ACQR: A Novel Framework to Identify and Predict Influential Users in Micro-Blogging

As key roles of online social networks, influential users in micro-blogging have the ability to influence the attitudes or behaviour of others. When it comes to marketing, the users’ influence should be associated with a certain topic or field on which people have different levels of preference and expertise. In order to identify and predict influential users in a specific topic more effectively, users’ actual influential capability on a certain topic and potential influence unlimited by topics is combined into a novel comprehensive framework named “ACQR” in this research. ACQR framework depicts the attributes of the influentials from four aspects, including activeness (A), centrality (C), quality of post (Q) and reputation (R). Based on this framework, a data mining method is developed for discovering and forecasting the top influentials. Empirical results reveal that our ACQR framework and the data mining method by TOPSIS and SVMs (with polynomial and RBF kernels) can perform very well in identifying and predicting influential users in a certain topic (such as iPhone 5). Furthermore, the dynamic change processes of users’ influence from longitudinal perspective are analysed and suggestions to the sales managers are provided

Kinetic Compensation Effect in Logistic Distributed Activation Energy Model for Lignocellulosic Biomass Pyrolysis

The kinetic compensation effect in the logistic distributed activation energy model (DAEM) for lignocellulosic biomass pyrolysis was investigated. The sum of square error (SSE) surface tool was used to analyze two theoretically simulated logistic DAEM processes for cellulose and xylan pyrolysis. The logistic DAEM coupled with the pattern search method for parameter estimation was used to analyze the experimental data of cellulose pyrolysis. The results showed that many parameter sets of the logistic DAEM could fit the data at different heating rates very well for both simulated and experimental processes, and a perfect linear relationship between the logarithm of the frequency factor and the mean value of the activation energy distribution was found. The parameters of the logistic DAEM can be estimated by coupling the optimization method and isoconversional kinetic methods. The results would be helpful for chemical kinetic analysis using DAEM

Theoretical Analysis of Double Logistic Distributed Activation Energy Model for Thermal Decomposition Kinetics of Solid Fuels

The distributed activation energy model (DAEM) has been widely used to analyze the thermal decomposition of solid fuels such as lignocellulosic biomass and its components, coal, microalgae, oil shale, waste plastics, and polymer etc. The DAEM with a single distribution of activation energies cannot describe those reactions well since the thermal decomposition normally involves multiple sub-processes of various components. The double DAEM employs a double distribution to represent the activation energies. The Gaussian distribution is usually used to represent the activation energies. However, it is not sufficiently accurate for addressing the activation energies in the initial and final stages of the thermal decomposition reactions of solid fuels. Compared to the Gaussian distribution, the logistic distribution is slightly thicker at the curve tail and suits better to describe the activation energy distribution. In this work, a theoretical analysis of the double logistic DAEM for the thermal decomposition kinetics of solid fuels has been systematically investigated. After the derivation of the double logistic DAEM, its numerical calculation method and the physical meanings of the model parameters have been presented. Three typical types of simulated double logistic DAEM processes have been obtained according to the overlapped situation of two derivative conversion peaks, namely separated, overlapped and partially overlapped processes. It is found that, for the partially overlapped process, the form of the minor peak (overlapped peak or peak shoulder) depends on the values of the frequency factor and heating rate. Considering the simulated processes and related examples from literature, the double logistic DAEM has been remarked as a more reliable tool with abundant flexibility to explain the thermal decomposition of various solid fuels. More accurate results are expected if the double logistic DAEM is coupled with the computational fluid dynamics (CFD) simulation for those reactions mentioned above

Poplar Wood Torrefaction: Kinetics, Thermochemistry and Implications

The kinetic and thermochemical models for poplar wood torrefaction were developed in the present work. The torrefaction kinetic model satisfactorily fitted the experimental thermogravimetric analysis (TGA) data of poplar wood torrefaction and provided a coherent description of the evolution of torrefaction volatile and solid products in terms of a set of identifiable chemical components and elemental compositions. The torrefaction thermochemical model described the thermochemical performance of poplar wood torrefaction processes. The results from the kinetic and thermochemical models for poplar wood torrefaction showed that (1) high temperature increases the evolution rate of torrefaction products, and favors the formation of torrefaction volatiles; (2) the heating rate has a slight effect on evolution for torrefaction process; (3) the mass and energy yields of torrefaction products are significantly influenced by both torrefaction temperature and residence time; (4) the heat of torrefaction reaction is mostly endothermic with a relatively small amount (less than 10% of the raw material energy content); (5) for the overall torrefaction processes, the sensible and latent energy of torrefaction products accounts for 5–18% of the total energy input and the remaining energy input transfers into the energy contents of torrefaction products. This work provides a theoretical guidance for future evaluation and optimization of woody biomass torrefaction systems/processes, and thereafter for the industrial application of woody biomass thermochemical conversion