Compositionality and lexical alignment of multi-word terms

The automatic compilation of bilingual lists of terms from specialized comparable corpora using lexical alignment has been successful for single-word terms (SWTs), but remains disappointing for multi-word terms (MWTs). The low frequency and the variability of the syntactic structures of MWTs in the source and the target languages are the main reported problems. This paper defines a general framework dedicated to the lexical alignment of MWTs from comparable corpora that includes a compositional translation process and the standard lexical context analysis. The compositional method which is based on the translation of lexical items being restrictive, we introduce an extended compositional method that bridges the gap between MWTs of different syntactic structures through morphological links. We experimented with the two compositional methods for the French–Japanese alignment task. The results show a significant improvement for the translation of MWTs and advocate further morphological analysis in lexical alignment.     

Cancellation of bulging effect on mould level in continuous casting: Experimental validation

During the continuous casting of steel, several disturbances occur and affect all the parts of the caster, including the mould where the molten steel has to be stable for good quality of the final product. Especially at high casting velocities, the bulging generates important level fluctuations which cannot be efficiently rejected by the classical controllers. To address these problems, this paper proposes an architecture combining disturbances estimation and compensation techniques. It operates as an additional module and does not need any change of the main controller currently implemented. The entire structure has been tested successfully through several simulations and by means of intensive water model experiments.     

Temperature sensor based on the Er green upconverted emission in a fluorotellurite glass

The temperature dependence of the green upconverted emission from the two thermally coupled ²H_11/2 and ⁴S_3/2 levels of the Er³⁺ ion in a fluorotellurite glass has been analyzed as a function of the optically active ion concentration in order to check its availability as a temperature sensor. The infrared-to-green upconverted emission have been observed by the naked eyes after a cw laser diode excitation at 800 nm. The fluorescence intensity ratio between the thermally coupled emitting levels as well as the temperature sensitivity has been experimentally obtained up to 540 K. A better behaviour as a temperature sensor has been obtained for the less Er³⁺ concentrated glass with a maximum sensitivity of 54 × 10⁻⁴ K⁻¹ at 540 K, one of the highest found in rare-earth doped transparent materials.     

Antichains and compositional algorithms for LTL synthesis

In this paper, we present new monolithic and compositional algorithms to solve the LTL realizability problem. Those new algorithms are based on a reduction of the LTL realizability problem to a game whose winning condition is defined by a universal automaton on infinite words with a k-co-Büchi acceptance condition. This acceptance condition asks that runs visit at most k accepting states, so it implicitly defines a safety game. To obtain efficient algorithms from this construction, we need several additional ingredients. First, we study the structure of the underlying automata constructions, and we show that there exists a partial order that structures the state space of the underlying safety game. This partial order can be used to define an efficient antichain algorithm. Second, we show that the algorithm can be implemented in an incremental way by considering increasing values of k in the acceptance condition. Finally, we show that for large LTL formulas that are written as conjunctions of smaller formulas, we can solve the problem compositionally by first computing winning strategies for each conjunct that appears in the large formula. We report on the behavior of those algorithms on several benchmarks. We show that the compositional algorithms are able to handle LTL formulas that are several pages long.     

Objective selection of suitable unit cell size in data-driven modeling of mineral prospectivity

In GIS-based data-driven modeling of mineral prospectivity, a suitably fine unit cell size is used for spatial representation of known occurrences of mineral deposits of the type sought (D) in a study area (T). However, until now, the unit cell size is chosen subjectively. In this paper, a methodology is proposed for objective selection of the most suitable unit cell size for data-driven modeling of mineral prospectivity using a raster-based GIS. A set of choices of suitable unit cell sizes is first derived via point pattern analysis of a set of known occurrences of mineral deposits of the type sought. Then, (a) the lower limit of a set of choices of suitable unit cell sizes is considered and defined according to the map scales from which spatial data for mineral prospectivity mapping were derived, and (b) the upper limit of the same set of choices of suitable unit cell sizes is considered (and revised as necessary) based on knowledge of spatial extents of mineral deposits of the type sought or via analysis of reflexive nearest neighbour points. Finally, it is shown that fractal analysis of spatial contrast between unit cells containing D and unit cells not containing D in T provides for objective selection of the most suitable unit cell size. In a case study application of the weight-of-evidence method to mineral prospectivity mapping, using the most suitable unit cell size, found via the proposed methodology, results in spatial evidence weights and weight uncertainties that are nearly identical to those derived by using the finest (i.e., lower limit) unit cell size. In contrast to using the most suitable unit cell size, using coarser unit cell sizes result in higher positive weights, lower negative weights and higher weight uncertainties of spatial evidence of mineral prospectivity. The proposed methodology for objective selection of the most suitable unit cell size in data-driven modeling of mineral prospectivity using a raster-based GIS is robust and can easily be implemented.     

Tool path smoothing of a redundant machine: Application to Automated Fiber Placement

Automated Tape Laying and Fiber Placement of composite materials are the two principal automated processes used for fabrication of large composite structures in aeronautical industry. The aluminum parts produced by High Speed Machining tend to be replaced by carbon fiber composite parts realized with these processes. However, structural parts present reinforcement zones which disturb the tool path follow-up and generate an increase of the manufacturing time. Thus, this paper deals with the optimization of tool paths of a 7-axis machine tool of Fiber Placement with the objective of reducing the manufacturing time while ensuring the requested quality of the final part. In this paper, two complementary methods are detailed. The first method takes advantage of the degree of redundancy of the machine tool to decrease the kinematic loads of the control joints. The second method aims to smooth the orientation of the machine head along the tool path while ensuring quality constraints. These two methods are then applied on a test tool path and bring to a significant decrease of the manufacturing time (32.9%).     

Evaluating increasing block tariff pricing policies when applied to multiple household connections

This paper develops a model for evaluating the consequences of increasing block tariff pricing policies when multiple households share a connection and applies it to a sample from Kumasi, Ghana. Results show that for any given consumption, a household's average share of total monthly water bill for shared connections can either be higher or lower than its single-household equivalent. Significant differences between the average and single-household equivalent bills were found in these cases, although this difference is under-estimated if the sample is not disaggregated by payment group.     

Enhanced energetic reasoning-based lower bounds for the resource constrained project scheduling problem

We present new and effective lower bounds for the resource constrained project scheduling problem. This problem is widely known to be notoriously difficult to solve due to the lack of lower bounds that are both tight and fast. In this paper, we propose several new lower bounds that are based on the concept of energetic reasoning. A major contribution of this work is to investigate several enhanced new feasibility tests that prove useful for deriving new lower bounds that consistently outperform the classical energetic reasoning-based lower bound. In particular, we present the results of a comprehensive computational study, carried out on 1560 benchmark instances, that provides strong evidence that a deceptively simple dual feasible function-based lower bound is highly competitive with a state-of-the-art lower bound while being extremely fast. Furthermore, we found that an effective shaving procedure enables to derive an excellent lower bound that often outperforms the best bound from the literature while being significantly simpler.