A social interaction system based on cloud computing for mobile video telephony

As the use of smartphones become popular,people heavily depend on smartphone applications to deal with their social activities.For this reason,traditional message texting between mobile applications does not fulfill the versatile requirements of social networking.Many mobile applications use multimodality to deliver multimedia messages including sticker,voice and photo message,video call,and snap movie to enhance the communicative capability.However,without face-to-face interaction,people may fail to detect the other side’s non-verbal social behavior such as fine-grain facial expressions,body movements,or hand gesture.During social interaction,non-verbal behavior conveys information about the involved individuals and help the speakers express their social emotion in an implicit way.It is so important for real-world face-to-face interaction but is often blocked on the mobile telephony.To cope with this problem,we propose an afective computing model to assist the representation of social emotion and then help the progress of social interaction on the mobile telephony.In this model,for the purpose of real-time afective analysis,we delegate the computing loading to the cloud side service and enhance the system’s scalability and availability.The result of this experiment approves the feasibility of our system design for the applications of social intelligent.Also,the system provides a research framework of the social intelligent system on the mobile telephony.     

Structure damage diagnosis using neural network and feature fusion

A structure damage diagnosis method combining the wavelet packet decomposition, multi-sensor feature fusion theory and neural network pattern classification was presented. Firstly, vibration signals gathered from sensors were decomposed using orthogonal wavelet. Secondly, the relative energy of decomposed frequency band was calculated. Thirdly, the input feature vectors of neural network classifier were built by fusing wavelet packet relative energy distribution of these sensors. Finally, with the trained classifier, damage diagnosis and assessment was realized. The result indicates that, a much more precise and reliable diagnosis information is obtained and the diagnosis accuracy is improved as well.     

Finite-time weighted average consensus with respect to a monotonic function and its application

The consensus state is an important and fundamental quantity for consensus problems of multi-agent systems, which indicates where all the dynamical agents reach. In this paper, weighted average consensus with respect to a monotonic function, which means that the trajectories of the monotonic function along the state of each agent reach the weighted average of their initial values, is studied for a group of kinematic agents with time-varying topology. By constructing a continuous nonlinear distributed protocol, such a consensus problem can be solved in finite time even though the time-varying topology involves unconnected graphs. Then the distributed protocol is employed to compute the maximum-likelihood estimation of unknown parameters over sensor networks. Compared with the existing results, the estimate scheme proposed here may reduce the costs of data communication, storage memory, book-keeping and computational overheads.     

Fuel provision for nonbreeding deuterium-tritium fusion reactors

Nontritium-breeding D-T reactors have decisive advantages in minimum size, unit cost, variety of applications, and ease of heat removal over reactors using any other fusion cycle, and significant advantages in environmental and safety characteristics over breeding D-T reactors. Considerations of relative energy production demonstrate that the most favorable source of tritium for a widely deployed system of nontritium-breeding D-T reactors is the very large (10 GW thermal) semicatalyzed-deuterium (SCD), or sub-SCD reactor, where none of the escaping³He (> 95%) or tritium (< 25%) is reinjected for burn-up. Feasibility of the ignited SCD tokamak reactor requires spatially averaged betas of 15 to 20% with a magnetic field at the TF coils of 12–13 T.On leave from Dept. of Electronic Engineering, University of Tokyo, Tokyo, Japan.     

A TDOA location algorithm based on data fusion

A new positioning method in mobile networks is presented. Based on the data fusion technology, it processes multi-layer information fusion for the location estimates achieved by the Chan algorithm, which increases mobile positioning accuracy effectively by only using measured difference of arriving (TDOA) signals. The method is simple and practical, especially when the location estimates are corrupted by the non-line-of-sight (NLOS) error. It not only has high positioning accuracy, but also reduces the location failure probability. Results from computer simulation show that the proposed method is effective in various environments. __________ Translated from Journal of Dalian University of Technology, 2005, 45(1): 138–141 (in Chinese)     

Attraction and Repulsion of Nucleons: Sources of Stellar Energy

The potential energy of a nuclide is enhanced by about 10 MeV per nucleon from the repulsion between like nucleons, and diminished by about 20 MeV per nucleon from the attraction between unlike nucleons. Nuclear stability results mostly from the interplay of these opposing forces, plus Coulomb repulsion of positive charges. Whereas fusion may be the primary mechanism by which first generation stars produce energy, repulsion between like nucleons may cause neutron emission from the collapsed core (neutron star) produced in a terminal supernova explosion and initiate luminosity in second generation stars that accrete on such objects. As noted earlier [1], the scarcity of solar neutrinos, the enrichment of light isotopes in the solar wind, and the presence of abundant short-lived nuclides and interlinked chemical and isotopic heterogeneities in the early solar system might also be explained if the Sun formed in this manner.     

基于侧抑制机制的一维多速度运动检测神经网络

运动感知是生物视觉系统的一个重要组成部分。运动对自然界的认识一大部分是通过运动感知。本文通过对同时具有方向和速度选择性的视觉皮层运动区神经元的侧抑制机制的模拟，提出了一种新的乘积抑制速度检测子（Ｍｕｌｔｉｐｌｉｃａｔｉｖｅ Ｉｎｈｉｂｉｔｏｒｙ Ｖｅｌｏｃｉｔｙ－ＭＩＶＤ），其时空联合参数Ｋ决定了检测子的最优速度，基于ＭＩＶＤ的响应幅度差特性，我们构造了两个速度融合神经网络（一个简单神经网络和一个