An encouraging technology that grabs the clash between spectrum scarcity and underutilization is cognitive radio (CR), spectrum sensing is the main task of cognitive radio. Cooperative spectrum sensing overcome the adverse effect of shadowing and multipath. In this paper we are focusing on the optimization of cooperative spectrum sensing. Optimization strategy is proposed in order to optimize the overall performance by variation of SNR. In this technique we consider three parameters, spectrum sensing technique used locally, SNR and the number of users. Decision made by all the users is sent to the fusion center which estimate the final presence or absence of primary user.
The cloud computing paradigm has achieved widespread adoption in recent years. Its success is due for the most part to customers' ability to use services on demand with a pay-as-you go evaluation model, that has tried convenient in several respects. Low prices and high flexibility create migrating to the cloud compelling. Despite its obvious benefits, however, several firms hesitate to "move to the cloud," principally thanks to issues associated with service availableness, information lock-in, and legal uncertainties.1 Lock in is especially problematic. For one issue, albeit public cloud availableness is usually high, outages still occur.2 Businesses bolted into such a cloud ar basically at a standstill till the cloud is back on-line. Moreover, public cloud suppliers typically don't guarantee explicit service level agreements (SLAs)3that's, businesses bolted into a cloud don't have any guarantees that it'll still give the desired quality of service (QoS). Finally, most public cloud suppliers' terms of service let that provider unilaterally amendment evaluation at any time. Hence, a business bolted into a cloud has no mid-or long run management over its own IT prices. At the core of of these issues, able to} determine a requirement for businesses to for good monitor the cloud they're victimization and be able to quickly "change horses"that's, migrate to a distinct cloud if they discover issues or if their estimates predict future problems.
Recently, the most notable field in virtual reality content is virtual reality game content. Virtual reality game content has a completely different play method from existing PC and mobile game content. Virtual reality game content wears HMD(Head Mounted Display), a device dedicated to virtual reality, on its head, and plays with a dedicated controller in its hand. With hardware and operation methods different from existing games, quality evaluation is also required to evaluate virtual reality game content, unlike existing game content quality evaluation. Existing research on game quality evaluation is steadily developing with the revitalization of the industry, but research on virtual reality game content quality evaluation is insufficient as an early market for new hardware and platforms. According to this industrial background, small and medium-sized game content developers have difficulties in conducting quality evaluation. The reason is the lack of professionals who can exclusively evaluate the quality of game content. This paper proposed a checklist that can conduct quality evaluation even in situations where there is a shortage of professional manpower using the quality characteristic model of ISO/IEC 25010.
The game industry is an industry that has continued to grow mainly in online and mobile games, but due to COVID-19 that occurred in January 2020, the number of game users increased rapidly than before, entering a high growth trend. Therefore, this study was conducted to examine the changes in the overall game industry, so that this study found out the current status of South Korea and the Chinese game industry, which is a major exporter of Korean games after COVID-19 outbreak. Data collection and text analysis were performed using big data analysis solutions including Textom and Ucinet. The data collection period is from January 1, 2020 to August 30, 2021, and game-related online documents and news articles from South Korea and China were used. After that, important keywords were classified and frequency, connection centrality analysis, and CONCOR analysis were conducted. The results were summarized as follows. There were a total of four issues in the South Korean game industry including e-sports industry, industrial trend, shutdown system, and game law revision and three issues in China's game industry including leisure activity, corporate trend, and content industry.
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