Task-Oriented Multi-User Semantic Communications for VQA

Semantic communications focus on the transmission of semantic features. In this letter, we consider a task-oriented multi-user semantic communication system for multimodal data transmission. Particularly, partial users transmit images while the others transmit texts to inquiry the information about the images. To exploit the correlation among the multimodal data from multiple users, we propose a deep neural network enabled semantic communication system, named MU-DeepSC, to execute the visual question answering (VQA) task as an example. Specifically, the transceiver for MU-DeepSC is designed and optimized jointly to capture the features from the correlated multimodal data for task-oriented transmission. Simulation results demonstrate that the proposed MU-DeepSC is more robust to channel variations than the traditional communication systems, especially in the low signal-to-noise (SNR) regime

Deep Learning Enabled Semantic Communication Systems

Recently, deep learned enabled end-to-end (E2E) communication systems have been developed to merge all physical layer blocks in the traditional communication systems, which make joint transceiver optimization possible. Powered by deep learning, natural language processing (NLP) has achieved great success in analyzing and understanding large amounts of language texts. Inspired by research results in both areas, we aim to providing a new view on communication systems from the semantic level. Particularly, we propose a deep learning based semantic communication system, named DeepSC, for text transmission. Based on the Transformer, the DeepSC aims at maximizing the system capacity and minimizing the semantic errors by recovering the meaning of sentences, rather than bit- or symbol-errors in traditional communications. Moreover, transfer learning is used to ensure the DeepSC applicable to different communication environments and to accelerate the model training process. To justify the performance of semantic communications accurately, we also initialize a new metric, named sentence similarity. Compared with the traditional communication system without considering semantic information exchange, the proposed DeepSC is more robust to channel variation and is able to achieve better performance, especially in the low signal-to-noise (SNR) regime, as demonstrated by the extensive simulation results.Comment: 13 pages, Journal, accepted by IEEE TS

Perforation resistance of aluminum/polyethylene sandwich structure

© 2016 Elsevier Ltd. Ballistic tests were performed on two types of polyethylene core sandwich structures (AA6082/LDPE/AA6082 and AA6082/UHMWPE/AA6082) to investigate their perforation resistance. Bulging and dishing deformation of layered plates were compared under low-velocity impact by hemispherical-nosed projectiles. Different impact failure mechanisms leading to perforation were revealed for laminates composed of a pair of aluminum alloy face sheets separated by a polyethylene interlayer. Using the finite element code Abaqus/Explicit, the perforation behavior and distribution of energy dissipation of each layer during penetration were simulated and analysed. The deformation resistance and anti-penetration properties of polyethylene core sandwich structures were compared with those of monolithic AA6082-T6 plates that had the same areal density. Although the polyethylene interlayer enlarged the plastic deformation zone of the back face, the polyethylene core sandwich structure was a little less effective than the monolithic Al alloy target at resisting hemispherical-nosed projectile impact.The authors gratefully acknowledge the Foundation of State Key Laboratory of Explosion Science and Technology of China under Grant No. KFJJ13-1Z, and Natural Science Foundation of China under Grant No. 11102023, 11172071

Deep Learning Enabled Semantic Communications with Speech Recognition and Synthesis

In this paper, we develop a deep learning based semantic communication system for speech transmission, named DeepSC-ST. We take the speech recognition and speech synthesis as the transmission tasks of the communication system, respectively. First, the speech recognition-related semantic features are extracted for transmission by a joint semantic-channel encoder and the text is recovered at the receiver based on the received semantic features, which significantly reduces the required amount of data transmission without performance degradation. Then, we perform speech synthesis at the receiver, which dedicates to re-generate the speech signals by feeding the recognized text and the speaker information into a neural network module. To enable the DeepSC-ST adaptive to dynamic channel environments, we identify a robust model to cope with different channel conditions. According to the simulation results, the proposed DeepSC-ST significantly outperforms conventional communication systems and existing DL-enabled communication systems, especially in the low signal-to-noise ratio (SNR) regime. A software demonstration is further developed as a proof-of-concept of the DeepSC-ST

Rethinking Outage Constraints for Resource Management in NOMA Networks

© 2007-2012 IEEE. In non-orthogonal multiple access (NOMA) systems, the outage is regarded to happen when a user cannot correctly decode the messages for users with higher decoding order and hence cannot perform the successive interference cancelation (SIC). However, in this case, the user may still correctly decode its message by treating the uncanceled signal as interference and avoid the outage. By considering this behavior, the outage probability should be redefined. In this paper, we investigate user scheduling and power allocation for a downlink NOMA system with imperfect SIC by using the alternative outage probability as a constraint. In order to tackle the complicated non-convex resource allocation problem, we propose a two-phase algorithm, in which the user scheduling is first optimized through a matching theory based algorithm, and then power allocation is performed with the aid of the branch and bound technique and the concave-convex procedure method. Simulation results show that the performance of the proposed low-complexity algorithm is near-optimal and the algorithm based on the alternative outage probability outperforms that based on the traditional one when the residual interference from imperfect SIC significantly affects the decoding

Classic yin and yang tonic formula for osteopenia: study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Osteoporosis is a growing worldwide problem, with the greatest burden resulting from fractures. Nevertheless, the majority of fractures in adults occur in those with "osteopenia" (bone mineral density (BMD) only moderately lower than young normal individuals). Since long-term drug therapy is an expensive option with uncertain consequences and side effects, natural herbal therapy offers an attractive alternative. The purpose of this study is to evaluate the effect on BMD and safety of the Classic Yin and Yang Tonic Formula for treatment of osteopenia and to investigate the mechanism by which this efficacy is achieved.</p> <p>Methods/design</p> <p>We propose a multicenter double-blind randomized placebo-controlled trial to evaluate the efficacy and safety of the Classic Yin and Yang Tonic Formula for the treatment of osteopenia. Participants aged 55 to 75 with low bone mineral density (T-score between -1 and -2.5) and kidney deficiency in TCM will be included and randomly allocated into two groups: treatment group and control group. Participants in the treatment group will be treated with Classic Yin and Yang Tonic Granule, while the controlled group will receive placebo. Primary outcome measure will be BMD of the lumbar spine and proximal femur using dual-energy X-ray absorptiometry. Secondary outcomes will include pain intensity measured with visual analogue scales, quality of life, serum markers of bone metabolism, indices of Neuro-endocrino-immune network and safety.</p> <p>Discussion</p> <p>If the Classic Yin and Yang Tonic Formula can increase bone mass without adverse effects, it may be a novel strategy for the treatment of osteoporosis. Furthermore, the mechanism of the Chinese medical formula for osteoporosis will be partially elucidated.</p> <p>Trial registration</p> <p>This study is registered at ClinicalTrials.gov, <a href="http://www.clinicaltrials.gov/ct2/show/NCT01271647">NCT01271647</a>.</p

MTHFR C677T and MTR A2756G polymorphisms and the homocysteine lowering efficacy of different doses of folic acid in hypertensive Chinese adults

<p>Abstract</p> <p>Background</p> <p>This study aimed to investigate if the homocysteine-lowering efficacy of two commonly used physiological doses (0.4 mg/d and 0.8 mg/d) of folic acid (FA) can be modified by individual methylenetetrahydrofolate reductase (MTHFR) C677T and/or methionine synthase (MTR) A2756G polymorphisms in hypertensive Chinese adults.</p> <p>Methods</p> <p>A total of 480 subjects with mild or moderate essential hypertension were randomly assigned to three treatment groups: 1) enalapril only (10 mg, control group); 2) enalapril-FA tablet [10:0.4 mg (10 mg enalapril combined with 0.4 mg of FA), low FA group]; and 3) enalapril-FA tablet (10:0.8 mg, high FA group), once daily for 8 weeks.</p> <p>Results</p> <p>After 4 or 8 weeks of treatment, homocysteine concentrations were reduced across all genotypes and FA dosage groups, except in subjects with MTR 2756AG /GG genotype in the low FA group at week 4. However, compared to subjects with MTHFR 677CC genotype, homocysteine concentrations remained higher in subjects with CT or TT genotype in the low FA group (<it>P </it>< 0.05 for either of these genotypes) and TT genotype in the high FA group (<it>P </it>< 0.05). Furthermore, subjects with TT genotype showed a greater homocysteine-lowering response than did subjects with CC genotype in the high FA group (mean percent reduction of homocysteine at week 8: CC 10.8% vs. TT: 22.0%, <it>P </it>= 0.005), but not in the low FA group (CC 9.9% vs. TT 11.2%, <it>P </it>= 0.989).</p> <p>Conclusions</p> <p>This study demonstrated that MTHFR C677T polymorphism can not only affect homocysteine concentration at baseline and post-FA treatment, but also can modify therapeutic responses to various dosages of FA supplementation.</p