UVOC-MAC: a MAC protocol for outdoor ultraviolet networks

As an alternative to radio-frequency (RF) communications, optical wireless communications can support high data rates and low power operations while providing good jamming resistance. Our focus in this paper is on deep ultraviolet (UV) outdoor communications (UVOC) where solar blind and non-line-of-sight operations are attractive. Light beams from UV light-emitting diode (LED) arrays serve as information carriers. In an abstract sense, this is similar to directional transmissions in RF; however, the physical (PHY) layer characteristics significantly differ due to atmospheric scattering. First, we perform extensive experiments on a UV testbed towards understanding signal propagation and the impact of the PHY on medium access. We find that UV propagation supports (a) fully duplex communications and (b) multiple data rate transmissions. Next, we propose a novel contention-based media access control (UVOC-MAC) protocol that inherently accounts for the UV PHY layer and fully exploits multi-fold spatial reuse opportunities. Evaluations via both simulations and analysis show that UVOC-MAC effectively mitigates collisions and achieves high throughput. In particular, up to a 4-fold increase in throughput and 50 % reduction in collision are possible compared to a MAC protocol agnostic to the UV PHY properties.     

Bioinspired Graphene Actuators Prepared by Unilateral UV Irradiation of Graphene Oxide Papers

Inspired by natural autonomous systems that demonstrate controllable shape, appearance, and actuation under external stimuli, a facile preparation of moisture responsive graphene‐based smart actuators by unilateral UV irradiation of graphene oxide (GO) papers is reported. UV irradiation of GO is found to be an effective protocol to trigger the reduction of GO; however, due to the limited light transmittance and thermal relaxation, thick GO paper cannot be fully reduced. Consequently, by tuning the photoreduction gradient, anisotropic GO/reduced GO (RGO) bilayer structure can be easily prepared toward actuation application. To get better control over the responsive properties, GO/RGO bilayer paper with a certain curvature and RGO patterns are successfully prepared for actuator design. As representative examples, smart humidity‐driven graphene actuators that mimic the cilia of respiratory tract and tendril climber plant are successfully developed for controllable objects transport.     

Supramolecular Chemistry in Molten Sulfur: Preorganization Effects Leading to Marked Enhancement of Carbon Nitride Photoelectrochemistry

Here, a new method for enhancing the photoelectrochemical properties of carbon nitride thin films by in situ supramolecular‐driven preorganization of phenyl‐contained monomers in molten sulfur is reported. A detailed analysis of the chemical and photophysical properties suggests that the molten sulfur can texture the growth and induce more effective integration of phenyl groups into the carbon nitride electrodes, resulting in extended light absorption alongside with improved conductivity and better charge transfer. Furthermore, photophysical measurements indicate the formation of sub‐bands in the optical bandgap which is beneficial for exciton splitting. Moreover, the new bands can mediate hole transfer to the electrolyte, thus improving the photooxidation activity. The utilization of high temperature solvent as the polymerization medium opens new opportunities for the significant improvement of carbon nitride films toward an efficient photoactive material for various applications.     

Strategies to Improve Field Emission Performance of Nanostructural ZnO

Nanostructural ZnO is a good candidate for field emission (FE) because of its high aspect ratio, controllable electrical conductivity, and good thermal and chemical stability. In order to improve the FE performance, ZnO nanopins, gallium-doped nanofibers, periodic nanorod arrays, and aligned nanotubes were designed and fabricated by a vapor-phase transport method using ZnO + C and ZnO + C + Ga₂O₃ powder mixtures, electrochemical deposition, and hydrothermal decomposition, respectively. The FE behaviors including threshold of electric field, emission current density, field enhancement factor, and stability are reviewed in this paper based on our previous works. Some strategies to improve the performance of the nanostructural ZnO field emitters are demonstrated.     

(Semi-)blind channel estimation for space time block coded system with transmit diversity

This paper deals with a blind channel estimation method for space-time coded block transmission system. By concatenating the real part and imaginary part of the received signal to form an elongated vector, we derive an equivalent input–output system model. Then channel state information (CSI) is blindly estimated using subspace method, utilizing only the redundancy inherent in space-time block coding (STBC) and cyclic prefix (CP). The estimation ambiguity, which is common to all blind methods, is analyzed in detail and we prove that there only exist four scalar indeterminacies. Three effective methods to eliminate the ambiguities are also proposed. Compared with other blind channel estimation methods for space time systems, this method needs neither redundant precoding nor oversampling, and thus has higher data rate. Besides, this method is robust to channel order overestimation, which is effectively demonstrated by numerical simulations. This work was supported by NSFC (60496310, 60672093), NSFJS(BK2005061) and BK2005061.     

多径信道PAM-TH-MA系统性能分析

超宽带(UWB)通信具有数据速率高、功率谱密度低、定位精度高以及抗多径能力强等优点,通过重复利用频谱,可解决频谱拥挤不堪的问题,已成为无线通信领域研究的热点。本文针对PAM-TH-MA系统在多径信道下的抗噪性能进行研究,并比较了分别采用S-Rake和P-Rake接收机时的性能。仿真结果表明,采用S-Rake接收机时的系统性能优于P-Rake接收机。     

EMG and EPP-integrated human-machine interface between the paralyzed and rehabilitation exoskeleton

Although a lower extremity exoskeleton shows great prospect in the rehabilitation of the lower limb, it has not yet been widely applied to the clinical rehabilitation of the paralyzed. This is partly caused by insufficient information interactions between the paralyzed and existing exoskeleton that cannot meet the requirements of harmonious control. In this research, a bidirectional human-machine interface including a neurofuzzy controller and an extended physiological proprioception (EPP) feedback system is developed by imitating the biological closed-loop control system of human body. The neurofuzzy controller is built to decode human motion in advance by the fusion of the fuzzy electromyographic signals reflecting human motion intention and the precise proprioception providing joint angular feedback information. It transmits control information from human to exoskeleton, while the EPP feedback system based on haptic stimuli transmits motion information of the exoskeleton back to the human. Joint angle and torque information are transmitted in the form of air pressure to the human body. The real-time bidirectional human-machine interface can help a patient with lower limb paralysis to control the exoskeleton with his/her healthy side and simultaneously perceive motion on the paralyzed side by EPP. The interface rebuilds a closed-loop motion control system for paralyzed patients and realizes harmonious control of the human-machine system.     

Low-Dose X-ray CT Reconstruction via Dictionary Learning

Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures.     

个性化推荐在移动互联网业务中的应用

以SoLoMo为标志的新一轮商业模式带动了移动互联网时代用户的上网行为及消费方式的转变,用户对互动性、实时性服务的需求愈发迫切,服务差异化和需求个性化的期望也为数据挖掘和应用提供了新的机遇和挑战。本文从移动互联网用户的行为知识库开放平台、智能化用户模型关键技术、个性化信息推荐及应用等几个方面,探索如何构造一个共赢的移动生态产业链体系。