Rational Analysis of University Administration Nomocracy

The university administration is the key to security teaching level and school efficiency, which play a crucial role in processes of reform of university education and improvement of the modern education system. Our country is promoting construction of society nomocracy. University Administration Nomocracy is an important part of promoting the construction of society nomocracy. It is able to ensure the effective operation of teaching and research work around university, in addition to promote the full implementation of university administration function. It has to rationally analyze administration nomocracy in aspect of university administration works and explore strategy to promote construction of nomocracy actively

Growth, financial development, market liquidity and risk

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThis thesis,firstly, studies the impact of financial liberalization and political instability on economic growth and quantitatively examines the relative importance of the identified underling reasons of Argentine riddle by using an innovative econometric methodology and unique data set: it presents power ARCH estimates for Argentina from 1896 to 2000. The main results show that the long-run effect of financial liberalization on economic growth is positive while the short-run effect is negative, albeit substantially smaller. The political instability effects are substantially larger in the short-run than in the long-run. We also investigate potential mechanisms for the effects of financial liberalization and political instability on economic growth: direct impact or happening through the variation of growth volatility. Our results also suggest that financial development, trade openness and political instability are the main factors to explain the Argentine decline. Furthermore, real business cycle variability - growth relationship and the link between inflation and its uncertainty are investigated by using monthly data of four Asian countries/regions (Japan, South Korea, Singapore and Taiwan) and parametric power ARCH methodology to proxy uncertainty. We fnd that more uncertainty about output leads to a higher rate of growth in three of the four countries/regions and the form of the uncertainty matters. Output growth reduces its uncertainty in all countries/regions via inflation uncertainty except Singapore. For all countries/regions, inflation significantly raises inflation uncertainty as predicted by Friedman. On the other hand, increased uncertainty affects inflation positively in Japan and Singapore, which support the Cukierman-Meltzer hypothesis. We find a negative sign for Taiwan which is in accordance with the Holland hypothesis when error term was normally distributed, however, this result is not statistically significant when the student-t distribution is applied. Interestingly, South Korea’s data reveals a positive sign initially, however, it turns around when a structural dummy is incorporated. This dramatic outcome in favour of the Holland hypothesis, and chimes in with Dueker and Kim (1999), who claim that the inflation was strictly controlled by the South Korean monetary authority. In addition, this thesis investigates two-way causal relationships between spread, volatility and volume in the FTSE100 stock index over the period from 1992 to 2004 by using bivariate AR-FI-GARCH model and multiple measurements of risk and spread. The measurements of the spread include relative bid-ask spread, effective bid-ask spread, the inventory cost component of the bid-ask spread and the information cost component of the bid-ask spread. Risk is proxied by two measurements of price volatility: the close-to-close volatility and the range-based volatility. We also take the impact of electronic trading into account. Our results suggest that the spread and volume are positively impacted by volatility simultaneously. In addition, both volatility and volume are negatively affected by the spread. Furthermore, we find that the inventory cost component of the spread has a negative effect on volatility, in contrast, the information component of the spread positively impacts volatility. These results support the argument that speculation generates volatility in the market and higher transaction costs bene t stability of the market

Efficient Journey Planning and Congestion Prediction Through Deep Learning

The advancements of technology continuously rising over the years has seen many applications that are useful in providing users with sufficient information to make better journey plans on their own. However, commuters still find themselves going through congested routes every day to get to their destinations. This paper attempts to delineate the possibilities of improving urban mobility through big data processing and deep-learning models. Essentially, through a predictive model to predict congestion and its duration, this paper aims to develop and validate a functional journey planning mobile application that can predict traffic conditions, allowing road users to make better informed decisions to their travel plans. This paper proposes a Multi-Layered Perceptron (MLP) deep learning model for congestion prediction and supplements a Linear Regression (LR) model to predict its duration. The proposed MLP-LR model performed reasonably well with an accuracy of 63% in predicting an occurrence of congestion. Some critical discussions on further research opportunities stemming from this study is also presented