Predicting Successful Memes using Network and Community Structure

We investigate the predictability of successful memes using their early spreading patterns in the underlying social networks. We propose and analyze a comprehensive set of features and develop an accurate model to predict future popularity of a meme given its early spreading patterns. Our paper provides the first comprehensive comparison of existing predictive frameworks. We categorize our features into three groups: influence of early adopters, community concentration, and characteristics of adoption time series. We find that features based on community structure are the most powerful predictors of future success. We also find that early popularity of a meme is not a good predictor of its future popularity, contrary to common belief. Our methods outperform other approaches, particularly in the task of detecting very popular or unpopular memes.Comment: 10 pages, 6 figures, 2 tables. Proceedings of 8th AAAI Intl. Conf. on Weblogs and social media (ICWSM 2014

Consumer choice prediction : artificial neural networks versus logistic models

Conventional econometric models, such as discriminant analysis and logistic regression have been used to predict consumer choice. However, in recent years, there has been a growing interest in applying artificial neural networks (ANN) to analyse consumer behaviour and to model the consumer decision-making process. Neural networks are considered as a field of artificial intelligence. The development of the models was inspired by the neural architecture of human brain. Neural networks have been generally applied to two different categories of problems - recognition problems and generalisation problems. Recognition problems include visual applications such as learning to recognize particular words and speak them. Generalization problems include classification and prediction. Recently, ANN have been applied in the business and marketing research areas. Most of the studies have utilised the multi-layer feed-forward neural networks (MLFN) in analysing consumer choice problems. The purpose of this paper is to empirically compare the predictive power of the probability neural network (PNN), a special class of neural networks, and a MLFN with a logistic model on consumers' choices between electronic banking and non-electronic banking. Data for this analysis was obtained through a mail survey sent to 1,960 New Zealand households. The questionnaire gathered information on the factors consumers use to decide between electronic banking versus non-electronic banking. The factors include service quality dimensions, perceived risk factors, user input factors, price factors, service product characteristics, and individual factors. In addition, demographic variables including age, gender, marital status, ethnic background, educational qualification, employment, income, and area of residence are considered in the analysis. Empirical results showed that both ANN models (MLFN and PNN) exhibit a higher overall percentage correct on consumer choice predictions than the logistic model. Furthermore, the PNN demonstrates to be the best predictive model since it has the highest overall percentage correct and a very low percentage error on both Type I and Type II errors

An Interpolative Analytical Cache Model with Application to Performance-Power Design Space Exploration

Caches are known to consume up to half of all system power in embedded processors. Co-optimizing performance and power of the cache subsystems is therefore an important step in the design of embedded systems, especially those employing application specific instruction processors. In this project, we propose an analytical cache model that succinctly captures the miss performance of an application over the entire cache parameter space. Unlike exhaustive trace driven simulation, our model requires that the program be simulated once so that a few key characteristics can be obtained. Using these application-dependent characteristics, the model can span the entire cache parameter space consisting of cache sizes, associativity and cache block sizes. In our unified model, we are able to cater for direct-mapped, set and fully associative instruction, data and unified caches. Validation against full trace-driven simulations shows that our model has a high degree of fidelity. Finally, we show how the model can be coupled with a power model for caches such that one can very quickly decide on pareto-optimal performance-power design points for rapid design space exploration.Singapore-MIT Alliance (SMA

Propensity of architects to commit fraudulent certification in Malaysian housing development projects

The Housing Development (control & licensing) Act 1966 (Act118) with its delegated relevant Regulations, were enacted to control the contractual outcomes of public housing developments and housing agreement dispute. Based on this legal administrative framework are the Sale and Purchase Agreement (S&P) that set out the many various respective rights, duties and obligations that bind the parties to the building development contracts commonly administered by the therein nominated project architect. As the nominated architect is, under the auspices of the Pertubuhan Architect Malaysia (PAM), duty bound to competently, fairly and impartially direct and, resolve in the first instance, all queries and conflicts, the architect is procedurally deemed fully equipped to fulfill these duties.This research seeks to identify potential major pitfalls and loop-holes associated with the administration of public housing projects. The development contracts are governed by the Housing Development (control & licensing) Act 1966 and the Housing Developers (Control and Licensing) Regulations 1989. The identification of these issues will be of particular value to the relatively inexperienced architects having to deal with very experienced contract and regulations administrators. Particularly, these research outcomes seek to equip the inexperienced architect with the skills necessary to recognize the dangers of one or more of the contractual parties seeking to pressure the architect to make premature determinations and to issue ‘obvious’ fault certification. Keywords: Housing Development Act, Regulation, Premature and Fault Certification

Substructuring Method in Structural Health Monitoring

In sensitivity-based finite element model updating, the eigensolutions and eigensensitivities are calculated repeatedly, which is a time-consuming process for large-scale structures. In this chapter, a forward substructuring method and an inverse substructuring method are proposed to fulfill the model updating of large-scale structures. In the forward substructuring method, the analytical FE model of the global structure is divided into several independent substructures. The eigensolutions of each independent substructure are used to recover the eigensolutions and eigensensitivities of the global structure. Consequently, only some specific substructures are reanalyzed in model updating and assembled with other untouched substructures to recover the eigensolutions and eigensensitivities of the global structure. In the inverse substructuring method, the experimental modal data of the global structure are disassembled into substructural flexibility. Afterwards, each substructure is treated as an independent structure to reproduce its flexibility through a model-updating process. Employing the substructuring method, the model updating of a substructure can be conducted by measuring the local area of the concerned substructure solely. Finally, application of the proposed methods to a laboratory tested frame structure reveals that the forward and inverse substructuring methods are effective in model updating and damage identification

Solution Of Wheeler-De Witt Equation, Potential Well And Tunnel Effect

This paper uses the relation of the cosmic scale factor and scalar field to solve Wheeler-DeWitt equation, gives the tunnel effect of the cosmic scale factor a and quantum potential well of scalar field, and makes it fit with the physics of cosmic quantum birth. By solving Wheeler-DeWitt equation we achieve a general probability distribution of the cosmic birth, and give the analysis of cosmic quantum birth.Comment: 12 page