This study examines the nexus between selected cryptocurrencies represented by Bitcoin and Ethereum and the expected market volatility denoted by the VIX index. We use daily data for the period of 06/01/2021 – 07/07/2023. Using Hong (2001) and Hong et al. (2009) Granger causality tests we find no causality in mean, however, we find strong bidirectional causality in variance for the variables at the 5% significance level across all lag lengths. At the time-varying causality analysis, we find BTC causes VIX in the 1st lag. The analysis findings have important implications for portfolio managers and potential investors. Although no direct causal relationship was found between Bitcoin and VIX, or Ethereum and VIX in terms of returns, the strong bidirectional causality in variance suggests that changes in volatility can affect related assets. This information can be utilized by portfolio managers to effectively assess mandates and manage portfolio risk.
The development of autonomous vehicles has been a rapidly growing field, with increasing interest in the technology and its potential applications. However, there are currently no commercially available vehicles that can be classified as level 3 or higher on the Society of Automotive Engineers’ autonomy scale. One key aspect of advancing the technology is the optimization of the verification and validation process through the use of simulators. This paper presents an in-depth analysis of the architecture of an autonomous vehicle, developed and tested using Simulink. The focus of the paper is to provide a comprehensive understanding of the path planning phase in autonomous vehicles, which is a crucial aspect of the vehicle’s navigation and decision-making capabilities. Through this research, we aim to gain a deeper understanding of the underlying decision-making processes of autonomous vehicles.
Nowadays, computer games have gained immense popularity, captivating gamers who can easily spend hours engrossed in their laptops. However, not every game has the ability to keep players emotionally engaged. To achieve this, a game requires a unique storyline and well-developed characters, each with their own distinct traits. One genre that tends to be highly addictive is the "survival of the fittest" concept, where a player's success depends on their chosen gameplay strategy. This article explores the utilization of multivariate normal distribution and Poisson distribution for spawning items in "Battle Royale" games. The term "Battle Royale" refers to a specific genre of video games that has gained significant traction in recent years. These games typically involve a large number of players competing simultaneously within a single game session, often ranging from tens to hundreds of participants. The primary objective for players in battle royale games is to survive and outlast their opponents, creating an intense and competitive gaming experience.
At present, LDA topic model, Word2Vec model and knowledge graph have been used to recommend doctors for online consultation, and have achieved certain results. However, the single word vector model will lead to some deficiencies in the recommendation results. In online consultation, patients have short questions and doctors have long answers, which is difficult to deal with uniformly. Therefore, this paper combines Sentence BERT sentence vector model, ELMO word vector model and doctor attribute model to build a set of combined recommendation model for intelligent doctor recommendation. In the empirical study, this paper chooses a large number of test patients as the research object. The results show that compared with the single word vector model, the combined recommendation model proposed in this paper is better in the accuracy rate, mean reciprocal rank and coverage rate of doctor recommendation.
Several probabilistic decoders of second-order Reed-Muller codes are considered. These decoders share a common construction idea based on the differentiation of polynomials. The properties of these decoders are considered. It is shown that it is possible to modify these decoders for the case of any odd Galois field of cardinality more than 3, but it is theoretically impossible to justify the correctness of such algorithms.
