This paper studies a special class of population-size-dependent branching processes, in which the offspring distribution is supercritical when the population size does not exceed a given threshold 𝐾𝐾, and is subcritical or critical when the population size exceeds 𝐾𝐾. Up to now, the author has found no paper concerning continuous time threshold processes, and study of the discrete case is also limited to the extinction time 𝑇𝑇 and 𝔼𝔼𝑇𝑇. In this paper, both of the two cases were studied more thoroughly: for the discrete case, a limit theorem of the process has been proved; for the continuous case, the existence of Markovian threshold processes has been proved, and an equivalent condition for the process to extinct almost surely was also given. This paper also further generalized discrete time threshold processes by giving a random delay to the threshold’s influence of offspring distribution. The properties of these delayed threshold processes were studied, and a limit theorem was obtained.

The development of modern technology is closely related to the use of metals, whose demand has been shifting from common industrial metals to a variety of minor metals, such as cobalt or indium. The industrial importance and limited geological availability of some minor metals have led to them being considered more “critical.” In this research, we develop a novel approach to investigate metal criticality. Instead of quantifying the supply risk of critical metals with static indicators, as used in conventional criticality measures, we propose a dynamic method by looking at the stock trend of the major critical metal producers, who would, in turn, influence the future supply. This allows us to utilize high-frequency time series data in creating machine learning models that predict the stock prices using metal-related features. Specifically, we use regularized linear regression, logistic regression, support vector machine and gradient boosted trees as base models. An ensemble of them is then used for the final prediction, with methods including majority vote, logistic regression stacking, and gradient boosted trees stacking. Based on a misclassification error of 34% in the validation set, we further develop a stock trading strategy, which leads to a back-tested return of 313%, or an excess return of 147%. More importantly, a set of significant features selected by our models leads to insightful suggestions that certain unseeming features, such as markets of other metal cycles and currency exchange rates, may play important roles in influencing the supply of critical metals.

No abstract uploaded!

Sign language bridges the communication between the deaf-mute and the rest of the world. With the development of computer technology, the research on sign language recognition is prospering. Currently, there are two kinds of research methods. One is based on machine vision, the other is based on wearable input devices. Comparing with machine vision, wearable devices have the advantage of being able to get real-time information of the bend of the fingers and the movement of the hand. The essay applies recent technology in the field of voice recognition, and aims at finding out the best algorithm for medium vocabulary continuous sign language recognition. By building a hybrid Deep Neural Network-Hidden Markov Model, and designing and making a low-cost digital glove, the essay successfully compares the features between Dynamic Time Warping (DTW), Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) and Deep Neural Network-Hidden Markov Model (DNN-HMM) as of solving the problem of sign language recognition. Tests show that in terms of calculating the observation probability, DNN has a much better performance than HMM, especially when syntax is not provided, meaning that DNN better suits the developing trend of sign language recognition. Real-time recognition is achieved on the intelligent terminal with an accuracy of over 97%, using the trained model and a decoding program.

Quotient sets have attracted the attention of mathe- maticians in the past three decades. The set of quotients of primes is dense in the positive real numbers and the set of all quotients of Gauss- ian primes is also dense in the complex plane. Sittinger has proved that the set of quotients of primes in an imaginary quadratic ring is dense in the complex plane and the set of quotients of primes in a real quadratic number ring is dense in R: An interesting open question is introduced by Sittinger: Is the set of quotients of Hurwitz primes dense in the quaternions? In this paper, we answer the question and prove that the set of all quotients of Hurwitz primes is dense in the quaternions.