Subjects: Digital Publishing >> New Media submitted time 2023-10-08 Cooperative journals: 《中国传媒科技》
Abstract：短视频在近几年以较快的速度发展成熟着,在很大程度上改变了原有的媒介传播模式和形态。许多官方主流媒体机构审时度势,通过开通抖音短视频账号,参与新媒体运营等方式丰富传播渠道,提升对舆论的把控与引导。本文主要以抖音短视频App内的主流媒体新闻生产为切入点,通过对现阶段短视频新闻及抖音短视频内容生产的基本特征、优势所在、不足之处等进行分析,进一步探究短视频整体行业的新闻作品生产、传播情况,并提出一定的合理化建议和可行性参考。
Subjects: Dynamic and Electric Engineering >> Electrical Engineering Subjects: Mathematics >> Control and Optimization. submitted time 2022-08-07
Xiaodong Zheng
Baorong Zhou
Xiuli Wang
Bo Zeng
Jizhong Zhu
Haoyong Chen
Peizheng Xuan
Waisheng Zheng
Abstract： Quick-start generation units are critical devices and flexible resources to ensure a high penetration level of renewable energy in power systems. By considering the wind uncertainty, and both binary and continuous decisions of quick-start units within the intraday dispatch, we develop a Wasserstein-metric-based distributionally robust optimization model for the day-ahead network-constrained unit commitment (NCUC) problem with mixed integer recourse. We propose two feasible frameworks for solving the optimization problem. One approximates the continuous support of random wind power with finitely many events, the other leverages the extremal distributions instead. Both solution frameworks rely on the classic nested column-and-constraint generation (C&CG) method. It is shown that due to the sparsity of L1-norm Wasserstein metric, the continuous support of wind power generation could be represented by a discrete one with a small number of events, and the extremal distributions rendered are sparse as well. With this reduction, the distributionally robust NCUC model with complicated mixed-integer recourse problems can be efficiently handled by both solution frameworks. Numerical studies are carried out, demonstrating that the model considering quick-start generation units ensures unit commitment (UC) schedules to be more robust and cost effective, and the distributionally robust optimization method captures the wind uncertainty well in terms of out-of-sample tests.
Subjects: Dynamic and Electric Engineering >> Electrical Engineering Subjects: Mathematics >> Control and Optimization. submitted time 2022-08-07
Abstract： In this paper, a study of the day-ahead unit commitment problem with stochastic wind power generation is presented, which considers conditional and correlated wind power forecast errors through a distributionally robust optimization approach. Firstly, to capture the characteristics of random wind power forecast errors, the least absolute shrinkage and selection operator (Lasso) is utilized to develop a robust conditional error estimator, while an unbiased estimator is used to obtain the covariance matrix. The conditional error and the covariance matrix are then used to construct an enhanced ambiguity set. Secondly, we develop an equivalent mixed integer semidefinite programming (MISDP) formulation of the two-stage distributionally robust unit commitment model with a polyhedral support of random variables. Further, to efficiently solve this problem, a novel cutting plane algorithm that makes use of the extremal distributions identified from the second-stage semidefinite programming (SDP) problems is introduced. Finally, numerical case studies show the advantage of the proposed model in capturing the spatiotemporal correlation in wind power generation, as well as the economic efficiency and robustness of dispatch decisions.
Subjects: Dynamic and Electric Engineering >> Electrical Engineering Subjects: Dynamic and Electric Engineering >> Engineering Thermophysics submitted time 2022-04-10
Abstract：
Exergy is an index to measure energy quality, which reveals the essence of work capacity loss in the process of energy transfer. In order to study the dynamic evolution mechanism of exergy in time-varying energy networks, the constitutive relations between physical quantities in energy networks are listed based on the energy network theory, and the generalized expressions of exergy are given, including the generalized description and loss equation of exergy based on the second law of thermodynamics, and the energy level factor is introduced to evaluate the energy quality. The dynamic evolution process of different forms of exergy in the energy transfer tube (line) is analyzed, including electric exergy, thermal exergy and pressure exergy, and the output equation and efficiency calculation method of exergy are given. The dynamic evolution process of exergy in energy conversion equipment is analyzed, and the loss, storage and efficiency of exergy are calculated. Finally, the dynamic evolution process of exergy in an integrated energy system is simulated by a specific example. The study of this paper can fully tap the energy efficiency potential of the integrated energy system, and lay a solid theoretical foundation for better realization of energy cascade utilization.
Peer Review Status:
Awaiting Review
Subjects: Materials Science >> Composite Material submitted time 2021-08-13
Abstract： "
Peer Review Status:Awaiting Review
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-10-11 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the challenges faced by the existing big data-oriented computing framework in the study of extensible machine learning, a distributed naive Bayesian text classification method based on MapReduce and Apache Spark framework is proposed. The proposed method explores the Bayesian network classifier by studying the adaptability of MapReduce and Apache Spark frameworks, and studies the existing computing framework for big data. First, the training sample data set is divided into m classes based on the naive Bayes text classification model. In the training phase, the output of the previous MapReduce is used as the input of the next MapReduce, and four MapReduce jobs are used to derive the model. This design process makes full use of the parallel advantages of MapReduce. Finally, when the classifier is tested, the value of the class label to which the maximum value belongs is fetched. Experiments in the new group’s dataset have resulted in more than 99% of the results on all five types of news data sets, and are all higher than the comparison algorithm. Proved the accuracy of the method of this article.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-07-23 Cooperative journals: 《计算机应用研究》
Abstract： Wearable medical devices with sensor continuously generate enormous data, due to the complexity of the data, it is difficult to process and analyze the big data for finding valuable information that can be useful in decision-making. In order to overcome this issue, this paper proposed a new architecture for the implementation of IoT to store and process scalable sensor data (big data) for health care applications. The proposed architecture consisted of two main sub architectures, namely, Meta Fog-Redirection (MF-R) and AWS key management mechanism. MF-R architecture used big data technologies such as Apache Pig and Apache HBase for collection and storage of the sensor data generated from different sensor devices and it also used kalman filter for removal of noise. AWS key management mechanism used a key management scheme to protect data in the cloud and prevent unauthorized access. When data was stored in the cloud, the proposed system could use stochastic gradient descent algorithms and logistic regression to develop a predictive model of heart disease. Simulation experiments show that compared with other algorithms, the proposed algorithm has smaller error and it has certain advantages in terms of throughput and accuracy.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-24 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problems and shortcomings of traditional methods in human motion recognition in classification decision, a novel nonlinear classification decision method based on deep neural network (DNN) and genetic algorithm (GA) merge algorithm is proposed. First, the proposed merging algorithm combines the feature extractors over the entire training set and combines them into two different independent networks. Then use DNN to initialize two independent networks and further use GA to merge the two networks. Then the deviation and weight of the network are expressed as a matrix between each layer of the network. Finally, use DNN to train the bias and weight of the network, and each row in the matrix is treated as a chromosome during the merge process. The experiment uses the standard MNIST data set to evaluate the performance of the proposed algorithm. The evaluation results showed that the crossover and mutation operations during the experiment increased the neuron nodes, improved the recognition performance, and weakened the irrelevant and related neuronal nodes. Therefore, the proposed algorithm has a lower error rate and better network performance.
Subjects: Biology >> Bioengineering submitted time 2017-09-20
Abstract：毕赤酵母作为常用的蛋白表达系统，广泛应用于实验室规模的蛋白质制备、表征以及结构解析等方面，已有上千种蛋白在毕赤酵母系统中成功地得到表达。在工业酶制剂领域，也有许多酶制剂包括植酸酶、脂肪酶、甘露聚糖酶、木聚糖酶等利用毕赤酵母实现了产业化规模的生产[1]。 酵母细胞壁在保护细胞完整性方面起到非常重要的作用，能够维持细胞渗透压平衡，在形态发生过程中产生并维持细胞的形态，并且在环境压力中有保护细胞的作用[2]。细胞壁主要由多糖和蛋白组成，其中多糖为β-1,3-葡聚糖，β-1,6-葡聚糖和几丁质，蛋白主要由N-和O-修饰的蛋白组成，在电子显微镜下观察发现，酵母的细胞壁厚约 200nm，分为电子密度不同的两层结构，外层甘露糖蛋白层和内层葡聚糖骨架[3]。GPI修饰的蛋白是一种通过糖脂共价连接在蛋白C端，从而将蛋白定位在细胞表面的一类蛋白。GPI修饰的蛋白在所有的真核细胞中都存在，并且其基本结构在大部分生物中都是保守的。通过对毕赤酵母全基因组中所有编码的蛋白序列进行分析，结合GPI型细胞壁蛋白的结构特征，最终在毕赤酵母GS115中发现50个潜在的GPI型细胞壁蛋白[4]，对这些蛋白的生化分析及功能鉴定需要进一步的探索。 通过对毕赤酵母GS115潜在的50个GPI细胞壁蛋白逐一进行单基因敲除，构建了GPI型细胞壁蛋白缺陷菌株库，研究了各细胞壁缺陷菌株在不同浓度碳源条件下的生长情况及细胞形态变化，以及细胞表面亲疏水变化及对细胞壁干扰剂的耐受性情况。研究发现敲除细胞壁蛋白会引起细胞多方面的变化，如对不同碳源的利用差异，对不同细胞壁干扰剂的耐受差异等。挑取一株甲醇耐受的菌株进行转录组学的分析，发现敲除后细胞代谢路径发生了明显变化，如细胞壁各组分的合成路径，细胞膜甾醇合成路径相关基因明显上调，同时一些胁迫路径也被激活，以抵抗高浓度甲醇对细胞的损害。通过对细胞壁蛋白功能进行深入的研究，将为毕赤酵母作为宿主菌表达外源蛋白提供重要的参考价值。
Subjects: Dynamic and Electric Engineering >> Electrical Engineering Subjects: Dynamic and Electric Engineering >> Engineering Thermophysics submitted time 2017-08-28
Abstract： Different types of energy systems are coupled by energy conversion devices (e.g., induction motors, centrifugal pumps, etc.). It is of great practical significance to study the dynamic characteristics and simulation method of multi-type energy system for the optimization design and performance analysis of multi-energy complementary system. In order to model and analyze the time-varying energy network, from the point of view of the essence of energy, lumped parameter models of time-varying transfer line (pipe) and energy conversion equipment are established through in-depth study of the mechanism of energy transfer and conversion. On the basis of the time-varying energy network model, a method of modeling and simulating the dynamic characteristics of the multi-energy complementary system by constructing time-varying energy network equations (including state equations and output equations) is proposed, then the validity and practicability of which are verified by a practical example. The research of this paper lays the foundation for the modeling, analysis, optimization and planning of time-varying energy network.
Peer Review Status:Awaiting Review
Subjects: Dynamic and Electric Engineering >> Electrical Engineering submitted time 2017-08-27
Abstract： The theory of spot pricing is the basis of power market design in many countries, but there are many problems in the practice of spot electricity market. Spot electricity price has two major drawbacks: one is that it is still based on the traditional hourly scheduling/dispatch model, ignores the crucial time continuity in electric power production and consumption and does not handle the intertemporal constraints seriously; the second is that it assumes that the electricity products are homogeneous in the same dispatch period and cannot distinguish the base, shoulder and peak load power with obviously different technical and economic characteristics. To overcome the shortcomings, this paper presents a continuous time commodity model of electricity, including spot pricing model and the model priced according to load duration. The market optimization models under the two pricing methods are established with the Riemann and Lebesgue integrals respectively and the functional optimization problem are solved by the Euler-Lagrange equation to obtain the market equilibria. The feasibility of pricing according to load duration is proved by strict mathematical derivation. The theory and methods proposed in this paper will provide new ideas and theoretical foundation for the development of electric power markets in China and all over the world.
Peer Review Status:Awaiting Review
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