Journal Articles

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Factors affecting Chinese short-term international students’ cross-cultural adaptation in psychology, learning, and life
(Hindawi, 20/08/2022) Zhang H; Li M
Although Chinese international students’ cross-cultural adaptation has achieved intense research, factors in developing Chinese SISs’ cross-cultural adaptation remain under-researched. This study examined the factors through a survey of Chinese SISs’ transitional adaptation in psychology, life, and learning. Mixed-method research was conducted: a survey of 155 SISs from a top Chinese university undertaking study across 16 countries and in-depth interviews with 15 SISs. Results indicate that knowledge of the host country and university, language proficiency, sense of participation, and engagement are the crucial factors in developing Chinese SISs’ cross-cultural adaptation. These factors reveal significant correlations with the students’ adaptive performances in psychology, life, and learning. However, the factor of duration indicates no significant correlation with students’ cross-cultural adaptation, which demonstrates an inconsistency with the previous studies. The findings of this study highlight the need for developing Chinese SISs’ sense of engagement, enhancing the language training, and building up the knowledge of the host cultures previous to the study abroad.
Modular neural network modelling for long-range prediction of an evaporator
(2000) Russell NT; Bakker HH; Chaplin RI
This paper presents the development of a modular neural network model of a three-effect, falling-film evaporator. The model comprises a number of sub-networks each modelling a specific element of the overall system. The modular structure was employed in order to provide benefits in terms of improved model training and performance. The performance of the modular neural model is demonstrated for long-range prediction by comparing it with process data, an analytical simulation and a linear ARX model. The results show that the modular neural model can satisfactorily predict over a horizon of arbitrary length and is suited for implementation within a predictive control scheme. Benefits in terms of model flexibility and interpretability are also discussed. (C) 2000 Elsevier Science Ltd. All rights reserved.
Numerical bifurcation theory for high-dimensional neural models
(BioMed Central, 25/07/2014) Laing CR
Numerical bifurcation theory involves finding and then following certain types of solutions of differential equations as parameters are varied, and determining whether they undergo any bifurcations (qualitative changes in behaviour). The primary technique for doing this is numerical continuation, where the solution of interest satisfies a parametrised set of algebraic equations, and branches of solutions are followed as the parameter is varied. An effective way to do this is with pseudo-arclength continuation. We give an introduction to pseudo-arclength continuation and then demonstrate its use in investigating the behaviour of a number of models from the field of computational neuroscience. The models we consider are high dimensional, as they result from the discretisation of neural field models—nonlocal differential equations used to model macroscopic pattern formation in the cortex. We consider both stationary and moving patterns in one spatial dimension, and then translating patterns in two spatial dimensions. A variety of results from the literature are discussed, and a number of extensions of the technique are given.
Population growth as a nonlinear process
(1/12/2003) Soboleva TK; Pleasants T
The evolution of the probability density of a biological population is described using nonlinear stochastic differential equations for the growth process and the related Fokker-Planck equations for the time-dependent probability densities. It is shown that the effect of the initial conditions disappears rapidly from the evolution of the mean of the process. But the behaviour of the variance depends on the initial condition. It may monotonically increase, reaching its maximum in the steady state, or have a rather complicated evolution reaching the maximum near the point where growth rates (not population size) is maximal. The variance then decreases to its steady-state value. This observation has implications for risk assessments associated with growing populations, such as microbial populations, which cause food poisoning if the population size reaches a critical level.
Shortability and Asset Pricing Model: Evidence from The Hong Kong Stock Market
(Elsevier BV, 2017-12) Bai M; Li X-M; Qin Y; Alexander, C
This study explores how the violation of free short selling assumption affects the performance of CAPM and the Fama-French three-factor model, as existing studies show that short-sales constraints affect asset pricing of the stocks. Using data from the Hong Kong Stock Market which has unique regulations on short selling, we conduct both time-series and cross-sectional regression analyses to evaluate the performance of the two models under the short-sales-constraints and the no-constraints market environment. The two models perform much worse in the former environment than in the latter, indicating a significant impact of the short sales constraints on the explanatory power of the models. We then augment the two models with a shortability-mimicking factor. Our results show that the factor has a significant power in explaining both time-series and cross-sectional variation in the size-B/M portfolio returns. The addition of the factor to the two models considerably increases their overall performance.
Solving fuzzy multi-objective linear programming problems using deviation degree measures and weighted max-min method
(Elsevier, 1/06/2013) Cheng HF; Huang WL; Zhou Q; Cai JH
This paper proposes a method for solving fuzzy multi-objective linear programming (FMOLP) problems where all the coefficients are triangular fuzzy numbers and all the constraints are fuzzy equality or inequality. Using the deviation degree measures and weighted max–min method, the FMOLP problem is transformed into crisp linear programming (CLP) problem. If decision makers fix the values of deviation degrees of two side fuzzy numbers in each constraint, then the δ-pareto-optimal solution of the FMOLP problems can be obtained by solving the CLP problem. The bigger the values of the deviation degrees are, the better the objectives function values will be. So we also propose an algorithm to find a balance-pareto-optimal solution between two goals in conflict: to improve the objectives function values and to decrease the values of the deviation degrees. Finally, to illustrate our method, we solve a numerical example.
The evolution of a truncated Gaussian probability density through time: Modelling animal liveweights after selection
(Elsevier, 2003) Wake GC; Soboleva TK; Pleasants AB
The form of the probability density derived from the evolution in time of a previously truncated frequency distribution of animal Liveweights is of interest in animal husbandry. Truncated frequency distributions arise when the heavier animals are sold for slaughter and the lighter animals retained. The demands of modern quality assurance schemes require that, given information on animal growth, the farmer is able to estimate the number of animals that would meet the specifications at some time in the future after truncation. Assuming that animal growth can be described by a linear stochastic differential equation, we derive an explicit expression for the probability density of animal Liveweights at any time after the truncation of an initial Gaussian density. It is shown that this probability density converges rapidly to a Gaussian density, so that after about 20 days of typical growth rates for lambs, the resulting density is practically indistinguishable from Gaussian.
Using data-driven and process mining techniques for identifying and characterizing problem gamblers in New Zealand
(RTU Press, 2016-12) Suriadi S; Susnjak T; Ponder-Sutton A; Watters P; Schumacher CR
When It Rains It Drains: Psychological Distress and Household Net Worth
(Elsevier, 21/07/2022) Balloch A; Engels C; Philip D

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