Using Performance Forecasting to Accelerate Elasticity

Cloud computing facilitates dynamic resource provisioning. The automation of resource management, known as elasticity, has been subject to much research. In this context, monitoring of a running service plays a crucial role, and adjustments are made when certain thresholds are crossed. On such occasions, it is common practice to simply add or remove resources. In this paper we investigate how we can predict the performance of a service to dynamically adjust allocated resources based on predictions. In other words, instead of “repairing” because a threshold has been crossed, we attempt to stay ahead and allocate an optimized amount of resources in advance. To do so, we need to have accurate predictive models that are based on workloads. We present our approach, based on the Universal Scalability Law, and discuss initial experiments

Enterprise IoT Security and Scalability : How Unikernels can Improve the Status Quo

Postprin

Agriculture in the Face of Changing Markets, Institutions and Policies: Challenges and Strategies

Since the late 1980s, agriculture in Central and Eastern European Countries (CEECs) has been under considerable adjustment pressure due to changing political, economic and institutional environments. These changes have been linked to the transition process, as well as the ongoing integration into the European Union and the world market. Reduced subsidies, increased environmental and food quality demands, as well as structural changes in the supply, processing and food retailing sector call for major structural adjustments and the improvement of farmersâ managerial abilities. Though such changes always carry significant threats to farms, they also offer new opportunities for the farms' entrepreneurial engagement. Upcoming changes in the agricultural environment and their possible consequences for farm structures across Europe are thus still timely subjects. The objective of the IAMO Forum 2006 is to contribute to the success of agriculture in the CEECs, as well as their neighboring countries, in todayâs increasingly competitive environment. Concrete questions the conference focuses on are: What are the most suitable farm organizations, cooperative arrangements and contractual forms? How to improve efficiency and productivity? Where do market niches lie and what are the new product demands? This book contains 33 invited and selected contributions. These papers will be presented at the IAMO Forum 2006 in order to offer a platform for scientists, practitioners and policy-makers to discuss challenges and potential strategies at the farm, value chain, rural society and policy levels in order to cope with the upcoming challenges. IAMO Forum 2006, as well as this book, would not have been possible without the engagement of many people and institutions. We thank the authors of the submitted abstracts and papers, as well as the referees, for their evaluation of the abstracts from which the papers were selected. In particular, we would like to express our thanks to OLIVER JUNGKLAUS, GABRIELE MEWES, KLAUS REINSBERG and ANGELA SCHOLZ, who significantly contributed to the organization of the Forum. Furthermore, our thanks goes to SILKE SCHARF for her work on the layout and editing support of this book, and to JIM CURTISS, JAMIE BULLOCH, and DÃNALL Ã MEARÃIN for their English proof-reading. As experience from previous years documents, the course of the IAMO Forum continues to profit from the support and engagement of the IAMO administration, which we gratefully acknowledge. Last but not least, we are very grateful to the Robert Bosch Foundation, the Federal Ministry of Nutrition, Agriculture and Consumer Protection (BMELV), the German Research Foundation (DFG), the Haniel Foundation and the Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO) for their respective financial support.Agribusiness, Community/Rural/Urban Development, Farm Management, Industrial Organization, International Development, Labor and Human Capital, Land Economics/Use, Productivity Analysis,

Simple mindreading abilities predict complex theory of mind: developmental delay in autism spectrum disorders

Theory of Mind (ToM) is impaired in individuals with Autism Spectrum Disorders (ASD). The aims of this study were to: i) examine the developmental trajectories of ToM abilities in two different mentalizing tasks in children with ASD compared to TD children; and ii) to assess if a ToM simple test known as Eyes-test could predict performance on the more advanced ToM task, i.e. Comic Strip test. Based on a sample of 37 children with ASD and 55 TD children, our results revealed slower development at varying rates in all ToM measures in children with ASD, with delayed onset compared to TD children. These results could stimulate new treatments for social abilities, which would lessen the social deficit in ASD

Spatial interactions in agent-based modeling

Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution of economic activities, - out of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with spatial structure, is used to illustrate the potential of such an approach for spatial policy analysis.Comment: 26 pages, 5 figures, 105 references; a chapter prepared for the book "Complexity and Geographical Economics - Topics and Tools", P. Commendatore, S.S. Kayam and I. Kubin, Eds. (Springer, in press, 2014

Data-efficient performance learning for configurable systems

Many software systems today are configurable, offering customization of functionality by feature selection. Understanding how performance varies in terms of feature selection is key for selecting appropriate configurations that meet a set of given requirements. Due to a huge configuration space and the possibly high cost of performance measurement, it is usually not feasible to explore the entire configuration space of a configurable system exhaustively. It is thus a major challenge to accurately predict performance based on a small sample of measured system variants. To address this challenge, we propose a data-efficient learning approach, called DECART, that combines several techniques of machine learning and statistics for performance prediction of configurable systems. DECART builds, validates, and determines a prediction model based on an available sample of measured system variants. Empirical results on 10 real-world configurable systems demonstrate the effectiveness and practicality of DECART. In particular, DECART achieves a prediction accuracy of 90% or higher based on a small sample, whose size is linear in the number of features. In addition, we propose a sample quality metric and introduce a quantitative analysis of the quality of a sample for performance prediction

Defining language impairments in a subgroup of children with autism spectrum disorder

Autism spectrum disorder (ASD) is diagnosed on the basis of core impairments in pragmatic language skills, which are found across all ages and subtypes. In contrast, there is significant heterogeneity in language phenotypes, ranging from nonverbal to superior linguistic abilities, as defined on standardized tests of vocabulary and grammatical knowledge. The majority of children are verbal but impaired in language, relative to age-matched peers. One hypothesis is that this subgroup has ASD and co-morbid specific language impairment (SLI). An experiment was conducted comparing children with ASD to children with SLI and typically developing controls on aspects of language processing that have been shown to be impaired in children with SLI: repetition of nonsense words. Patterns of performance among the children with ASD and language impairment were similar to those with SLI, and contrasted with the children with ASD and no language impairment and typical controls, providing further evidence for the hypothesis that a subgroup of children with ASD has co-morbid SLI. The findings are discussed in the context of brain imaging studies that have explored the neural bases of language impairment in ASD and SLI, and overlap in the genes associated with elevated risk for these disorders.M01 RR00533 - NCRR NIH HHS; R01 DC10290 - NIDCD NIH HHS; U19 DC03610 - NIDCD NIH HH

Similar exemplar pooling processes underlie the learning of facial identity and handwriting style: Evidence from typical observers and individuals with Autism

Considerable research has addressed whether the cognitive and neural representations recruited by faces are similar to those engaged by other types of visual stimuli. For example, research has examined the extent to which objects of expertise recruit holistic representation and engage the fusiform face area. Little is known, however, about the domain-specificity of the exemplar pooling processes thought to underlie the acquisition of familiarity with particular facial identities. In the present study we sought to compare observers’ ability to learn facial identities and handwriting styles from exposure to multiple exemplars. Crucially, while handwritten words and faces differ considerably in their topographic form, both learning tasks share a common exemplar pooling component. In our first experiment, we find that typical observers’ ability to learn facial identities and handwriting styles from exposure to multiple exemplars correlates closely. In our second experiment, we show that observers with autism spectrum disorder (ASD) are impaired at both learning tasks. Our findings suggest that similar exemplar pooling processes are recruited when learning facial identities and handwriting styles. Models of exemplar pooling originally developed to explain face learning, may therefore offer valuable insights into exemplar pooling across a range of domains, extending beyond faces. Aberrant exemplar pooling, possibly resulting from structural differences in the inferior longitudinal fasciculus, may underlie difficulties recognising familiar faces often experienced by individuals with ASD, and leave observers overly reliant on local details present in particular exemplars

Subgrouping the autism "spectrum": reflections on DSM-5

DSM-5 has moved autism from the level of subgroups ("apples and oranges") to the prototypical level ("fruit"). But making progress in research, and ultimately improving clinical practice, will require identifying subgroups within the autism spectrum