第三代移动通信智能天线的研究现状及发展趋势分析

本文首先简单地介绍移动通信发展以及第三代移动通信（3G）的技术特征和实现目标，并阐述了如何用多址来解决通信资源紧缺的问题，随后重点讲述智能天线的定义、优点、组成、工作原理、信道模型以及要解决的关键技术问题和发展现状。最后，提出了智能空分多址的概念，并对智能天线未来的发展进行了分析和预测。     

Extractive summarization using complex networks and syntactic dependency

The realization that statistical physics methods can be applied to analyze written texts represented as complex networks has led to several developments in natural language processing, including automatic summarization and evaluation of machine translation. Most importantly, so far only a few metrics of complex networks have been used and therefore there is ample opportunity to enhance the statistics-based methods as new measures of network topology and dynamics are created. In this paper, we employ for the first time the metrics betweenness, vulnerability and diversity to analyze written texts in Brazilian Portuguese. Using strategies based on diversity metrics, a better performance in automatic summarization is achieved in comparison to previous work employing complex networks. With an optimized method the Rouge score (an automatic evaluation method used in summarization) was 0.5089, which is the best value ever achieved for an extractive summarizer with statistical methods based on complex networks for Brazilian Portuguese. Furthermore, the diversity metric can detect keywords with high precision, which is why we believe it is suitable to produce good summaries. It is also shown that incorporating linguistic knowledge through a syntactic parser does enhance the performance of the automatic summarizers, as expected, but the increase in the Rouge score is only minor. These results reinforce the suitability of complex network methods for improving automatic summarizers in particular, and treating text in general.     

空间信息系统安全与防护技术

本文从空间信息系统面临的威胁出发 ,初步探讨了防截获反入侵、抗干扰、抗摧毁的多种措施以及它们的综合利用     

Rejoinder on “A distance-based statistical analysis of fuzzy number-valued data”

This note is a rejoinder on our paper in this issue. It attempts to provide some clarifications and thoughts in connection with the discussions/comments made about it by Didier Dubois and Sébastien Destercke. We hope our comments are at the level of the discussants'.     

A comprehensive survey and mathematical insights towards video summarization

Video Summarization is a technique to reduce the original raw video into a short video summary. Video summarization automates the task of acquiring key frames/segments from the video and combining them to generate a video summary. This paper provides a framework for summarization based on different criteria and also compares different literature work related to video summarization. The framework deals with formulating model for video summarization based on different criteria. Based on target audience/ viewership, number of videos, type of output intended, type of video summary and summarization factor; a model generating video summarization framework is proposed. The paper examines significant research works in the area of video summarization to present a comprehensive review against the framework. Different techniques, perspectives and modalities are considered to preserve the diversity of survey. This paper examines important mathematical formulations to provide meaningful insights for video summarization model creation.     

网络处理器技术综述

本文在归纳总结网络处理器所涉及的关键技术基础之上，介绍了网络处理器的主要体系结构及其在网络设备中的主要作用，并针对未来网络建设和网络设备发展的需要，提出了网络处理器可能的发展趋势。     

通用短波数据传输协议发展状况综述

主要介绍通用短波数据传输协议从产生到现在所经历的3个发展阶段，对3代协议的性能进行了简要比较。     

Sentiment-based sub-event segmentation and key photo selection

The number of people collecting photos has surged owing to social media and cloud services in recent years. A typical approach to summarize a photo collection is dividing it into events and selecting key photos from each event. Despite the fact that a certain event comprises several sub-events, few studies have proposed sub-event segmentation. We propose the sentiment analysis-based photo summarization (SAPS) method, which automatically summarizes personal photo collections by utilizing metadata and visual sentiment features. For this purpose, we first cluster events using metadata of photos and then calculate the novelty scores to determine the sub-event boundaries. Next, we summarize the photo collections using a ranking algorithm that measures sentiment, emotion, and aesthetics. We evaluate the proposed method by applying it to the photo collections of six participants consisting of 5,480 photos in total. We observe that our sub-event segmentation based on sentiment features outperforms the existing baseline methods. Furthermore, the proposed method is also more effective in finding sub-event boundaries and key photos, because it focuses on detailed sentiment features instead of general content features.