主持人“网感化传播”的话语特征与传播价值研究

“网感化传播”作为一种新兴的传播方式,其利用新媒体传播的特点,通过情感化的内容和互动性强的交流方式,有效地提升了信息的吸引力和传播效果,呈现出网络文化的独特风格。本文对“网感化传播”的话语特征进行深入分析,并探讨其传播价值,以期为主持人的能力塑造和传播实践提供有益参考。

《鲜生史》:纪录片的网感化表达

“网感”是互联网时代内容打造与传播的重要基点。纪录片的“网感化”表达是指文本的视听语言、叙事手法等逐渐顺应互联网思维逻辑和网络受众偏好的过程。纪录片《鲜生史》通过画面并置、影像抠图与合成等方式在影像表达上具备网感特征;在内容叙述层面,则依托文化母体通过跨码搬运、内容喂靶等手法赋予其网感特性。二者相互交融,使纪录片博取了较好的关注度与传播效果。

论网感化语境下青少年受众对影视明星人设的期待结构

网感化语境下影视明星人设传播的过程中,青少年受众不再是被动的接受者,而是明星人设塑造中的能动构成,以期待和想象参与明星人设的建构。在受众凝视、召唤结构、共生关系等因素的合力作用下,促成青少年受众参与明星人设的实现。受众的期待分为外表、气质、道德三重维度,逐层递进。明星利益方试图通过陌生化叙事、舞台真实性策略维持人设的有效性;明星人设的塑造和维持过程,也是粉丝群体和明星组建情感共同体和发展共同体的过程,形成共生效应;人设崩塌预示明星粉丝共同体的终结,受众期待也随之幻灭。未来的社会发展中,思考网感化语境产生的无限可能,是偶像价值生存需要做出的准备。

网生人文纪录片叙事特色分析——以《这货哪来的》为例

互联网媒体强大的传播能力为网生纪录片的出现提供了强有力的技术支撑,同时网生纪录片自身也在寻求创新和突破。相较于传统纪录片的宏大叙事,网生纪录片的选题更加符合观众的口味,同时在叙事语言上也更加贴近年轻人的表达方式。本文以网生纪录片《这货哪来的》为例,深入探讨其如何从货品的角度窥见众生百态,如何用多元融合的叙事语言彰显纪录片内涵,如何通过多维度的叙事建立精巧的叙事结构。

新闻播音员主持人的网感化表达

互联网诞生以来实实在在地改变了我们的生活,它在传媒领域更是催生了一场前所未有的变革。在融媒发展的环境下,主持人的表达和话语样态也需要与时俱进,接地气的语言一“网感化”的表达往往能凸显播音员主持人对于语言的驾驭能力和对新闻事件的感知能力。

浅析我国纪录片“翻红”的原因

当前,媒体融合传播已经成为了一种常态。这对纪录片的传播带来了巨大的机遇。特别是近年来,通过融合视频形式,纪录片传播再次“翻红”。文中主要就针对我国纪录片“翻红”的原因进行了分析,希望可以为纪录片的传播提供借鉴。

Energy-efficient mechanism based on ACO for the coverage problem in sensor networks

An energy-efficient heuristic mechanism is presented to obtain the optimal solution for the coverage problem in sensor networks. The mechanism can ensure that all targets are fully covered corresponding to their levels of importance at minimum cost, and the ant colony optimization algorithm （ACO） is adopted to achieve the above metrics. Based on the novel design of heuristic factors, artificial ants can adaptively detect the energy status and coverage ability of sensor networks via local information. By introducing the evaluation function to global pheromone updating rule, the pheromone trail on the best solution is greatly enhanced, so that the convergence process of the algorithm is speed up. Finally, the optimal solution with a higher coverage- efficiency and a longer lifetime is obtained.

Securing Sensor Networks Based on Optimization of Weighted Confidence

In this paper, an optimized rmlicious nodes detection algorithm, based on Weighted Confidence Filter （WCF）, is proposed to protect sensor networks from attacks. In this algorithm, each cluster head in a cluster-based hierarchical network figures out an average confidence degree by means of messages from its child nodes. The cluster head only accepts a message from the child node whose confidence degree is higher than the average. Meanwhile, it updates the confidence degrees for each of its child nodes by comparing the aggregation value and the received messages, and regards them as the weight of exactness of messages from nodes. A sensor node is judged to be rmlicious if its weight value is lower than the predefined threshold. Comparative simulation results verify that the proposed WCF algorithm is better than the Weighted Trust Evaluation （WTE） in terms of the detection ratio and the false alarm ratio. More specifically, with the WCF, the detection ratio is significantly improved and the false alarm ratio is observably reduced, especially when the malicious node ratio is 0.25 or greater. When 40% of 100 sensors are malicious, the detection accuracy is above 90% and the false alarm ratio is nearly only 1.8%.

The Glacier Area Changes in the Qangtang Plateau Based on the Multi-temporal Grid Method and its Sensitivity to Climate Change

Glacier area changes in the Qangtang Plateau are analyzed during 1970-2000 using air photos,relevant photogrammetric maps and satellite images based on the multi-temporal grid method.The results indicate that the melting of glaciers accelerated,only a few of glaciers in an advancing state during 1970-2000 in the whole Qangtang Plateau.However,the glaciers seemed still more stable in the study area than in most areas of western China.We estimate that glacier retreat was likely due to air temperature warming during 1970-2000 in the Qangtang Plateau.Furthermore,the functional model of glacier system is applied to study climate sensitivity of glacier area changes,which indicates that glacier lifespan mainly depends on the heating rate,secondly the precipitation,and precipitation increasing can slow down glacier retreat and make glacier lifespan prolonged.

A movement-assisted software-defined sensor network with NFV support

A flexible and controllable movement-assisted software-defined sensor network(MA-SDSN)based on the software-defined network(SDN)and network function virtualization(NFV)is proposed.First,a three-layer fundamental architecture is proposed to overcome the inherent distributed management and rigidity of the conventional wireless sensor networks.Furthermore,the platform for research and development of MA-SDSN is established,and the dumb node(DN),the software-defined node(SN)and the movement-assisted node(MN)are designed and implemented.Then,the southbound application programming interface(API)is designed to provide a series of frames for communication between controllers and sensor nodes.The northbound API is developed and demonstrated overall and in detail.The functions of the controller are presented including topology discovery,dynamic networking,packet processing,mobility management and virtualization.Followed by the MA-SDSN network model,a Markov chain-based movement-assisted weighted relocation(MMWR)topology control algorithm is proposed to redeploy the MNs based on the node status and weight.Simulation results and analysis indicate that the proposed algorithm based on the MA-SDSN extends network lifetime with a lower average power consumption.

Multi-objective optimization sensor node scheduling for target tracking in wireless sensor network

Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lifetime and improving tracking accuracy,sensor node scheduling for target tracking is indeed a multi-objective optimization problem.In this paper,a multi-objective optimization sensor node scheduling algorithm is proposed.It employs the unscented Kalman filtering algorithm for target state estimation and establishes tracking accuracy index,predicts the energy consumption of candidate sensor nodes,analyzes the relationship between network lifetime and remaining energy balance so as to construct energy efficiency index.Simulation results show that,compared with the existing sensor node scheduling,our proposed algorithm can achieve superior tracking accuracy and energy efficiency.

An evolutionary game based security decision algorithm for wireless sensor networks

When using traditional game methods to study information security of the wireless sensor networks,players are mostly based on the assumption of completely rational.Based on bounded rationality,the evolutionary game theory is used to establish the attack-defense model,analyze the strategy selection process of players,solve the evolutionarily stable strategy and design the optimal strategy selection algorithm.Then,considering the strategy dependence,the incentive and punishment mechanism is introduced to improve the replicator dynamic equation.The simulation results show that the model is reasonable and the algorithm is effective,which provides new theoretical support for the security of wireless sensor networks.

Energy-Efficient Distributed Lifetime Optimizing Scheme for Wireless Sensor Networks

In this paper, a sensing model for the coverage analysis of wireless sensor networks is provided. Using this model and Monte Carlo method, the ratio of private range to sensing range required to obtain the desired coverage can be derived considering the scale of deployment area and the number of sensor nodes. Base on the coverage analysis, an energy-efficient distributed node scheduling scheme is proposed to prolong the network lifetime while maintaining the desired sensing coverage, which does not need the geographic or neighbor information of nodes. The proposed scheme can also handle uneven distribution, and it is robust against node failures. Theoretical and simulation results demonstrate its efficiency and usefulness.

Adaptive Optimal Capacity Perception and Control for Wireless Multi-Hop Networks

In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes.

网络综艺节目的短视频化传播研究

由于网综节目变化能力快、制作周期短、风格多元化等特点,各大视频网站纷纷投身于网综制作,但也面临着题材单一、内容同质化等发展困境。如何摆脱类型同质化倾向,成为亟待解决的问题。而短视频利用碎片化、精简化等优势,成功占据新媒体用户的主要关注力,日益成为网综节目重要的推广手段。本文从发展背景、主要营销手段、未来发展趋势等方面,对网络综艺节目短视频化传播进行探析。

Node deployment strategy optimization for wireless sensor network with mobile base station

The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.

Optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing in cognitive radio network

In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.

Generation Y and Online Advertising： Perceptions and Preferences of Social Media Networking Sites （SMNSs）

Because most people consider advertising as an irritant and a distraction and would avoid it, should there be an alternative, advertising agencies strive to utilize the interactive, demassifying, and asynchronous qualities of newer technologies to create an appealing advertisement. The current study investigates whether college students＇ attitudes toward advertising on traditional media are different when online advertising is used, especially on Social Media Networking Sites （SMNSs）. Employing the concept of reciprocity （of replicating offline attitudes online） and the flow theory that relates one＇s concentration on an activity and its impact on other occurrences happening around him/her, 287 college students responded to a questionnaire on their perceptions of online advertising, their preferred SMNS, and the SMNS on which they would consider viewing an advertising message. The results showed that 57.8% of the participants avoid online advertising at all costs, which is similar to their offline perception of advertising. Some 42.2% reported that they may consider viewing online advertising if the attributes of relevance, interest, creativity, and interactivity are present, as in viral advertisement. In addition, among the four SMNSs reviewed--Facebook, MySpace, Twitter, and Linkedln--a majority of students indicated that Facebook is their preferred site for online advertising because it allows for creativity and they consider those messages credible, especially if their Facebook friends tagged, liked, or shared the advertisement.

Delay optimization for planar wireless sensor network with N-policy

In N-policy, the nodes attempt to seize the channel when the number of packets in the buffer approaches N. The performance of N-policy on the energy efficiency is widely studied in the past years. And it is presented that there exists one optimal N to minimize the energy consumption. However, it is noticed that the delay raised by N-policy receives little attention. This work mathematically proves the delay to monotonically increase with increasing N in the collision-unfree channel. For planar network where the near-to-sink nodes burden heavier traffic than the external ones, the data stemming from the latter undergo longer delay.The various-N algorithm is proposed to address this phenomenon by decreasing the threshold N of outer nodes. Without the impacting on the network longevity, the maximum delay among the network has decreased 62.9% by the algorithm. Extensive simulations are given to verify the effectiveness and correctness of our analysis.

Application of data fusion on multi-function earth drill

taking the bucket of multi function earth drill as an example, combining with the conception of multi sensor integration and data fusion, adopting the terrene column chart and digging torque formula as control dependence, the detecting method of the earth drill’s working state is introduced. Multi sensor data fusion is done with the aid of BP neural network in Matlab. The data to be interfused are pre processed and the program of simulation and “point checking” is given.