基于世界大学城空间的网络医学教育建设研究——以“医网情深”特色专栏构建为例

现代网络信息技术已经成为高校学生教育的新载体,利用世界大学城构建"医网情深"特色空间,学生不再把网络空间仅仅当成知识的海量存储库,而是转变为展示学生应用知识、转化技能的平台,并且利用这个平台做出服务社会的事情,实现"全员、全方位、全过程"育人的教育目标。

河北省网情舆论生态特点及对策研究

2015年1月26日,河北省全省宣传部长会议在石家庄召开。为推动全省网络宣传管理工作再上台阶,会议提出,要牢牢掌握网上舆论工作的主导权话语权,紧紧围绕网络空间全面清朗,坚持"用"、"管"并重,进一步提升用网管网的能力和水平。本文在总结2014年河北省网情舆论生态特点的基础上,提炼了2014年河北省十大网络舆情事件,并就进一步改善河北省网上舆论生态提出了若干对策建议。

基于机器学习的网情监测及预警系统

为解决互联网舆情转播速度快、分布广、不易监测及预警的问题,本文提出了一种基于机器学习的网情监测及预警系统,通过采用自动采集、自然语言处理、数据挖掘等关键技术,实现海量网络舆情的实时监测、态势感知、专题分析等特殊功能,提供自动预警和辅助决策等智能服务。文章首先对网络舆情的现状及行业痛点进行分析;然后逐一介绍了系统的整体架构以及数据采集、挖掘分析及应用服务等核心子系统;最后介绍了该系统在不同领域的应用效果。

教育原本可以这样表达——读《E网情深》有感

《E网情深》由李镇西编著，是朱永新教授任总主编的教育随笔系列丛书中的一本。这本书最初吸引我的是外观：封面上橙黄色的底色中间，有一块极富现代气息和冲击力的绿色图案，透射出旺盛的生命活力，昭示着教育需要用心去创造、用手去实践。

基于AI分析的本地网情聚合系统设计与实现

随着移动互联网的深度普及,普通用户从信息的接收者成为网络内容的创造者和传播者。一条域内的网情信息通过大众的关注、评论、转发,可以快速地触达全网,从而产生广泛的社会影响。利用Spark on YARN对爬虫采集的多平台信息进行大数据清洗,结合AI自然语言处理技术,对情感、行业分类、热词、热门话题等指标进行分析,通过ECharts大屏展示技术对各类指标进行直观展示,并基于用户配置的地域行业兴趣点给予消息推送,从而为地方政府提供直观的网情监督手段,进而为其智慧政务的建设贡献力量。

片名：一网情深

“柏菲”这款新碟，让旗下众多演唱好手轮番上阵，留下真声，也留住真情。碟名取得有意思，一往情深变成了一“网”情深。似欲以情歌为网，编织更多更好的深情故事。网上有人说，

网络歌曲的传播学分析:以《E网情深》为例

《月光百合》、《你是我的玫瑰》、《吉祥三宝》,这些都是脍炙人口的网络流行歌曲,得到广大网民的支持和热爱,从而在大江南北广为传唱。网络歌曲一般指通过网络传播的、由网民原创、翻唱、改唱的歌曲,是网民直抒胸臆、表达个性的一种文化手段。网民能够通过音乐网站、讨论区、博客等多种渠道发表自己的音乐作品。

互联网+国家治理

互联网是一把锋利的双刃剑,也是当今中国社会面临的一个巨大变量:互联网+国家治理等于许许多多的社会治理契机,而另一方面,也等于许多的问题、挑战与漏洞。如果处置得当,这将是政府进行公共治理和基层民主建设的一个崭新的平台,也将是引领我国国家治理体系与治理能力现代化转型的一个最大的动力。因此,在推动"四个全面"进程当中,国家应对互联网加以更大限度的整合和应用,并借鉴互联网的多元向度的方式将政府机构、公共组织以及公民个人这三者组合起来治理国家事务,让互联网在国家治理中发挥更大的作用。

互联网+国家治理

互联网是一把锋利的双刃剑,也是当今中国社会面临的一个巨大变量:互联网+国家治理等于许许多多的社会治理契机,而另一方面,也等于许多的问题、挑战与漏洞。如果处置得当的话,这将是政府进行公共治理和基层民主建设的一个崭新的平台,也将是引领我国国家治理体系与治理能力现代化转型的一个最大的动力。因此,在推动"四个全面"进程当中,国家应对互联网加以更大限度的整合和应用,并借鉴互联网的多元向度的方式将政府机构、公共组织以及公民个人这三者组合起来治理国家事务,让互联网在国家治理中发挥更大的作用。

曳纲形状和张力计算

本文将曳纲看作为柔索,把钢丝索曳纲在动水槽试验中所求得的水动力系数C_x、C_y、C_z和柔索平衡方程式相结合,建立求解曳纲形状和张力的常微分方程组,并利用电子计算机对这组方程式进行数值解,从而求得曳纲在水下的形状和张力。经过与网位仪在海上实测的数据相对照后,情况是令人满意的。

做好电力企业离退休老同志管理服务工作--实现国网“中国梦”

习近平总书记这样描述中国梦：“实现中华民族的伟大复兴，实现国家富强、民族振兴、人民幸福是中华民族近代以来最伟大的梦想。”这一重要论述指出了中国梦是全国人民共同享有、建设的同一个梦。为此，国家电网公司提出“中国梦，国网情”的概念，是在国家电网顺应时代潮流的重大战略举措。作为国家电网公司的一员，我们始终致力于实现和谐美丽中国梦。我们必须充分重视离退休同志的生活，对于离退休人员要采用科学化的管理新思路，丰富他们的精神文化。本文主要分析了对于离退休人员的现状和在离退休同志管理制度中存在的问题，提出了几点科学化管理新思路的建议，提出了一些科学化管理思路，以期实现国网“中国梦”。

Study on Pests Forecasting Using the Method of Neural Network Based on Fuzzy Clustering

Aimed to the characters of pests forecast such as fuzziness, correlation, nonlinear and real-time as well as decline of generalization capacity of neural network in prediction with few observations, a method of pests forecasting using the method of neural network based on fuzzy clustering was proposed in this experiment. The simulation results demonstrated that the method was simple and practical and could forecast pests fast and accurately, particularly, the method could obtain good results with few samples and samples correlation.

浅析新媒体环境下如何应对网络舆情危机

互联网时代,网络热点层出不穷,舆情危机一触即发。例如前段时间,成都49中学学生坠亡等事件,引发了网友们的持续关注,使一度趋于平稳良好的网络舆情,一下子又迎来了网情危机高峰,成为人们关注热议的焦点。这再次说明了网情危机无处不在,应对网络舆情危机的弦始终不能松,也勾起了笔者对网络舆情危机的再思考。

Explicit Rate Based Transmission Control Scheme in Vehicle-to-lnfrastructure Communication Networks

In Vehicle-to-infrastructure(V2I)communication networks,mobile users are able to access Internet services,such as video streaming,digital map downloading,database access,online gaming,and even safety services like accident alarm,traffic condition broadcast,etc.,through fixed roadside units.However,the dynamics of communication environment and frequent changing topology critically challenge the design of an efficient transport layer protocol,which makes it difficult to guarantee diverse Quality of Service(QoS) requirements for various applications.In this paper,we present a novel transport layer scheme in infrastructure based vehicular networks,and aim to resolve some challenging issues such as source transfer rate adjustment,congestion avoidance,and fairness.By precisely detecting packet losses and identifying various causes of these losses(for example,link disconnection,channel error,packet collision,buffer overflow),the proposed scheme adopts different reacting mechanisms to deal with each of the losses.Moreover,it timely monitors the buffer size of the bottleneck Road-Side Unit(RSU),and dynamically makes transfer rate feedbacks to source nodes to avoid buffer overflow or vacancy.Finally,analysis and simulation results show that the proposed scheme not only successfully reduces packet losses because of buffer overflow and link disconnection but also improves the utilization efficiency of channel resource.

Risk-based water quality decision-making under small data using Bayesian network

A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data.

Predicting Complex Word Emotions and Topics through a Hierarchical Bayesian Network

In this paper, we provide a Word Emotion Topic （WET） model to predict the complex word e- motion information from text, and discover the dis- trbution of emotions among different topics. A complex emotion is defined as the combination of one or more singular emotions from following 8 basic emotion categories： joy, love, expectation, sur- prise, anxiety, sorrow, anger and hate. We use a hi- erarchical Bayesian network to model the emotions and topics in the text. Both the complex emotions and topics are drawn from raw texts, without con- sidering any complicated language features. Our ex- periment shows promising results of word emotion prediction, which outperforms the traditional parsing methods such as the Hidden Markov Model and the Conditional Random Fields（CRFs） on raw text. We also explore the topic distribution by examining the emotion topic variation in an emotion topic diagram.

SPEECH EMOTION RECOGNITION USING MODIFIED QUADRATIC DISCRIMINATION FUNCTION

Quadratic Discrimination Function （QDF） is commonly used in speech emotion recognition, which proceeds on the premise that the input data is normal distribution. In this paper, we propose a transformation to normalize the emotional features, emotion recognition. Features based on prosody then derivate a Modified QDF （MQDF） to speech and voice quality are extracted and Principal Component Analysis Neural Network （PCANN） is used to reduce dimension of the feature vectors. The results show that voice quality features are effective supplement for recognition, and the method in this paper could improve the recognition ratio effectively.

Research on College Frustrated Students＇ Network Mentality and Behaviors

Network has not only become a habit and lifestyle for university student, but also brought all sorts of ethical misconducts and ethical issues in society. Based on the analysis of college students＇ frustrations, this paper explores the causes of network behavior anomie for college students, which mainly include： dissatisfaction in real communication, game addiction to the network, craving online pornography, and hooking on online shopping. In addition, it also investigates the ways to wipe out mental frustration in such a cyber era. These ways mainly are to strenzthen online education and management, to make psychological counseling, and to carry on frustration education.

Hybrid Satellite-Aerial-Terrestrial Networks in Emergency Scenarios:A Survey

Natural disaster or large-scale unexpected events easily make the terrestrial network overloaded,paralyzed, or totally destroyed. It is highly demanded to build an emergency network which can be deployed rapidly, offer high data rate and wide coverage. The emergence of aerial platforms especially the low altitude platforms(LAPs) indicates a stable and reliable direction for the development of emergency network. Hybrid satellite-aerial-terrestrial(HSAT) networks have the ability to provide effective services rather than traditional infrastructures during the emergency situation. In this paper, the aerial platforms and the HSAT networks are surveyed and the key technologies are discussed from several aspects. The challenges of the HSAT networks are also outlined finally.

Multimodal emotion recognition based on deep neural network

In order to increase the accuracy rate of emotion recognition in voiceand video,the mixed convolutional neural network(CNN)and recurrent neural network(RNN)ae used to encode and integrate the two information sources.For the audio signals,several frequency bands as well as some energy functions are extacted as low-level features by using a sophisticated audio technique,and then they are encoded w it a one-dimensional(I D)convolutional neural network to abstact high-level features.Finally,tiese are fed into a recurrent neural network for te sake of capturing dynamic tone changes in a temporal dimensionality.As a contrast,a two-dimensional(2D)convolutional neural network and a similar RNN are used to capture dynamic facial appearance changes of temporal sequences.The method was used in te Chinese Natral Audio-'Visual Emotion Database in te Chinese Conference on Pattern Recognition(CCPR)in2016.Experimental results demonstrate that te classification average precision of the proposed metiod is41.15%,which is increased by16.62%compaed with te baseline algorithm offered by the CCPR in2016.It is proved ta t te proposed method has higher accuracy in te identification of emotional information.