浅谈电影频道互联互通环境下的播出流程问题

互联互通环境下的播出系统与传统播出系统相比,其视音频结构、同步系统、时钟系统等结构没有较大变化,主要增加了与全台网流程的交互、素材的交互以及相应的管理功能。本文将分为以下三个方面介绍电影频道互联互通环境下的播出系统:1、对"白皮书"互联互通的理解2、电影频道播出系统与全台网的互联互通接口3。

A dynamic decision model for portfolio investment and assets management

This paper addresses a dynamic portfolio investment problem. It discusses how we can dynamically choose candidate assets, achieve the possible maximum revenue and reduce the risk to the minimum level. The paper generalizes Markowitz’s portfolio selection theory and Sharpe’s rule for investment decision. An analytical solution is presented to show how an institu- tional or individual investor can combine Markowitz’s portfolio selection theory, generalized Sharpe’s rule and Value-at-Risk (VaR) to find candidate assets and optimal level of position sizes for investment (dis-investment). The result shows that the gen- eralized Markowitz’s portfolio selection theory and generalized Sharpe’s rule improve decision making for investment.

Heuristic Solutions of Virtual Network Embedding： A Survey

Network virtualization(NV) is considered as an enabling tool to remove the gradual ossification of current Internet. In the network virtualization environment, a set of heterogeneous virtual networks(VNs), isolated from each other, share the underlying resources of one or multiple substrate networks(SNs) according to the resource allocation strategy. This kind of resource allocation strategy is commonly known as so called Virtual Network Embedding(VNE) algorithm in network virtualization. Owing to the common sense that VNE problem is NP-hard in nature, most of VNE algorithms proposed in the literature are heuristic. This paper surveys and analyzes a number of representative heuristic solutions in the literature. Apart from the analysis of representative heuristic solutions, a taxonomy of the heuristic solutions is also presented in the form of table. Future research directions of VNE, especially for the heuristics, are emphasized and highlighted at the end of this survey.

Rule-based scheduling of multi-stage multi-product batch plants with parallel units

A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing.Firstly,hierarchical scheduling strategy is presented for solving the former sub-problem,where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages,and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective.Line-up competition algorithm(LCA)is presented to find out optimal order sequence and order assignment rule,which can minimize total flow time or maximize total weighted process time.Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders.Moreover,with the problem size increasing,the solutions obtained by the proposed approach are improved remarkably.The proposed approach has the potential to solve large size MMSP.

Research and strategy employment information based on extension data mining

This paper uses the extension theory of knowledge, probes into the problems of students employment of College of computer science, puts forward to the solving method,specific and provides corresponding strategies. At the same time, it carries on the appraisal to provide strategy, put forward to optimal strategies; it uses of baseing on extension data mining and mining association rules of the corresponding and finding the meaning relations existing in enterprise recruitment,

Evolution of a flexible rule for foraging that copes with environmental variation

Models of adaptive behaviour typically assume that animals behave as though they have highly complex, detailed strategies for making decisions. In reality, selection favours the optimal balance between the costs and benefits of complexity. Here we investigate this trade-off for an animal that has to decide whether or not to forage for food - and so how much energy reserves to store - depending on the food availability in its environment. We evolve a decision rule that controls the target reserve level for different ranges of food availability, but where increasing complexity is costly in that metabolic rate increases with the sensitivity of the rule. The evolved rule tends to be much less complex than the optimal strategy but performs almost as well, while being less costly to implement. It achieves this by being highly sensitive to changing food availability at low food abun- dance - where it provides a close fit to the optimal strategy - but insensitive when food is plentiful. When food availability is high, the target reserve level that evolves is much higher than under the optimal strategy, which has implications for our under- standing of obesity. Our work highlights the important principle of generalisability of simple decision-making mechanisms, which enables animals to respond reasonably well to conditions not directly experienced by themselves or their ancestors.