Modelling methodology and forecast failure

We analyse by simulation the impact of model-selection strategies (sometimes called pre-testing) on forecast performance in both constant-and non-constant-parameter processes. Restricted, unrestricted and selected models are compared when either of the first two might generate the data. We find little evidence that strategies such as general-to-specific induce significant over-fitting, or thereby cause forecast-failure rejection rates to greatly exceed nominal sizes. Parameter non-constancies put a premium on correct specification, but in general, model-selection effects appear to be relatively small, and progressive research is able to detect the mis-specifications.

Contributions of maternal and infant factors to infant responding to the Still Face paradigm: a longitudinal study

Early mother–infant interactions are characterised by periods of synchronous interaction that are interrupted by periods of mismatch; the experience of such mismatches and their subsequent repair is held to facilitate the development of infant self-regulatory capacities (Tronick, Als, Adamson, Wise, & Brazelton, 1978). Infant responding to such interactive challenge is assumed to be a function of both maternal behaviour and pre-existing infant characteristics. However, the latter has received relatively little attention. In a prospective longitudinal study of a sample comprising high and low adversity dyads (n = 122), we examined the contributions of both maternal sensitivity and neonatal irritability to infant behavioural and physiological responding to the interactive challenge of the Still Face paradigm. Results indicated that higher levels of maternal sensitivity were associated with more regulated infant behaviour during the Still Face paradigm. Neonatal irritability also predicted poorer behavioural and heart rate recovery following the Still Face challenge. Furthermore, there was an interaction such that irritable infants with insensitive mothers showed the worst behavioural outcomes. The findings highlight the importance of the interplay between maternal and infant characteristics in determining dyadic responding.

Effects and mechanisms of ginseng and ginsenosides on cognition

Reviewed here is the existing evidence for the effects of ginseng extracts and isolated ginsenosides relevant to cognition in humans. Clinical studies in healthy volunteers and in patients with neurological disease or deficit, evidence from preclinical models of cognition, and pharmacokinetic data are considered. Conditions under which disease modification may indirectly benefit cognition but may not translate to cognitive benefits in healthy subjects are discussed. The number of chronic studies of ginseng effects in healthy individuals is limited, and the results from acute studies are inconsistent, making overall assessment of ginseng's efficacy as a cognitive enhancer premature. However, mechanistic results are encouraging; in particular, the ginsenosides Rg 3 , Rh 1 , Rh 2 , Rb 1 , Rd, Rg 2 , and Rb 3 , along with the aglycones protopanaxadiol and protopanaxatriol, warrant further attention. Compound K has a promising pharmacokinetic profile and can affect neurotransmission and neuroprotection. Properly conducted trials using standardized tests in healthy individuals reflecting the target population for ginseng supplementation are required to address inconsistencies in results from acute studies. The evidence summarized here suggests ginseng has potential, but unproven, benefits on cognition.

Efficient interactive budget planning and adjusting under financial stress

One of the most challenging tasks in financial management for large governmental and industrial organizations is Planning and Budgeting (P&B). The processes involved with P&B are cost and time intensive, especially when dealing with uncertainties and budget adjustments during the planning horizon. This work builds on our previous research in which we proposed and evaluated a fuzzy approach that allows optimizing the budget interactively beyond the initial planning stage. In this research we propose an extension that handles financial stress (i.e. drastic budget cuts) occurred during the budget period. This is done by introducing fuzzy stress parameters which are used to re-distribute the budget in order to minimize the negative impact of the financial stress. The benefits and possible issues of this approach are analyzed critically using a real world case study from the Nuremberg Institute of Technology (NIT). Additionally, ongoing and future research directions are presented.

Rule Type Identification using TRCM for trend analysis in Twitter

This paper considers the use of Association Rule Mining (ARM) and our proposed Transaction based Rule Change Mining (TRCM) to identify the rule types present in tweet’s hashtags over a specific consecutive period of time and their linkage to real life occurrences. Our novel algorithm was termed TRCM-RTI in reference to Rule Type Identification. We created Time Frame Windows (TFWs) to detect evolvement statuses and calculate the lifespan of hashtags in online tweets. We link RTI to real life events by monitoring and recording rule evolvement patterns in TFWs on the Twitter network.

Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

What is the right balance for performance and isolation with virtualization in HPC?

The use of virtualization in high-performance computing (HPC) has been suggested as a means to provide tailored services and added functionality that many users expect from full-featured Linux cluster environments. The use of virtual machines in HPC can offer several benefits, but maintaining performance is a crucial factor. In some instances the performance criteria are placed above the isolation properties. This selective relaxation of isolation for performance is an important characteristic when considering resilience for HPC environments that employ virtualization. In this paper we consider some of the factors associated with balancing performance and isolation in configurations that employ virtual machines. In this context, we propose a classification of errors based on the concept of “error zones”, as well as a detailed analysis of the trade-offs between resilience and performance based on the level of isolation provided by virtualization solutions. Finally, a set of experiments are performed using different virtualization solutions to elucidate the discussion.

Expansion quality of epidemic protocols

Epidemic protocols are a bio-inspired communication and computation paradigm for large and extreme-scale networked systems. This work investigates the expansion property of the network overlay topologies induced by epidemic protocols. An expansion quality index for overlay topologies is proposed and adopted for the design of epidemic membership protocols. A novel protocol is proposed, which explicitly aims at improving the expansion quality of the overlay topologies. The proposed protocol is tested with a global aggregation task and compared to other membership protocols. The analysis by means of simulations indicates that the expansion quality directly relates to the speed of dissemination and convergence of epidemic protocols and can be effectively used to design better protocols.

Another look at family adjustment

This chapter argues that in the international career context there is a need to conceptualise the adjustment of the family unit holistically. We discuss what that means and how it can be done. We note that to date the family has almost always been conceptualised as a hindrance to or a support for the working expatriate. However, in international assignments the family as a whole is expatriated and the family may become part of the expatriate resources with the line between work and family/personal life blurring. We draw on the Family Adjustment and Adaptation Response (FAAR) literature to argue that previous conceptions of adjustment have failed to capture the complexity of the process from the family perspective and we use that literature to develop our understanding of the process of adjustment of the family unit and suggest ways forward.

Examining the interfaces to e-journal articles: what do users expect?

Researchers are increasingly relying on e-journals to access literature within their fields. The design of the interfaces to these journals is determined by the individual host or publisher and there appears to be little standardization. This exploratory study samples a set of sixteen home screens of e-journals from different disciplines and identifies common features across the set. The particular wording used to identify the features and their locations are recorded. An online survey of e-journal readers investigates where users would normally expect to locate features when first accessing a journal article. Comparison of observed and expected locations confirms inconsistencies across interfaces in terminology and locations. Mental models of the interface design do not appear to be well developed. A move toward standardization, based on some existing conventions, is desirable.