Regional Integration: The Next Wave

The nature and extent of trade has changed over time as transport technologies, production technologies and the rules of trade have evolved. As briefly discussed by Goldstein and van Lieshout in Chapter 7 of this Handbook, the multilateral trade rules currently governing world trade are a relatively recent phenomenon from a historical perspective. The General Agreement on Tariffs and Trade (GATT) celebrated its 70th anniversary in 2017. Before the existence of the GATT, international trade was largely governed by bilateral treaties among a limited numbers of players and by power relationships resulting from colonialism. The shift in global power relationships in the aftermath of World War II opened the door for a new set of rules for trade that ended up being multilateral in nature

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets

Parametric modelling of growth curve data: An overview

Alc, BIC, covariance structure, longitudinal data, mean structure, repeated measures, RLRT, 62J05, 62F10, 62P10,