One-Way Functions Using Algorithmic and Classical Information Theories

We prove several results relating injective one-way functions, time-bounded conditional Kolmogorov complexity, and time-bounded conditional entropy. First we establish a connection between injective, strong and weak one-way functions and the expected value of the polynomial time-bounded Kolmogorov complexity, denoted here by?E(K ^t (x|f(x))). These results are in both directions. More precisely, conditions on?E(K ^t (x|f(x))) that imply that?f is a weak one-way function, and properties of?E(K ^t (x|f(x))) that are implied by the fact that?f is a strong one-way function. In particular, we prove a separation result: based on the concept of time-bounded Kolmogorov complexity, we find an interval in which every function?f is a necessarily weak but not a strong one-way function. Then we propose an individual approach to injective one-way functions based on Kolmogorov complexity, defining Kolmogorov one-way functions and prove some relationships between the new proposal and the classical definition of one-way functions, showing that a Kolmogorov one-way function is also a deterministic one-way function. A relationship between Kolmogorov one-way functions and the conjecture of polynomial time symmetry of information is also proved. Finally, we relate?E(K ^t (x|f(x))) and two forms of time-bounded entropy, the unpredictable entropy?H ^unp, in which ??one-wayness?? of a function can be easily expressed, and the Yao⁺ entropy, a measure based on compression/decompression schema in which only the decompressor is restricted to be time-bounded.     

Workflows for Heliophysics

In this paper we describe how we have introduced workflows into the working practices of a community for whom the concept of workflows is very new, namely the heliophysics community. Heliophysics is a branch of astrophysics which studies the Sun and the interactions between the Sun and the planets, by tracking solar events as they travel throughout the Solar system. Heliophysics produces two major challenges for workflow technology. Firstly it is a systems science where research is currently developed by many different communities who need reliable data models and metadata to be able to work together. Thus it has major challenges in the semantics of workflows. Secondly, the problem of time is critical in heliophysics; the workflows must take account of the propagation of events outwards from the sun. They have to address the four dimensional nature of space and time in terms of the indexing of data. We discuss how we have built an environment for Heliophysics workflows building on and extending the Taverna workflow system and utilising the myExperiment site for sharing workflows. We also describe how we have integrated the workflows into the existing practices of the communities involved in Heliophysics by developing a web portal which can hide the technical details from the users, who can concentrate on the data from their scientific point of view rather than on the methods used to integrate and process the data. This work has been developed in the EU Framework 7 project HELIO, and is being disseminated to the worldwide Heliophysics community, since Heliophysics requires integration of effort on a global scale.     

Real-time inverse dynamics control of parallel manipulators using general-purpose multibody software

This work deals with the problem of computing the inverse dynamics of complex constrained mechanical systems for real-time control applications. The main goal is the control of robotic systems using model-based schemes in which the inverse model itself is obtained using a general purpose multibody software, exploiting the redundant coordinate formalism. The resulting control scheme is essentially equivalent to a classical computed torque control, commonly used in robotics applications. This work proposes to use modern general-purpose multibody software to compute the inverse dynamics of complex rigid mechanisms in an efficient way, so that it suits the requirements of realistic real-time applications as well. This task can be very difficult, since it involves a higher number of equations than the relative coordinates approach. The latter is believed to be less general, and may suffer from topology limitations. The use of specialized linear algebra solvers makes this kind of control algorithms usable in real-time for mechanism models of realistic complexity. Numerical results from the simulation of practical applications are presented, consisting in a “delta” robot and a bio-mimetic 11 degrees of freedom manipulator controlled using the same software and the same algorithm.     

Generation and interpretation of parsimonious predictive models for load forecasting in smart heating networks

Applied Intelligence - Forecasting future heat load in smart district heating networks is a key problem for utility companies that need such predictions for optimizing their operational activities....     

Delignification kinetics of empty fruit bunch (EFB): a sustainable and green pretreatment approach using malic acid-based solvents

Recently, the development of efficient and environmentally benign solvents has received great attention to replace current harsh organic solvents. In this context, low-transition-temperature mixtures (LTTMs) have emerged as favorable green solvents for biomass delignification. Palm oil biomass, empty fruit bunch (EFB) was pretreated with commercial l-malic acid and microwave hydrothermally extracted cactus malic acid-derived LTTMs at 60, 80, and 100 °C. The LTTMs applied in this study were derived from malic acid–choline chloride–water and malic acid–monosodium glutamate–water with a molar ratio of 2:4:2 and 3:1:5, respectively. Three first-order reactions were used to express the delignification kinetic model of EFB. The first term was based on the initial stage and assigned as infinite due to the fast rate of delignification which could not be detected. The second and third terms were proportional to bulk and residual delignification stages. A good agreement was obtained between the kinetic model and the experimental data obtained in this study with R²?≥?0.91. The activation energies for the delignification reactions using l-malic acid and cactus malic acid-based LTTMs in the bulk and residual stages were approximated as 36–56 and 19–26 kJ/mol and 34–90 and 47–87 kJ/mol, respectively.     

The renaming problem in shared memory systems: An introduction

Exploring the power of shared memory communication objects and models, and the limits of distributed computability are among the most exciting research areas of distributed computing. In that spirit, this paper focuses on a problem that has received considerable interest since its introduction in 1987, namely the renaming problem. It was the first non-trivial problem known to be solvable in an asynchronous distributed system despite process failures. Many algorithms for renaming and variants of renaming have been proposed, and sophisticated lower bounds have been proved, that have been a source of new ideas of general interest to distributed computing. It has consequently acquired a paradigm status in distributed fault-tolerant computing.In the renaming problem, processes start with unique initial names taken from a large name space, then deciding new names such that no two processes decide the same new name and the new names are from a name space that is as small as possible.This paper presents an introduction to the renaming problem in shared memory systems, for non-expert readers. It describes both algorithms and lower bounds. Also, it discusses strong connections relating renaming and other important distributed problems such as set agreement and symmetry breaking.     

Performance evaluation of efficient multi-objective evolutionary algorithms for design space exploration of embedded computer systems

Multi-objective evolutionary algorithms (MOEAs) have received increasing interest in industry because they have proved to be powerful optimizers. Despite the great success achieved, however, MOEAs have also encountered many challenges in real-world applications. One of the main difficulties in applying MOEAs is the large number of fitness evaluations (objective calculations) that are often needed before an acceptable solution can be found. There are, in fact, several industrial situations in which fitness evaluations are computationally expensive and the time available is very short. In these applications efficient strategies to approximate the fitness function have to be adopted, looking for a trade-off between optimization performance and efficiency. This is the case in designing a complex embedded system, where it is necessary to define an optimal architecture in relation to certain performance indexes while respecting strict time-to-market constraints. This activity, known as design space exploration (DSE), is still a great challenge for the EDA (electronic design automation) community. One of the most important bottlenecks in the overall design flow of an embedded system is due to simulation. Simulation occurs at every phase of the design flow and is used to evaluate a system which is a candidate for implementation. In this paper we focus on system level design, proposing an extensive comparison of the state-of-the-art of MOEA approaches with an approach based on fuzzy approximation to speed up the evaluation of a candidate system configuration. The comparison is performed in a real case study: optimization of the performance and power dissipation of embedded architectures based on a Very Long Instruction Word (VLIW) microprocessor in a mobile multimedia application domain. The results of the comparison demonstrate that the fuzzy approach outperforms in terms of both performance and efficiency the state of the art in MOEA strategies applied to DSE of a parameterized embedded system.