Effects of Saving and Spending Patterns on Holding Time Distribution

The effects of saving and spending patterns on holding time distribution of money are investigated based on the ideal gas-like models. We show the steady-state distribution obeys an exponential law when the saving factor is set uniformly, and a power law when the saving factor is set diversely. The power distribution can also be obtained by proposing a new model where the preferential spending behavior is considered. The association of the distribution with the probability of money to be exchanged has also been discussed.Comment: 9 pages, 6 figure

Behind appearance : hidden dimensions in the work of Wassily Kandinsky and Paul Klee

What is the feel like to be a successful artist? Works being appreciated,being valuable,become famous all over the world? But what is under? What is behind? The audience seems never to know the story as well as the artworks. Take an example. When you look at The Scream of Edward Munch, what do you see? A melting image, a disgusting face, or the derived emoji, which is so popular on the SNS? What\u27s really behind the painting is Edward Munch\u27s illness, and decades of struggling under sickness, madness, and death. Most times, when the audience enjoys painting, the imagination can lead to empathy between the audience\u27s emotions and the work, which somehow may help the audience understand the work. Even if you know nothing about the background story, you can still catch the spirit,whether it\u27s dark or light, depressed, or brightful. But how do you extend that feeling to an abstract artwork? That is what I\u27m trying to explore in this thesis---Making the chosen works readable

Essays on the effects of rural-urban migration on migrants' behaviour in china : marriage, fertility, and cigarette smoking

The thesis examines the effects of rural-urban migration on migrants' marriage, fertility and smoking behaviour. This research attempts to fill these gaps. The data used are from the Chinese Rural Household sample of Rural-Urban Migration in China and Indonesia (RUMiCI) project. Chapter 2 analyses the effect of rural-urban migration on fertility behaviour of rural females in China. The results show that the rural-urban migration decreases the number of births and delays the timing of the first birth. On average, the first birth is delayed about seven months. Furthermore, it is suggested that female migrants postpone their marriages, and subsequently the timing of the first birth. Chapter 3 examines the correlation between the timing of the first marriage and the first rural-urban migration. It is found that male migrants marry four months earlier and female migrants four months later than their rural counterparts. In details, the accelerating effect of migration for males significantly depends on the duration of migration; for females, the postponement effect of migration varies across birth cohorts. Chapters 4 and 5 explore the effect of rural-urban migration on cigarette smoking from two perspectives - smoking prevalence and age of smoking onset. The results show that the rural-urban migration has a significant and positive effect on current smoking prevalence. In terms of the timing of smoking onset, rural-urban migration can increase the hazard rate of smoking substantially, and counterfactual experiments show that the lifetime prevalence of smoking can also be increased significantly. More alarmingly, the effect of migration is extremely substantial for younger birth cohorts

Agnostically Learning Boolean Functions with Finite Polynomial Representation

Agnostic learning is an extremely hard task in computational learning theory. In this paper we revisit the results in [Kalai et al. SIAM J. Comput. 2008] on agnostically learning boolean functions with finite polynomial representation and those that can be approximated by the former. An example of the former is the class of all boolean low-degree polynomials. For the former, [Kalai et al. SIAM J. Comput. 2008] introduces the l_1-polynomial regression method to learn them to error opt+epsilon. We present a simple instantiation for one step in the method and accordingly give the analysis. Moreover, we show that even ignoring this step can bring a learning result of error 2opt+epsilon as well. Then we consider applying the result for learning concept classes that can be approximated by the former to learn richer specific classes. Our result is that the class of s-term DNF formulae can be agnostically learned to error opt+epsilon with respect to arbitrary distributions for any epsilon in time poly(n^d, 1/epsilon), where d=O(sqrt{n}cdot scdot log slog^2(1/epsilon))