The KlaperSuite framework for model-driven reliability analysis of component-based systems

Automatic prediction tools play a key role in enabling the application of non-functional requirements analysis, to simplify the selection and the assembly of components for component-based software systems, and in reducing the need for strong mathematical skills for software designers. By exploiting the paradigm of Model-Driven Engineering (MDE), it is possible to automatically transform design models into analytical models, thus enabling formal property verification. MDE is the core paradigm of the KlaperSuite framework presented in this paper, which exploits the KLAPER pivot language to fill the gap between design and analysis of component-based systems for reliability properties. KlaperSuite is a family of tools empowering designers with the ability to capture and analyze quality of service views of their systems, by building a one-click bridge towards a number of established verification instruments. In this article, we concentrate on the reliability-prediction capabilities of KlaperSuite and we evaluate them with respect to several case studies from literature and industry.     

Effective molarities in supramolecular catalysis of two-substrate reactions

Reactivity data related to processes in which molecular receptors promote the reaction of two simultaneously complexed reactants have been surveyed and analyzed in terms of effective molarity (EM). Methods and criteria for the calculation of reliable EM's have been highlighted. Extension of a previous extrathermodynamic treatment of intramolecular reactions of bifunctional chains to the intracomplex reactions of the ternary complexes involved in two-substrate catalyzed reactions has provided a sound framework for a comparative analysis of reactivity and catalytic efficiency in structurally diverse and apparently unrelated systems.     

Ranking Approach for the User Story Prioritization Methods

The AHP （analytic hierarchy process） has been applied in many fields and especially to complex engineering problems and applications. AHP is capable of structuring decision problems and finding mathematically determined judgments built on knowledge and experience. This suggests that AHP should prove useful in agile software development, where complex decisions occur routinely. This paper describes a ranking approach to help stakeholders select the best prioritization method for prioritizing the user stories.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Outlier detection using default reasoning

Default logics are usually used to describe the regular behavior and normal properties of domain elements. In this paper we suggest, conversely, that the framework of default logics can be exploited for detecting outliers. Outliers are observations expressed by sets of literals that feature unexpected semantical characteristics. These sets of literals are selected among those explicitly embodied in the given knowledge base. Hence, essentially we perceive outlier detection as a knowledge discovery technique. This paper defines the notion of outlier in two related formalisms for specifying defaults: Reiter's default logic and extended disjunctive logic programs. For each of the two formalisms, we show that finding outliers is quite complex. Indeed, we prove that several versions of the outlier detection problem lie over the second level of the polynomial hierarchy. We believe that a thorough complexity analysis, as done here, is a useful preliminary step towards developing effective heuristics and exploring tractable subsets of outlier detection problems.     

Scheduling algorithms for fault-tolerance in hard-real-time systems

Many time-critical applications require predictable performance in the presence of failures. This paper considers a distributed system with independent periodic tasks which can checkpoint their state on some reliable medium in order to handle failures. The problem of preemptively scheduling a set of such tasks is discussed where every occurrence of a task has to be completely executed before the next occurrence of the same task can start. Efficient scheduling algorithms are proposed which yield sub-optimal schedules when there is provision for fault-tolerance. The performance of the solutions proposed is evaluated in terms of the number of processors and the cost of the checkpoints needed. Moreover, analytical studies are used to reveal interesting trade-offs associated with the scheduling algorithms.This work has been supported by grants from the Italian Ministero dell'Università e della Ricerca Scientifica e Tecnologica and the Consiglio Nazionale delle Ricerche-Progetto Finalizzato Sistemi Informatici e Calcolo Parallelo.     

Magnetic Properties of Thermal Sprayed Tungsten Carbide–Cobalt Coatings

In the information age, the storage and accessibility of data is of vital importance. There are several possibilities to fulfill this task. Magnetic storage of data is a well‐established method and the range of materials used is continuously extended. In this study, the magnetic remanence of thermally sprayed tungsten carbide–cobalt (WCCo)‐coatings in dependence of their thickness is examined. Two magnetic fields differing in value and geometry are imprinted into the coatings and the resulting remanence field is measured. It is found that there are two effects, which in combination determine the effective value of the magnetic remanence usable for magnetic data storage.

     

Optimization–Simulation Model for Planning Supply Transport to Large Infrastructure Public Works Located in Congested Urban Areas

This article proposes an optimization–simulation model for planning the transport of supplies to large public infrastructure works located in congested urban areas. The purpose is to minimize their impact on the environment and on private transportation users on the local road network. To achieve this goal, the authors propose and solve an optimization problem for minimizing the total system cost made up of operating costs for various alternatives for taking supplies to the worksite and the costs supported by private vehicle users as a result of increased congestion due to the movement of heavy goods vehicles transporting material to the worksite. The proposed optimization problem is a bi-level Math Program model. The upper level defines the total cost of the system, which is minimized taking into account environmental constraints on atmospheric and noise pollution. The lower level defines the optimization problem representing the private transportation user behavior, assuming they choose the route that minimizes their total individual journey costs. Given the special characteristics of the problem, a heuristic algorithm is proposed for finding optimum solutions. Both the model developed and the specific solution algorithm are applied to the real case of building a new port at Laredo (Northern Spain). A series of interesting conclusions are obtained from the corresponding sensitivity analysis.