Unsupervised steganalysis over social networks based on multi-reference sub-image sets

Multimedia Tools and Applications - This work proposes a new unsupervised steganalysis scheme which mainly tackles the challenge in identifying individual JPEG image as stego or cover. The proposed...     

A new probability transformation method based on a correlation coefficient of belief functions

The Dempster-Shafer evidence theory is widely used in many fields of information fusion because of its advantage in handling uncertain information. One of the key issues in this theory is how to make decision based on a basic probability assignment (BPA). Currently, a feasible scheme is transforming a BPA to a distribution of probabilities. However, little attention was paid to the correlation between BPA and probability distribution. In this paper, a novel method about the probability transformation based on a correlation coefficient of belief functions is proposed. The correlation coefficient is a new measurement, which can effectively measure the correlation between BPAs. The proposed method aims at maximizing the correlation coefficient between the given BPA and the transformed probability distribution. On the basis of this idea, the corresponding probability distribution can be obtained and could reflect the original information of the given BPA to the maximum extent. It is valid to consider that the proposed probability transformation method is reasonable and effective. Numerical examples are given to show the effectiveness of the proposed method.     

适应于自动驾驶的计算结构与平台综述

信息与通信技术领域的不断发展,推动了自动驾驶汽车的巨大进步。自动驾驶汽车有效解决了用户对出行日益提高的安全、便捷、舒适、高效等个性化需求,有着巨大的商业前景和应用价值。首先从自动驾驶的定义出发,对自动驾驶汽车计算任务进行了分类总结,阐述了自动驾驶汽车集移动端、边缘节点和云端一体的计算结构。然后分类讨论了目前自动驾驶汽车移动端计算平台,呈现出异构多核的特点,并对当前主流的底层计算平台进行了对比分析。最后,从性能与成本和信息安全两个方面总结目前自动驾驶汽车计算结构和平台遇到的问题与挑战。     

Architecture design and implementation of image based autonomous car: THUNDER-1

Autonomous driving with high velocity is a research hotspot which challenges the scientists and engineers all over the world. This paper proposes a scheme of indoor autonomous car based on ROS which combines the method of Deep Learning using Convolutional Neural Network (CNN) with statistical approach using liDAR images and achieves a robust obstacle avoidance rate in cruise mode. In addition, the design and implementation of autonomous car are also presented in detail which involves the design of Software Framework, Hector Simultaneously Localization and Mapping (Hector SLAM) by Teleoperation, Autonomous Exploration, Path Plan, Pose Estimation, Command Processing, and Data Recording (Co- collection). what’s more, the schemes of outdoor autonomous car, communication, and security are also discussed. Finally, all functional modules are integrated in nVidia Jetson TX1.

     

Natural tongue physique identification using hybrid deep learning methods

Multimedia Tools and Applications - Traditional Chinese Medicine (TCM) illustrates that the physique determines the susceptibility of human to certain diseases and treatment programs for illness....     

Optimal control data scheduling with limited controller-plant communication

This paper considers optimal control data scheduling for finite-horizon linear quadratic regulation (LQR) control of scalar systems with limited controller-plant communication. Both the single-system and multiple-system scenarios are studied. For the first scenario, we derive the necessary and sufficient condition for a comparison function to be positive. Using this condition, the optimality of an explicit schedule is extended from unstable systems in the existing work to general systems. For the second scenario, we are able to construct explicit optimal scheduling policies for three particular classes of problems. Numerical examples are provided to illustrate the proposed results.     

Conceptualization topic modeling

Multimedia Tools and Applications - Recently, topic modeling has been widely used to discover the abstract topics in the multimedia field. Most of the existing topic models are based on the...     

压力容器-保温层流道变形条件下临界热流密度试验研究

针对压力容器外部冷却(ERVC)应用中的压力容器-保温层流道(RPV-保温层流道)变形问题,利用提高临界热通量影响因素(FIMR)的试验装置,在相同流量范围开展了变形条件下壁面临界热流密度(CHF)的试验研究,分析了流道变形和流量变化对压力容器(RPV)下封头壁面CHF的影响规律,获得了流道变形情况下ERVC的安全裕度。结果表明:随着RPV下封头角度升高,循环流量增加,下封头壁面CHF增大;与原型流道相比,变形流道下封头壁面CHF的变化幅度小于7%,流道变化的影响并不显著;变形流道中,下封头壁面安全裕量最小的位置与原型流道相同,其安全裕量略有提高。     

Correction to: Theoretical prediction of radiation-enhanced diffusion behavior in nickel under self-ion irradiation

Nuclear Science and Techniques - 166.6-MHz quarter-wave $$\beta =1$$ superconducting cavities have been adopted for the High Energy Photon Source, a 6-GeV diffraction-limited synchrotron light...     

高剂量水平吸收剂量测量用辐射变色薄膜剂量计研究

为建立制备高剂量水平吸收剂量测量的辐射变色薄膜剂量计的方法,对相应的配方及制备工艺进行研究,批量制备了以尼龙为基材,副品红氰化物为染料的辐射变色薄膜剂量计。在60 Coγ参考辐射场中对辐射变色薄膜的各剂量学响应性能进行了研究,结果表明,重复性好于1.0%,在5~210kGy剂量范围内具有较好的剂量响应线性,辐射变色薄膜剂量计辐照后置于低温条件下贮存2周内信号较稳定。此外,该辐射变色薄膜剂量计在本实验范围内未发现明显的剂量率依赖性。通过上述剂量学性能研究,在线性剂量范围内,测量吸收剂量的扩展不确定度为4.2%(k=2)。通过在加速器上进一步实验表明,该膜可用于电子束辐照参数测量。