Analysing anaphoric ambiguity in natural language requirements

Many requirements documents are written in natural language (NL). However, with the flexibility of NL comes the risk of introducing unwanted ambiguities in the requirements and misunderstandings between stakeholders. In this paper, we describe an automated approach to identify potentially nocuous ambiguity, which occurs when text is interpreted differently by different readers. We concentrate on anaphoric ambiguity, which occurs when readers may disagree on how pronouns should be interpreted. We describe a number of heuristics, each of which captures information that may lead a reader to favor a particular interpretation of the text. We use these heuristics to build a classifier, which in turn predicts the degree to which particular interpretations are preferred. We collected multiple human judgements on the interpretation of requirements exhibiting anaphoric ambiguity and showed how the distribution of these judgements can be used to assess whether a particular instance of ambiguity is nocuous. Given a requirements document written in natural language, our approach can identify sentences that contain anaphoric ambiguity, and use the classifier to alert the requirements writer of text that runs the risk of misinterpretation. We report on a series of experiments that we conducted to evaluate the performance of the automated system we developed to support our approach. The results show that the system achieves high recall with a consistent improvement on baseline precision subject to some ambiguity tolerance levels, allowing us to explore and highlight realistic and potentially problematic ambiguities in actual requirements documents.     

Enhancement of Peroxidase Activity in Artificial Mimochrome VI Catalysts through Rational Design

Rational design provides an attractive strategy to tune and control the reactivity of bioinspired catalysts. Although there has been considerable progress in the design of heme oxidase mimetics with active‐site environments of ever‐growing complexity and catalytic efficiency, their stability during turnover is still an open challenge. Herein, we show that the simple incorporation of two 2‐aminoisobutyric acids into an artificial peptide‐based peroxidase results in a new catalyst (Fe^III‐MC6*a) with higher resistance against oxidative damage and higher catalytic efficiency. The turnover number of this catalyst is twice as high as that of its predecessor. These results point out the protective role exerted by the peptide matrix and pave the way to the synthesis of robust bioinspired catalysts.     

Experimental Investigation on Magnetic Field Effects of IPT for Electric Bikes

The wireless power transmission (WPT) is increasingly representing a promising technology and an innovative solution, especially for the electric vehicles (EVs) battery charging. The inductive power transfer (IPT) is the standard technology of wireless charging: the energy transfer occurs between two magnetically coupled coils. The IPT-based battery charging is especially convenient for E-bikes and the physiological effects related to the generated magnetic fields should be estimated. In this context, this work presents a 200 W prototype of wireless battery charger for E-bikes. In addition, the measurements regarding the surrounding magnetic field are given in detail in order to evaluate the actual physiological compatibility of the system.     

Event based choreography

An important feature of the service-oriented approach is the ability to aggregate, through programmable coordination patterns, the activities involved in service interactions. Two different approaches can be adopted to tackle service coordination: orchestration and choreography. In this paper, we introduce a formal methodology to handle coordination among services from the perspective of a global observer, in the spirit of choreography models. In particular, we address the problem of verifying compliance and consistency between the design of service interactions and the choreography constraints.     

A comparison of simplex and simulated annealing for optimization of a new rear underrun protective device

In this paper, two optimization approaches to improve the product design process have been analysed. Through the analysis of a case study, concerning the designing of a new High Energy Absorption Rear Underrun Protective Device (HEARUPD), two different optimization approaches (simplex and simulated annealing) have been compared. In the implemented optimization processes, the crash between an economy car and the rear part of a truck has been simulated by dynamic numerical (FEM) analyses. Moreover, authors have proposed the use of a suitable linear function of four variables with the purpose of reducing the multi-objective optimization processes to mono-objective ones. That has been made to simplify the analysis procedures without affecting the quality and the completeness of the optimization processes. The obtained results, as well as showing the high effectiveness of the integrated use of numerical crash analyses and optimization methods, demonstrate that simplex method is more effective than simulated annealing one for optimization problems where the single analysis loop requires much time. Even if the solutions are quite similar in terms of calculated values of the objective function, design and state variables, simplex method needs shorter computational time than simulated annealing to obtain an optimized solution.     

Superposition Based on Watson–Crick-Like Complementarity

In this paper we propose a new formal operation on words and languages, called superposition. By this operation, based on a Watson–Crick-like complementarity, we can generate a set of words, starting from a pair of words, in which the contribution of a word to the result need not be one subword only, as happens in classical bio-operations of DNA computing. Specifically, starting from two single stranded molecules x and y such that a suffix of x is complementary to a prefix of y, a prefix of x is complementary to a suffix of y, or x is complementary to a subword of y, a new word z, which is a prolongation of x to the right, to the left, or to both, respectively, is obtained by annealing. If y is complementary to a subword of x, then the result is x. This operation is considered here as an abstract operation on formal languages. We relate it to other operations in formal language theory and we settle the closure properties under this operation of classes in the Chomsky hierarchy. We obtain a useful result by showing that unrestricted iteration of the superposition operation, where the "parents" in a subsequent iteration can be any words produced during any preceding iteration step, is equivalent to restricted iteration, where at each step one parent must be a word from the initial language. This result is used for establishing the closure properties of classes in the Chomsky hierarchy under iterated superposition. Actually, since the results are formulated in terms of AFL theory, they are applicable to more classes of languages. Then we discuss "adult" languages, languages consisting of words that cannot be extended by further superposition, and show that this notion might bring us to the border of recursive languages. Finally, we consider some operations involved in classical DNA algorithms, such as Adleman's, which might be expressed through iterated superposition.     

QoS Driven Per-Request Load-Aware Service Selection in Service Oriented Architectures

Service selection has been widely investigated by the SOA research community as an effective adaptation mechanism that allows a service broker, offering a composite service, to bind at runtime each task of the composite service to a corresponding concrete implementation, selecting it from a set of candidates which differ from one another in terms of QoS parameters. In this paper we present a load-aware per-request approach to service selection which aims to combine the relative benefits of the well known per-request and perflow approaches. Our service selection policy represents the core methodology of the Plan phase of a self-adaptive service oriented system based on the MAPE-K reference loop. Since the service broker operates in a variable and uncertain environment where the QoS levels negotiated with the service providers can fluctuate, it requires some mechanism to enforce the QoS constraints with its users. To this end, we also propose an algorithm for the Analyze phase of MAPE-K which is based on the adaptive Cusum algorithm and allows to determine whether a change in the QoS level requires a service selection replanning. We present experimental results obtained with a prototype implementation of a service broker. Our results show that the proposed load-aware approach is superior to the traditional perrequest one and combines the ability of sustaining large volume of service requests, as the perflow approach, while at the same time offering a finer customizable service selection, as the per-request approach. Furthermore, the results show that the adaptive Cusum algorithm can quickly detect changes in the execution environment and trigger a new optimization plan before the system performance degrades.     

Issues on soot removal from exhaust gases by means of radial flow ceramic traps

Radial flow ceramic foam traps (uncatalytic and catalytic) for soot removal from the exhausts of combustion systems were prepared. Their performances were tested by treating the exhaust of a gas-oil burner. Two different trap volumes (0.5 and 1.5 l) were employed to evaluate the effect of gas velocity on the trap filtering performances. It was found that at high gas velocity through the trap critical conditions leading to soot blow off may be reached in dependence of gas velocity and temperature, soot load on the trap and burner operating conditions (quantity and quality of particulate matter). At lower velocity critical conditions are unlikely to be achieved but the behaviour is still strongly dependent of the burner operating conditions. The catalytic trap showed good performances being able to remove soot from the burner exhaust gases with an efficiency of 70% and allowing the simultaneous filtration and combustion of the captured soot as well of part of the soot accumulated when the trap operating conditions were not favourable for soot combustion.     

Sketched symbol recognition using Latent-Dynamic Conditional Random Fields and distance-based clustering

In this paper we propose a two-stage method for recognizing sketched symbols that combine the use of a discriminative model, for labeling symbol strokes and a distance-based clustering algorithm, for grouping the labels belonging to the same symbol. In the first stage, we employ Latent-Dynamic Conditional Random Field (LDCRF), a discriminative model able to analyze the features of unsegmented sequences of strokes by taking into account spatio-temporal information, and to classify the symbol parts by considering contextual information. In the second stage, the labels obtained from LDCRF are grouped into symbol labels by using a distance-based clustering algorithm which takes into account the geometric relationships among strokes. The effectiveness of our method has been evaluated on the domain of electric circuit diagrams achieving accuracy values varying between 81.3% and 91.0%.     

Microwave Regenerated Catalytic Foam: A More Effective Way for PM Reduction

In this work the effect of microwave irradiation on the regeneration of soot-loaded uncatalytic and catalytic ceramic foam filters was studied for two different catalytic filter formulations. Combining dielectric permittivity and catalytic activity of the foam filter components with microwave absorbing properties of soot allowed a more effective filter regeneration. Moreover, iron based catalysts, typically not active towards soot oxidation in case of electrical heating, showed a significant activity in the presence of microwave.