Alpha-CIR Model with Branching Processes in Sovereign Interest Rate Modelling

We introduce a class of interest rate models, called the $\alpha$-CIR model, which gives a natural extension of the standard CIR model by adopting the $\alpha$-stable L{\'e}vy process and preserving the branching property. This model allows to describe in a unified and parsimonious way several recent observations on the sovereign bond market such as the persistency of low interest rate together with the presence of large jumps at local extent. We emphasize on a general integral representation of the model by using random fields, with which we establish the link to the CBI processes and the affine models. Finally we analyze the jump behaviors and in particular the large jumps, and we provide numerical illustrations

Neutron Density Distributions of Neutron-Rich Nuclei Studied with the Isobaric Yield Ratio Difference

The isobaric yield ratio difference (IBD) between two reactions of similar experimental setups is found to be sensitive to nuclear density differences between projectiles. In this article, the IBD probe is used to study the density variation in neutron-rich $^{48}$Ca. By adjusting diffuseness in the neutron density distribution, three different neutron density distributions of $^{48}$Ca are obtained. The yields of fragments in the 80$A$ MeV $^{40, 48}$Ca + $^{12}$C reactions are calculated by using a modified statistical abrasion-ablation model. It is found that the IBD results obtained from the prefragments are sensitive to the density distribution of the projectile, while the IBD results from the final fragments are less sensitive to the density distribution of the projectile.Comment: 3 figure

Exploring the Influencing Factors of IP Film Rating by Sentiment Analysis and GMM

Recently, intellectual property (IP) film has become an important accessory for entertainment, and its rating has become the focus of quality evaluation. However, existing research seldom conducts study on influencing factors of rating. In this paper, we use sentiment analysis and generalized method of moments (GMM) to explore the factors that affect IP film rating. We take advantage of production, broadcast, genre and audience feedback to construct six explanatory variables, including actor influence, screenwriter participation, broadcast time, broadcast platform, genre, and adaptation satisfaction. We use LLC, IPS and Sargan tests to conduct variable stability test and model setting test. From the regression results of 134 IP films that obtained by sample filtering, the impact of each influencing factor on the rating is obtained. We found that short-term historical rating, actor influence, adaptation satisfaction and screenwriter participation positively affect current rating. While, long-term historical rating has a negative impact on current rating. In addition, broadcast time and broadcast platform have imposed positive impact on IP film rating, and genre has only a weak impact on rating. Our work provides advice for IP film producers, prompting them to improve quality by emphasizing celebrity effects and author participation

Study on Downlink Spectral Efficiency in Orthogonal Frequency Division Multiple Access Systems

In previous studies on the capacity of orthogonal frequency division multiple access (OFDMA) systems, it is usually assumed that co-channel interference (CCI) from adjacent cells is a Gaussian-distributed random variable. However, very-little work shows that the Gaussian assumption does not hold true in OFDMA systems. In this paper, the statistical property of CCI in downlink OFDMA systems is studied, and spectral efficiency of downlink OFDMA system is analyzed based on the derived statistical model. First, the probability density function (PDF) of CCI in downlink OFDMA cellular systems is studied with the considerations of path loss, multipath fading and Gaussian-like transmit signals. Moreover, some closed-form expressions of the PDF are obtained for special cases. The derived results show that the PDFs of CCI are with a heavy tail, and significantly deviate from the Gaussian distribution. Then, based on the derived statistical properties of CCI, the downlink spectral efficiency is derived. Numerical and simulation results justify the derived statistical CCI model and spectral efficiency.Comment: 23 pages, 8 figures, IET Communications, 201

NasHD: Efficient ViT Architecture Performance Ranking using Hyperdimensional Computing

Neural Architecture Search (NAS) is an automated architecture engineering method for deep learning design automation, which serves as an alternative to the manual and error-prone process of model development, selection, evaluation and performance estimation. However, one major obstacle of NAS is the extremely demanding computation resource requirements and time-consuming iterations particularly when the dataset scales. In this paper, targeting at the emerging vision transformer (ViT), we present NasHD, a hyperdimensional computing based supervised learning model to rank the performance given the architectures and configurations. Different from other learning based methods, NasHD is faster thanks to the high parallel processing of HDC architecture. We also evaluated two HDC encoding schemes: Gram-based and Record-based of NasHD on their performance and efficiency. On the VIMER-UFO benchmark dataset of 8 applications from a diverse range of domains, NasHD Record can rank the performance of nearly 100K vision transformer models with about 1 minute while still achieving comparable results with sophisticated models