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With the rise of computing power networks, a novel infrastructure centered around computational power has emerged as a key driver in the development of the information economy. Data, recognized as a crucial production factor in the digital era, serves as a vital pillar for constructing new development paradigms. The data factor market, acting as the link between data and computational power networks, is particularly critical. Its robust operation directly affects the sustainable development of computational power networks and is provided with crucial support for the information economy system. Therefore, the data products were treated as the focal point, while the processes involved in the data factor market and the inherent connections among these components were introduced. Subsequently, the existing work on three key aspects of the data factor market was studied, including data value, data pricing, and data transactions. Regarding data value assessment, key aspects such as relative data value evaluation were discussed, introducing indicator systems, indicator weights, and value indices. For data asset value assessment, traditional methods such as the cost method, income method, and market method were discussed, as well as emerging methods based on machine learning. In terms of data pricing models, existing methods were categorized into two main types: pricing for dataset products and pricing for data service products. Seven pricing methods were summarized, and the advantages, disadvantages, and applicable scenarios of each method were further analyzed. Regarding data transaction systems, the applications of centralized and distributed architectures in the data trading market were analyzed from the perspective of system architecture. The current status and prospects of both on-exchange and over-the-counter trading modes were then introduced.

At present, exercises have become a frequent international competitive exchange activity. To some extent, a country's exercise level also measures the country's comprehensive economic strength. The holding of various international and domestic exercise events directly leads to the explosive increase of exercise videos digital. Therefore, efficient exercise video analysis is necessary. With the expansion of multimedia techniques and the emergence of message highways, the storage and transmission of digital video is no longer a difficult thing. The holding of different exercise events directly leads to the explosive increase of exercise videos. Therefore, efficient exercise video analysis is very necessary. Computer techniques have injected new vitality into most industries, but their expansion in the exercise industry is relatively slow. The means used in this paper is picture sequence analysis. The basic operation of sequence picture analysis is to detect motion messages or aims from picture sequences. It is a very active branch of picture courseing and computer sight. Because it has been widely used in many aspects of national eco and military, its research has attracted the general concentration of scientists all over the world.

We study production-and-order strategy in a two-echelon supply chain consisting of a single manufacturer and a single retailer in which both market demand and spot price are uncertain. The retailer updates early demand information through observing new market signal during long production season. The retailer may order product before the demand is updated by signing wholesale price contract (called a contract order), or order from the manufacturer in spot market after the demand is updated (called a spot order). In a retailer-led Stackelberg game, we construct a two-stage dynamic decision model to derive the optimal equilibrium solutions for the production and order quantity under both contract order strategy and spot order strategy. We characterize the conditions under which demand information updating benefits or hurts the members and a win-win is achieved. In sharp contrast to the existing findings in that the retailer always prefers to order late until demand information is updated, we discover that the retailer may prefers to order early when the spot price uncertainty is above a certain threshold. Then, we design a single-side payment contract to stimulate the manufacturer to choose order mode satisfying the retailer's preference. [ABSTRACT FROM AUTHOR]

We consider a two-echelon supply chain consisting of one capacity-constrained supplier and two Cournot-competitive retailers. The incumbent retailer has private demand information and takes strategic information sharing to maximize its expected profit. The supplier carries out capacity allocation strategy when the capacity cannot satisfy both retailers' total order quantity. We model three scenarios of information sharing: (1) no member is informed; (2) only the entrant retailer is informed; and (3) both the supplier and entrant retailer are informed. We characterize the conditions under which information sharing may benefit or hurt the supply chain and different members and meaningful information sharing is achieved via "cheap talk". Compared with no information sharing, when only the entrant retailer is informed, the incumbent retailer always has incentive to deflate its demand information to make the entrant retailer order less. Both retailers cannot achieve meaningful information sharing. When the supplier and entrant retailer both are informed, the incumbent retailer faces a trade-off between the desire to receive more products and the fear of intense competition and high wholesale price. The meaningful information sharing is achieved and all members are benefitted. The numerical examples verify theoretical results. [ABSTRACT FROM AUTHOR]