandwidth situations. The performance of the multipath streaming schemes is further compared with that of an ideal single high bandwidth path. We also identify the remaining challenges that must be overcome if such streaming schemes are to offer performance close to that of the ideal single high bandwidth path. [ABSTRACT FROM AUTHOR]

Technological advancements have enabled emerging multimedia applications requiring powerful devices with real-time capabilities, and advanced computation and control. Some of these challenges include: how to design an efficient fog/edge computing-based multimedia computing framework, how to make multimedia systems more intelligent, how to achieve the efficient multimedia data processing and distribution with edge/fog computing, and how to design a fog/edge computing assisted service enhancement mechanism. The paper "3D Point Cloud Registration Denoising Method for Human Motion Image Using Deep Learning Algorithm" by Qidong Du, proposed a 3D point cloud registration denoising method for human motion image using depth learning algorithm in complex scenes. [Extracted from the article]

The development of transdermal therapeutic systems (TTS) often involves in vitro evaluation of formulations and prototypes using flow-through diffusion cells. The apparent flux obtained from such methodologies does not accurately represent the actual (intrinsic) permeation of the compound through the skin. Flow-through system parameters, i.e., fraction collector tube volume, receiver cell volume, flow rate, and sampling interval, modify the flux yielding an apparent flux. Both finite-dose flux profiles and infinite-dose diffusional lag times are modified by these parameters. In this study, a transfer function is derived which describes the effect of these parameters. The intrinsic flux is calculated from apparent flux data using the transfer function and experimental flow-through system parameters. This allows the calculation of permeant flux profiles devoid of modification by the experimental methodology. [ABSTRACT FROM AUTHOR]