Multimodal sensing and active continuous closed‐loop feedback for achieving reliable manipulation in the outdoor physical world

The use of field robots can greatly decrease the amount of time, effort, and associated risk compared to if human workers were to carryout certain tasks such as disaster response. However, transportability and reliability remain two main issues for most current robot systems. To address the issue of transportability, we have developed a lightweight modularizable platform named AeroArm. To address the issue of reliability, we utilize a multimodal sensing approach, combining the use of multiple sensors and sensor types, and the use of different detection algorithms, as well as active continuous closed‐loop feedback to accurately estimate the state of the robot with respect to the environment. We used Challenge 2 of the 2017 Mohammed Bin Zayed International Robotics Competition as an example outdoor manipulation task, demonstrating the capabilities of our robot system and approach in achieving reliable performance in the fields, and ranked fifth place internationally in the competition.     

REST API技术及在移动通信网络管理中的应用

介绍了目前最炙手可热的REST架构风格，该风格顺应Web2.0的兴起，完美的匹配了云计算时代来临的可扩展要求，在各种应用场景中都得到了充分的表现。根据其技术特点，分析了该风格的API在移动通信网络管理中的应用，从网管系统内部、网管系统之间以及网管系统与上层APP应用之间等多方面对是否适用于REST风格以及如何在合适的位置使用REST API进行了分析。     

基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines

In this article we illustrate a methodology for building cross-language search engine. A synergistic approach between thesaurus-based approach and corpus-based approach is proposed. First, a bilingual ontology thesaurus is designed with respect to two languages: English and Spanish, where a simple bilingual listing of terms, phrases, concepts, and subconcepts is built. Second, term vector translation is used – a statistical multilingual text retrieval techniques that maps statistical information about term use between languages (Ontology co-learning). These techniques map sets of t f id f term weights from one language to another. We also applied a query translation method to retrieve multilingual documents with an expansion technique for phrasal translation. Finally, we present our findings.     

改进HSR-FCN的服装图像识别分类算法研究

目前网络上的服装图像数量增长迅猛，对于大量服装图像实现智能分类的需求日益增加。将基于区域的全卷积网络（Region-Based Fully Convolutional Networks，R-FCN）引入到服装图像识别中，针对服装图像分类中网络训练时间长、形变服装图像识别率低的问题，提出一种新颖的改进框架HSR-FCN。新框架将R-FCN中的区域建议网络和HyperNet网络相融合，改变图片特征学习方式，使得HSR-FCN可以在更短的训练时间内达到更高的准确率。在模型中引入了空间转换网络，对输入服装图像和特征图进行了空间变换及对齐，加强了对多角度服装和形变服装的特征学习。实验结果表明，改进后的HSR-FCN模型有效地加强了对形变服装图像的学习，且在训练时间更短的情况下，比原来的网络模型R-FCN平均准确率提高了大约3个百分点，达到96.69%。     

移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

ProVoc: An app to train vocabulary depth in order to foster children's reading comprehension

Many studies have demonstrated the crucial role of vocabulary in predicting reading performance in general. More recent work has indicated that one particular facet of vocabulary (its depth) is more closely related to language comprehension, especially inferential comprehension. On this basis, we developed a training application to specifically improve vocabulary depth. The objective of this study was to test the effectiveness of a mobile application designed to improve vocabulary depth. The effectiveness of this training was examined on 3rd and 4th grade children's vocabulary (breadth and depth), decoding and comprehension performances. A randomized waiting-list control paradigm was used in which an experimental group first received the intervention during the first 4 weeks (between pretest and post-test1), thereafter, a waiting control group received the training for the next 4 weeks (between postest1 and posttest2). Results showed that the developed application led to significant improvements in terms of vocabulary depth performance, as well as a significant transfer effect to reading comprehension. However, we did not observe such a beneficial effect on either vocabulary breadth or written word identification. These results are discussed in terms of the links between vocabulary depth and comprehension, and the opportunities the app presents for remedying language comprehension deficits in children.     

Development of mobile miniature natural gas liquefiers

With increasing consumption of natural gas (NG), small NG reservoirs, such as coalbed methane and oil field associated gas, have recently drawn significant attention. Owing to their special characteristics (e.g., scattered distribution and small output), small-scale NG liquefiers are highly required. Similarly, the mixed refrigerant cycle (MRC) is suitable for small-scale liquefaction systems due to its moderate complexity and power consumption. In consideration of the above, this paper reviews the development of mobile miniature NG liquefiers in Technical Institute of Physics and Chemistry (TIPC), China. To effectively liquefy the scattered NG and overcome the drawbacks of existing technologies, three main improvements, i.e., low-pressure MRC process driven by oil-lubricated screw compressor, compact cold box with the new designed heat exchangers, and standardized equipment manufacturing and integrated process technology have been made. The development pattern of “rapid cluster application and flexible liquefaction center” has been eventually proposed. The small-scale NG liquefier developed by TIPC has reached a minimum liquefaction power consumption of about 0.35 kW·h/Nm³. It is suitable to exploit small remote gas reserves which can also be used in boil-off gas reliquefaction and distributed peak-shaving of pipe networks.     

On Cost Aware Cloudlet Placement for Mobile Edge Computing

As accessing computing resources from the remote cloud inherently incurs high end-to-end (E2E) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost (i.e., consisting of both the cloudlet cost and average E2E delay cost) has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing (CAPABLE) strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations.      

移动智能平台的可信计算体系结构与应用研究

在分析移动智能平台安全需求基础上,从逻辑原理、硬件组成、软件系统三个层面提出了移动智能平台的可信计算体系结构,之后提出了包含十种可信计算应用功能的全景图。