Effective DOA Estimation Under Low Signal-to-Noise Ratio Based on Multi-Source Information Meta Fusion

Efficiently performing high-resolution direction of arrival (DOA) estimation under low signal-to-noise ratio (SNR) conditions has always been a challenge task in the literatures. Obvi-ously, in order to address this problem, the key is how to mine or reveal as much DOA related in-formation as possible from the degraded array outputs. However, it is certain that there is no per-fect solution for low SNR DOA estimation designed in the way of winner-takes-all. Therefore, this paper proposes to explore in depth the complementary DOA related information that exists in spa-tial spectrums acquired by different basic DOA estimators. Specifically, these basic spatial spec-trums are employed as the input of multi-source information fusion model. And the multi-source in-formation fusion model is composed of three heterogeneous meta learning machines, namely neural networks (NN), support vector machine (SVM), and random forests (RF). The final meta-spec-trum can be obtained by performing a final decision-making method. Experimental results illus-trate that the proposed information fusion based DOA estimation method can really make full use of the complementary information in the spatial spectrums obtained by different basic DOA estim-ators. Even under low SNR conditions, promising DOA estimation performance can be achieved.     

5G时代下的移动自组织网络探讨

移动自组织网络在高带宽低延时的5G下,赋予更多的技术优势,使其综合性、应用性以及系统性都得到有效的提高,本文从基于5G移动自组织网络展开探讨,论述移动自组织mesh的网络架构技术及其应用前景和未来趋势。     

战略性新兴产业创新空间格局及影响因素研究——以湖南省为例

应用ArcGIS软件,选取2010年、2016年两个时间节点,用空间核密度、空间自相关、地理探测器等方法,分析了湖南省战略性新兴产业技术创新的空间分布与集聚特征,结果表明:湖南省战略性新兴产业创新活动整体呈现"东北多,西南少"的分布态势,空间集聚分布特征明显,长株潭城市群为空间热点与核心区域;专利数量空间核密度分布存在明显的"区域差异",具体表现为大面积的块状分布和小面积的零星核分布并存;湖南省战略性新兴产业创新空间分布主要受科学研究和技术服务业单位数、人均GDP、固定资产投资、农业机械总动力、消费品零售总额、卫生技术人员数等因素的影响。     

虚拟环境下机床主传动系统故障诊断的仿真实现

本文介绍了用AutoCAD完成机床主传动系统三维实体造型，用VisualC 、Visual LISP等工具完成主轴箱轴承、齿轮、轴等部位在运行中出现故障时的立体动画。经压电晶体加速度传感器实时检测机床的振动信号，对这些信号进行分析(统计处理、频谱分析等)提取出故障特征，经人工神经网络、模糊决策及专家系统等手段进行决策，判定故障部位和程度，可在微机上直观地观察主轴箱在运行过程中，各故障具体部位及损伤程度的虚拟现实情况。     

Learning experiences from digital laboratory safety training

We present a digital laboratory safety training platform called AALTOLAB which we have developed to address the need for more flexible and engaging ways to teach laboratory safety for chemical engineers. AALTOLAB consists of an interactive, web-based 360° virtual laboratory, integrated with a Moodle-based digital exam with automatic assessment. The modular platform offers different modules from general comprehensive laboratory training to more specialised modules. Students and staff can freely navigate in the laboratory rooms at any time and interact with different action points including interactive videos, slideshows, and minigames. Our technical solution allows teachers even with limited technological skills to easily modify the training materials in real time. The relationship of students’ learning experiences and level of learning is also discussed. We believe that our safety training concept facilitates deep learning and students’ engagement, thus improving safety culture in our laboratories.     

50年来辽宁省不同等级舒适日数演变及空间区划分析

根据1964—2015年辽宁省23个气象站点的逐日平均气温、相对湿度及平均风速资料,采用人体舒适度指数法计算人体舒适度指数,在季尺度上分析辽宁省不同等级舒适日数演变情况及典型旅游城市最佳旅游期;运用旋转经验正交函数分解法(REOF),分析人体舒适度指数季尺度空间变化特征,并应用ArcGIS软件进行舒适区域划分。结果表明:①辽宁省多年平均冷不舒适日数呈降低趋势,舒适日数呈增加趋势,热不舒适日数也呈微弱增加趋势;舒适程度夏季＞秋季＞春季＞冬季;②除冬季外5座典型旅游城市均适宜旅游,夏季为最佳旅游期;其中,沈阳、本溪更适宜春季旅游,大连更适宜秋季旅游。③辽宁省四季舒适度变化情况可大致划分为辽西、辽中、辽东三个区域,具体划分情况随季节有相应变化,总体舒适度由辽宁东部向西部逐渐递减。     

Mobile augmented reality based context-aware library management system

Mobile augmented reality has gained popularity in recent years due to the technological advances of smartphones and other mobile devices. One particular area in which mobile augmented reality is being used is library management. However, current mobile augmented reality solutions in this domain are lacking in context-awareness. It has been suggested in the literature that agent programming may be suitable at overcoming this problem, but little research has been conducted using modern mobile augmented reality applications with agents. This paper aims to bridge this gap through the development of an agent-based, mobile augmented reality prototype, titled Libagent. Libagent was subjected to five experiments to determine its suitability, efficiency, and accuracy for library management. The results of these experiments indicate that agent-based mobile augmented reality is a promising tool for context-aware library management.     

用于虚拟现实的360度视频编码技术新进展*

随着虚拟现实技术不断发展,360度视频编码开始成为研究热点。应用于虚拟现实的360度视频与传统的视频相比分辨率更高,编码数据量更大,在实际应用中面临传输带宽有限的瓶颈,编码效率问题有待解决。归纳分析了国际标准组织联合视频研究组（joint video exploration team, JVET）正在制定的360度视频编码投影变换技术及其编码优化方法,综合对比了各变换技术的编码性能。根据当前最新研究成果,对下一步研究需要解决的问题进行了探讨总结,给出未来的研究方向和思路。     

Peer-to-peer bichromatic reverse nearest neighbours in mobile ad-hoc networks

The increasing use of mobile communications has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Reverse Nearest Neighbour (RNN). An RNN query returns all objects that consider the query object as their nearest neighbour. Existing methods mostly rely on a centralised base station. However, mobile P2P systems offer many benefits, including self-organisation, fault-tolerance and load-balancing. In this study, we propose and evaluate 3 distinct P2P algorithms focusing on bichromatic RNN queries, in which mobile query peers and static objects of interest are of two different categories, based on a time-out mechanism and a boundary polygon around the mobile query peers. The Brute-Force Search Algorithm provides a naive approach to exploit shared information among peers whereas two other Boundary Search Algorithms filter a number of peers involved in query processing. The algorithms are evaluated in the MiXiM simulation framework with both real and synthetic datasets. The results show the practical feasibility of the P2P approach for solving bichromatic RNN queries for mobile networks.     

Computational Problem Solving in Spatial Substrates -- A Cognitive Systems Engineering Approach

The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. A common artificial intelligence approach to accomplish spatial tasks is to represent spatial configurations and tasks in form of detailed knowledge about various aspects of space and time. Suitable algorithms then use the representations to compute solutions to spatial problems. In comparison, natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects that are due to spatio-temporal affordances in their bodies and environments. Accordingly, we propose a paradigm that makes the spatio-temporal substrate an integral part of the engine that drives spatial problem solving. We argue that spatial and temporal structures in body and environment can substantially support (and even replace) reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation. While the approach is well known – for example, we employ diagrams as spatial substrate for geometric problem solving and maps for wayfinding – the underlying principle has not been systematically investigated or formally analyzed as a paradigm of cognitive processing. Topology, distance, and orientation constraints are all integrated and interdependent in truly 2- or 3-dimensional space. Exploiting this fact may not only help overcome the need for acquiring detailed knowledge about the interrelationships between different aspects of space; it also can point to a way of avoiding exploding computational complexity that occurs when we deal with these aspects of space in complex real-world scenarios. Our approach employs affordance-based object-level problem solving to complement knowledge-level formal approaches. We will assess strengths and weaknesses of the new cognitive systems paradigm.