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An Analysis and Empirical Study on the Generation Mechanism of Consumer Flow Experience in Brand Community 品牌社区消费者流动体验生成机制分析与实证研究
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35443
Jian Han
Brand community is a new type of community in the era of brand consumption formed by consumers with brand as the link, experience as the core, identity, sense of identity, belonging and selftranscendence as the goal. This paper mainly analyzes the phenomenon of flow experience produced by consumers in the brand community systematically, mainly from the basic connotation and generating mechanism of flow experience, discusses the factors and mechanisms that stimulate consumers to produce flow experience in brand community, and proves the phenomenon that consumers produce flow experience in brand community by combining with actual case analysis.
品牌社区是以品牌为纽带,以体验为核心,以身份、认同感、归属感和自我超越为目标的消费者在品牌消费时代形成的新型社区。本文主要系统地分析了消费者在品牌社区中产生的流动体验现象,主要从流动体验的基本内涵和产生机制入手,探讨了激发消费者在品牌社区中产生流动体验的因素和机制,并结合实际案例分析,证明了消费者在品牌社区中产生流动体验的现象。
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引用次数: 0
Wireless Sensor Missing Value Estimation Algorithm Based On Multi-Attribute 基于多属性的无线传感器缺失值估计算法
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35435
Xingliang Zhang, Tao Fang, Chun Yang, Zhengzheng Huang, Xiaodie Zhang
Because the wireless sensor is arranged in the environment of unmanned management and complex, in the process of collecting data and transmitting data, it often leads to data loss due to the influence of itself or external environment. The best way to reduce the impact of missing value is to estimate the missing value. In this paper, we propose a missing value estimation algorithm based on time attribute and trust mechanism. We use Arima to predict the time attribute, and use the relationship between current value, historical value and error to predict the future data. We use subjective logic to convert the interaction information between nodes into trust value, and then Linear Regression prediction value by selecting the number of trust nodes. Finally, according to the optimal fit degree, weight distribution is carried out to form the final prediction value. Because the algorithm not only considers the node data of the trusted neighbor, but also predicts the future data changes through the changes of its own historical data, it has higher accuracy and lower error when compared with other algorithms.
由于无线传感器布置在无人管理的环境中且复杂,在采集数据和传输数据的过程中,往往会由于自身或外界环境的影响而导致数据丢失。减少缺失值影响的最好方法是对缺失值进行估计。本文提出了一种基于时间属性和信任机制的缺失值估计算法。我们使用Arima来预测时间属性,并使用当前值、历史值和误差之间的关系来预测未来数据。我们使用主观逻辑将节点间的交互信息转换为信任值,然后通过选择信任节点的数量进行线性回归预测。最后,根据最优拟合度进行权重分配,形成最终预测值。由于该算法不仅考虑了可信邻居的节点数据,而且还通过自身历史数据的变化来预测未来数据的变化,因此与其他算法相比,具有更高的精度和更低的误差。
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引用次数: 0
Study on Dynamic Adaptive Bitrate Selection Algorithm for Mobile Streaming Media 移动流媒体的动态自适应比特率选择算法研究
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35432
Taoshen Li, Zhihui Ge, Jichang Chen
An energy-aware dynamic adaptive Bitrate selection algorithm (EDABS) was proposed to solve the problem of rate switching frequency and low energy utilization efficiency while receiving streaming media data. According to the monitored network bandwidth and streaming media coding rate, the algorithm adaptively adjusted the lower limit threshold of the terminal cache area, so that the size of the cache space was more fit the current bandwidth and streaming media coding rate. And then, it set a dynamic security boundary and response delay factor, and adaptively selected the next target video block's code rate. The experimental results show that proposed algorithm can better reduce rate switching frequency and improve the utilization efficiency of the energy.
针对接收流媒体数据时速率切换频率高、能量利用效率低的问题,提出了一种能量感知的动态自适应比特率选择算法(EDABS)。该算法根据监控的网络带宽和流媒体编码率,自适应调整终端缓存区域的下限阈值,使缓存空间的大小更适合当前带宽和流媒体编码率。然后,设置动态安全边界和响应延迟因子,自适应选择下一个目标视频块的码率。实验结果表明,该算法能较好地降低速率开关频率,提高能量利用效率。
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引用次数: 0
Design and Application of Intelligent Epidemic Prevention Monitoring System Based on Behavior Track 基于行为跟踪的智能防疫监测系统设计与应用
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35410
Maopu Wu, Jun Zhu, Guangteng Bian, Caiyun Liu
The novel coronavirus pneumonia is highly infectious and has a long incubation period. In order to solve novel coronavirus infection in enterprises, institutions and communities, such as detection and monitoring of early and latent period of pneumonia, contact personnel search and other issues, an intelligent epidemic prevention monitoring system has been developed based on the technologies of no body temperature detection, personnel positioning trajectory analysis, epidemic information filling, data analysis and intelligent alarm. The system has functions of filling in body temperature reports, reworking information, daily attendance cards, epidemic analysis reports, suspicious personnel contact and tracking, etc. it helps to report and isolate patients for treatment timely, and provides powerful data support for comprehensive monitoring of regional epidemic situation, effectively protecting people's health.
新型冠状病毒肺炎传染性强,潜伏期长。为解决新型冠状病毒感染在企事业单位和社区中,肺炎早期和潜伏期的检测和监测、接触人员搜索等问题,基于无体温检测、人员定位轨迹分析、疫情信息填充、数据分析和智能报警等技术,开发了一套智能防疫监测系统。系统具有填写体温报告、返工信息、每日考勤卡、疫情分析报告、可疑人员接触追踪等功能,有助于及时报告和隔离患者进行治疗,为区域疫情综合监测提供强大的数据支持,有效保护人民健康。
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引用次数: 1
Integrated Tunable Distributed Feedback Reflection Filter Based on Double-Layer Graphene 基于双层石墨烯的集成可调谐分布式反馈反射滤波器
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35447
Lang Xue, Wei Xu, Z. Zhu
A silicon waveguide integrated electrically tunable distributed feedback grating device based on double-layer graphene is proposed and analysed by mode coupling theory and finite element simulation method. The theroresults show that with the graphene fermi energy level change from 0. 5eV to 0. 8eV, the center wavelength of TM mode reflection spectrum shifts from 1. 55um to shorter wave by 3. 9nm, and the center wavelength of TE mode reflection spectrum shifts from 1. 89um to shorter wave by 4. 8nm. The graphene electrically tunable distributed feedback grating device may has potential application in the integrated tunable wavelength selection device.
提出了一种基于双层石墨烯的硅波导集成电可调谐分布反馈光栅器件,并利用模式耦合理论和有限元仿真方法对其进行了分析。结果表明,随着石墨烯的加入,费米能级从0。5eV到0。8eV时,TM模式反射光谱的中心波长从1。55um至短波3。, TE模式反射光谱中心波长从1。89毫米至4短波。8海里。石墨烯电可调谐分布反馈光栅器件在集成可调谐波长选择器件中具有潜在的应用前景。
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引用次数: 0
High-Tc rf SQUIDs with Large Flux Focusing 具有大通量聚焦的高tc射频squid
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35431
W. Tao
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引用次数: 0
Research on Intelligent Community Home- Based Elderly Supporting System Based on Blockchain Technology 基于区块链技术的智能社区居家养老系统研究
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35423
L. Chang, Ping Ren
The Aging of the Population has become a major challenge facing the community of shared future for mankind, and solving the problem of old-age care in the context of population aging has become an unavoidable social problem and a worldwide issue. In view of the problems existing in the model of community home-based elderly supporting in China, combined with the characteristics of decentralization and non-tampering of blockchain technology, the inevitability of the application of blockchain technology in the field of elderly supporting and its specific application form in Intelligent community are analyzed. The Intelligent community home-based elderly supporting system based on blockchain technology realizes” providing for the elderly and enjoying the fun", and provides data support for the development management and service quality monitoring of the industry of elderly supporting. 1 Research background 1.1 Background of population aging People and population are always the core of sustainable development. The trend of the global population development shows four characteristics: population growth, population aging, migration and urbanization. Among them, the population aging has become a major challenge facing the community of shared future for mankind. According to The 2019 Revision of World Population Prospects Report, published by the United Nations, shows that the proportion of the world’s population aged 65 and above to the total population is 9%, that is, one in every 11 people is aged 65 and over, and it is expected that the proportion will reach 15.9% in 2050, that is, one in every six people will be aged 65 and over. As early as 1999, China has stepped into the ranks of aging countries, and has been showing a rapid growth trend. According to the data of The Statistical Bulletin of National Economic and Social Development of the people's Republic of China in 2019, the proportion of people aged 65 and above to the total population is 12.6%, which is 3.6% higher than the world average in the same period. The population aging of China shows five characteristics: the number of elderly people is the largest in the world, the development speed of aging is amazing, the population grows old before getting rich, the
人口老龄化已成为人类命运共同体面临的重大挑战,在人口老龄化背景下解决养老问题已成为一个不可回避的社会问题和世界性问题。针对中国社区居家养老模式存在的问题,结合区块链技术去中心化、不可篡改的特点,分析了区块链技术在养老领域应用的必然性及其在智慧社区中的具体应用形式。基于区块链技术的智慧社区居家养老系统实现了“养老、寓养”,为养老行业的发展管理和服务质量监控提供数据支撑。1研究背景1.1人口老龄化背景人口和人口始终是可持续发展的核心。全球人口发展趋势呈现出人口增长、人口老龄化、人口迁移和城市化四个特征。其中,人口老龄化已成为人类命运共同体面临的重大挑战。根据联合国发布的《2019年世界人口展望报告修订版》显示,全球65岁及以上人口占总人口的比例为9%,即每11人中就有1人是65岁及以上人口,预计到2050年这一比例将达到15.9%,即每6人中就有1人是65岁及以上人口。早在1999年,中国就已步入老龄化国家的行列,并呈现出快速增长的趋势。根据《中华人民共和国国民经济和社会发展统计公报》2019年数据,65岁及以上人口占总人口的比例为12.6%,高于同期世界平均水平3.6个百分点。中国人口老龄化呈现出五大特点:老龄人口数量居世界之最;老龄化发展速度惊人;人口未富先老
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引用次数: 0
Cardiology Prediction Based on Machine Learning 基于机器学习的心脏病预测
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35399
Yu Shi, Qiuli Qin
Heart disease is an important disease that endangers human health, with a high mortality rate. Machine learning assisted diagnosis of medical data is a hot topic, and it has made great contributions in predicting patient outcomes and reducing mortality. Therefore, based on the heart disease index data, this paper uses Decision tree model, Clustering model, and Naive Bayes model to predict whether or not having heart disease. The results show that the Naive Bayes algorithm has better prediction accuracy and can assist doctors in diagnosis and treatment.
心脏病是危害人类健康的重要疾病,死亡率高。机器学习辅助医疗数据诊断是一个热门话题,它在预测患者预后和降低死亡率方面做出了巨大贡献。因此,本文基于心脏病指标数据,采用决策树模型、聚类模型和朴素贝叶斯模型来预测是否患有心脏病。结果表明,朴素贝叶斯算法具有较好的预测精度,可以辅助医生进行诊断和治疗。
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引用次数: 0
Price Prediction of Traditional Chinese Medicine Based on ARIMA and Improved Elman Neural Network 基于ARIMA和改进Elman神经网络的中药价格预测
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35433
Tao Fang, Xingliang Zhang, Chun Yang, Zhengzheng Huang, Xiaodie Zhang
The price’s change of traditional Chinese medicine contains linear, non-linear and other miscellaneous factors. It is difficult for people to use a separate model such as neural network model to judge its price trend. Based on the background, a combined forecasting model is proposed in this paper, it consists of Autoregressive Integrated Moving Average model and Elman neural network which is improved by correlation analysis. The combined forecasting model can use its two algorithm model to deal with the linear and nonlinear factors. Meanwhile, the innovation of this paper is using correlation analysis to import extra additional parameters for the neural network, which can increase its accuracy. A large number of traditional Chinese medicine’s price data was collected to be training samples, the final results show that the combined forecasting model has advantages over stability and accuracy than ARIMA or Elman neural network.
中药价格的变化包含线性、非线性等多种因素。人们很难使用神经网络模型等单独的模型来判断其价格走势。在此背景下,本文提出了一种由自回归综合移动平均模型和经相关分析改进的Elman神经网络组成的组合预测模型。该组合预测模型可以使用其两种算法模型来处理线性和非线性因素。同时,本文的创新之处在于利用相关分析为神经网络引入额外的附加参数,从而提高了神经网络的精度。收集了大量的中药价格数据作为训练样本,最终结果表明,该组合预测模型相对于ARIMA或Elman神经网络具有稳定性和准确性方面的优势。
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引用次数: 0
Signal Adaptive Control of Isolated Intersection Based on Type-Two Fuzzy Control 基于二类模糊控制的孤立交叉口信号自适应控制
Pub Date : 2021-03-13 DOI: 10.12783/DTCSE/CCNT2020/35395
Linlu Ma, Fuyang Chen, Li Wang
In this paper, the signal control problem of isolated intersection during peak period is studied based on the type-two fuzzy control method to reduce the vehicle delay of isolated intersection. Firstly, the traffic flow model and evaluation index model of isolated intersection are established, and the factors of saturation flow rate and lane length are fully considered. In order to relieve the traffic pressure effectively, a type-two fuzzy controller is proposed for the signal control method, which solves the coordination and dynamic uncertainty problems in the traffic of isolated intersection. By using adaptive genetic algorithm to optimize the parameters of membership function in the type-two fuzzy controller, the parameters of the type-two fuzzy controller can be adjusted in real time according to the change of traffic flow, so that the controller can achieve adaptive control effect of traffic signals. At last, the simulation results show that the type-two fuzzy controller designed in this chapter has a better control effect in the peak period of traffic flow and reduces the vehicle delay of isolated intersection. 1 Establishment of four phase isolated intersection model In the field of traffic control, the study of signal control algorithms at isolated intersections is the basis [1] . In recent years, the development of artificial intelligence technology is getting faster and faster, so the research on the intelligent control methods of isolated intersection signals is also increasing. Among them, fuzzy control is very popular in the field of traffic control [2] because it does not rely on the mathematical model of the controlled system. J. Guo proposed a particle swarm optimization to reduce vehicle delays based on Akcelik delay model [3] . Junjie Lu designed a two-step fuzzy controller for a isolated intersection system and optimized the controller parameters using a differential evolution algorithm. The results prove that the controller has achieved good control results [4] . M. J. Shirvani Shiri adopted a fuzzy control method to adjust the maximum green light time in response to real-time traffic conditions in an isolated intersection, proving the effectiveness and robustness of the proposed method [5-6] . D. Nagarajan proposed an improved interval neutron number scoring function using triangular interval type II fuzzy numbers and interval neutron number scores to control traffic flow by identifying intersections with more vehicles [7] . Based on the above discussion, this paper designs a type-two fuzzy controller. At the same time, the adaptive genetic algorithm was used to optimize the membership parameters
本文基于二类模糊控制方法,研究了隔离交叉口高峰时段的信号控制问题,以降低隔离交叉口的车辆延误。首先,建立孤立交叉口的交通流模型和评价指标模型,充分考虑饱和流率和车道长度等因素;为了有效缓解交通压力,提出了一种二类模糊控制器的信号控制方法,解决了孤立交叉口交通的协调性和动态不确定性问题。采用自适应遗传算法对二类模糊控制器中的隶属函数参数进行优化,使二类模糊控制器的参数能够根据交通流的变化进行实时调整,从而达到对交通信号的自适应控制效果。最后,仿真结果表明,本章设计的二类模糊控制器在交通流高峰时段具有较好的控制效果,能够降低孤立交叉口的车辆延误。在交通控制领域,孤立交叉口信号控制算法的研究是基础[1]。近年来,人工智能技术的发展越来越快,因此对孤立交叉口信号的智能控制方法的研究也越来越多。其中,模糊控制由于不依赖于被控系统的数学模型,在交通控制领域非常流行[2]。J. Guo提出了一种基于Akcelik延迟模型的粒子群优化方法[3]。陆俊杰针对孤立交叉口系统设计了一种两步模糊控制器,并采用微分进化算法对控制器参数进行了优化。结果证明该控制器取得了良好的控制效果[4]。M. J. Shirvani Shiri采用模糊控制方法根据孤立交叉口的实时交通状况调整最大绿灯时间,证明了所提出方法的有效性和鲁棒性[5-6]。D. Nagarajan提出了一种改进的区间中子数评分函数,利用三角区间II型模糊数和区间中子数评分,通过识别车辆较多的交叉口来控制交通流量[7]。在此基础上,本文设计了一种二类模糊控制器。同时,采用自适应遗传算法对隶属度参数进行优化
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引用次数: 0
期刊
DEStech Transactions on Computer Science and Engineering
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