Imran Hussain Shah

Bio: Imran Hussain Shah is an academic researcher from University of Bath. The author has contributed to research in topics: Monetary policy & Inflation. The author has an hindex of 5, co-authored 18 publications receiving 120 citations. Previous affiliations of Imran Hussain Shah include University of Leicester.

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis.

Abstract: Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features.

Three essays on monetary policy and inflation in developing countries

Abstract: The principal objective of this thesis is to evaluate appropriate measures of inflation which are to be applicable for implementing monetary policy in developing countries. The first essay attempts to assess real effects of high inflation episodes for Indonesia, Malaysia and Pakistan. In order to investigate the real effects of high inflation episodes, the study adopts an indicator for the inflationary real effect, named inflationary real response (IRR), which is the difference between the expected and output-neutral inflation. Both the expected and output-neutral inflation are computed as the decomposition of shocks induced in the vector autoregressive (VAR) model. The main finding of this chapter is that there is a positive real effect in economic growth in the period after high inflation. The second essay investigates the responses of real output and inflation to oil price, aggregate supply and demand shocks in the four Asian developing countries; Indonesia, Malaysia, Pakistan, and Thailand. The structural VAR model is used to identify the different shocks and to explore the relative contributions of these shocks in explaining macroeconomic fluctuations. It is found that oil price shocks have negligible effects on economic activities for all the examined countries. However, aggregate supply and demand shocks are key sources of variation in output and inflation. The final essay examines whether the central bank should target a broader measure of the price index that incorporates stock prices alongside the prices of current goods and services. The primary contribution of this chapter is the estimation of a price index that can be efficiently utilised by central banks aiming to minimise output volatility. The results suggest that the central bank should use a price index that gives a sizeable weight to the fundamental component of stock prices to minimise output gap variance.

Revisiting the Dynamics Effects of Oil Price Shocks on Small Developing Economies

Abstract: This paper examines the dynamic effects of oil price, aggregate demand and aggregate supply shocks on output and inflation in four small developing economies using a structural VAR model. For all countries, despite finding the expected response of output to oil price shocks, an upward causal effect of oil price innovations on the domestic price level is established which adversely accompanies the growth stimulating effects in oil-exporting countries. This paper also finds asymmetric effects of oil price changes on macroeconomic variables in all sample countries. Finally, our empirical results find two further things: firstly, that for Malaysia, Pakistan and Thailand, nominal demand and supply shocks are the main sources of fluctuations in inflation and output respectively, whereas for Indonesia the converse holds and secondly that whilst the 1998 recession was largely induced by only supply and demand shocks the recession of 2008-09 could potentially be explained by oil price changes.

반도체 공정 overview

Abstract: With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.