Local Analysis for Global Inputs

Fuzz testing and symbolic test generation both face their own challenges. While symbolic testing has scalability issues, fuzzing cannot uncover faults which require carefully engineered inputs. In this paper I propose a combination of both approaches, compensating weaknesses of each approach with the strength of the other approach. I present my plans for evaluation, which include applications of the hybrid tool to programs which neither of the approaches can handle on its own

Complex Network Analysis of State Spaces for Random Boolean Networks

We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains $N$ Boolean elements each with $K$ inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of an SSN at both local and global scales, as well as sample-to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity [Phys. Rev. Lett. 98, 198701 (2007)] of an SSN as a global topological measure. RBNs with $2 \leq K \leq 5$ exhibit non-trivial fluctuations at both local and global scales, while K=2 exhibits the largest sample-to-sample, possibly non-self-averaging, fluctuations. We interpret the observed ``multi scale'' fluctuations in the SSNs as indicative of the criticality and complexity of K=2 RBNs. ``Garden of Eden'' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for $K>1$ SSNs can assume any integer value between 0 and $2^N$, for K=1 all the non-GoE nodes in an SSN have the same in-degree which is always a power of two

Investigations of Building-Related LCC Sensitivity of a Cost-Effective Renovation Package by One-at-a-Time and Monte Carlo Parameter Variation Methods

Nearly Zero Energy Building (NZEB) is becoming a standard for new and renovated buildings throughout the European Union (EU). Through the ongoing implementation of directives related to energy efficiency and NZEB-compliant buildings, the EU commission has established that new and renovated NZEB-compliant buildings shall be implemented cost-effectively. This is assessed by linking the Life Cycle Cost (LCC) and energy demand calculations, representing them in a cost-optimality plot, and finding the optimal solution from the resulting Pareto front. Given that the results of an LCC calculation are quite dependent on the calculation model’s scope and inputs, this study takes an explorative approach to determine the most influential parameters in LCC calculations for a pre-selected cost-effective package. This is achieved by varying the inputs using local and global variation methods. The local variation approach consists of varying the inputs one-at-a-time (OAT), whereas with global variation, all the selected inputs are variated simultaneously. The OAT approach identified the amount and unit cost of the utility supply (district heating, electricity, and gas) as the most influential parameters to the output. The OAT results were further used to rank the next five most sensitive parameters and perform a global sensitivity analysis using Monte Carlo (MC) simulations. A regression analysis of the MC results revealed high R2 values (≥0.98), suggesting a linear correlation between the output and the variable inputs. The sensitivity analysis determined the unit price of attic insulation, the gas price, and the lifetime of the Heat Pump (HP) as the most sensitive parameters in the three investigated models

Synchronization induced by periodic inputs in finite NN-unit bistable Langevin models: The augmented moment method

We have studied the synchronization induced by periodic inputs applied to the finite $N$-unit coupled bistable Langevin model which is subjected to cross-correlated additive and multiplicative noises. Effects on the synchronization of the system size ($N$), the coupling strength and the cross-correlation between additive and multiplicative noises have been investigated with the use of the semi-analytical augmented moment method (AMM) which is the second-order moment approximation for local and global variables [H. Hasegawa, Phys. Rev. E {\bf 67} (2003) 041903]. A linear analysis of the stationary solution of AMM equations shows that the stability is improved (degraded) by positive (negative) couplings. Results of the nonlinear bistable Langevin model are compared to those of the linear Langevin model.Comment: 19 pages, 10 figures, the final version with a changed title, accepted in Physica

Identification of System Behaviours by Approximation of Time Series Data

The behavioural framework has several attractions to offer for the identification of multivariable systems. Some of the variables may be left unexplained without the need for a distinction between inputs and outputs; criteria for model quality are independent of the chosen parametrization; and behaviours allow for a global (i.e., non-local) approximation of the system dynamics. This is illustrated with a behavioural least squares method with an application in dynamic factor analysis

Local Termination: theory and practice

The characterisation of termination using well-founded monotone algebras has been a milestone on the way to automated termination techniques, of which we have seen an extensive development over the past years. Both the semantic characterisation and most known termination methods are concerned with global termination, uniformly of all the terms of a term rewriting system (TRS). In this paper we consider local termination, of specific sets of terms within a given TRS. The principal goal of this paper is generalising the semantic characterisation of global termination to local termination. This is made possible by admitting the well-founded monotone algebras to be partial. We also extend our approach to local relative termination. The interest in local termination naturally arises in program verification, where one is probably interested only in sensible inputs, or just wants to characterise the set of inputs for which a program terminates. Local termination will be also be of interest when dealing with a specific class of terms within a TRS that is known to be non-terminating, such as combinatory logic (CL) or a TRS encoding recursive program schemes or Turing machines. We show how some of the well-known techniques for proving global termination, such as stepwise removal of rewrite rules and semantic labelling, can be adapted to the local case. We also describe transformations reducing local to global termination problems. The resulting techniques for proving local termination have in some cases already been automated. One of our applications concerns the characterisation of the terminating S-terms in CL as regular language. Previously this language had already been found via a tedious analysis of the reduction behaviour of S-terms. These findings have now been vindicated by a fully automated and verified proof

Robust Rescaling Methods for Integrated Water, Food, and Energy Security Management under Systemic Risks and Uncertainty

The aim of this presentation is to discuss robust, non-Bayesian, probabilistic, cross-entropy-based disaggregation (downscaling) techniques. Systems analysis of global change (including climate) processes requires new approaches to integrating and rescaling of models, data, and decision-making procedures between various scales. For example, in the analysis of water security issues, the hydrological models require inputs that are much finer than the resolution of, say, the economic or climatic models generating those inputs. In relation to food security, aggregate national or regional land-use projections derived with global economic land-use planning models give no insights into potentially critical heterogeneities of local trends. Many practical studies analyzing regional developments use cross-entropy minimization as an underlying principle for estimation of local processes. However, the traditional cross-entropy approach relies on a single prior distribution. In reality, we can identify a set of feasible priors. This is relevant, in particular, for land-cover data. Existing global land cover maps (GLC2000, MODIS2000, GLOBCOVER2000) differ in terms of spatially resolved estimates of land use, (e.g., crop, forest, and grass lands). We present novel general approach to achieving downscaling results that are robust with respect to a set of potential prior distributions reflecting non-Bayesian uncertainties, that is, data that are incomplete or not directly observable. The robust downscaling problem is formulated as a probabilistic inverse problem (from aggregate to local data) generally in the form of a non-convex, cross-entropy minimization model. The approach will be illustrated by sequential downscaling aggregate model projections of land-use changes using the Global Biosphere Management Model, with case studies from Africa, Brazil, China, and Ukraine. The approach is being used to harmonize alternative land-cover maps and to develop hybrid maps

Multinational firms, global value chains and the organization of technology transfer

This paper combines insights from different streams of literature to develop a more comprehensive framework for the analysis of technology transfer via value chain relationships. We integrate the existing literature in three ways. First, we consider value chain relationships as a multi-facet process of interaction between buyers and suppliers, involving different degrees of knowledge transmission and development. Second, we assess whether and to what extent value chain relationships are associated with the presence of multinationals and with their embeddedness in the host economy. Third, we take into account the capabilities of local firms to handle the technology as a factor influencing knowledge transfer through value chain relationships. Using data on 1385 firms active in Thailand in 2001-2003, we apply a multinomial logit model to test how the nature and intensity of multinational presence and the competencies of local firms affect the organisation of international technology transfer. We find that knowledge intensive relationships, which are characterized by a significant transmission of technology along the value chains, are positively associated with the presence of global buyers in the local market, with the efforts of MNCs to adapt technology to local contexts, and with the technical capabilities of domestic firms. By contrast, the age of subsidiaries and the share of inputs purchased locally appear to increase the likelihood of value chain relationships with a lower technological profile. Key words: Global value chain, multinationals, technology transfer, knowledge spilloversGlobal value chain, multinationals, technology transfer, knowledge spillovers