Large-scale linked data integration using probabilistic reasoning and crowdsourcing

We tackle the problems of semiautomatically matching linked data sets and of linking large collections of Web pages to linked data. Our system, ZenCrowd, (1) uses a three-stage blocking technique in order to obtain the best possible instance matches while minimizing both computational complexity and latency, and (2) identifies entities from natural language text using state-of-the-art techniques and automatically connects them to the linked open data cloud. First, we use structured inverted indices to quickly find potential candidate results from entities that have been indexed in our system. Our system then analyzes the candidate matches and refines them whenever deemed necessary using computationally more expensive queries on a graph database. Finally, we resort to human computation by dynamically generating crowdsourcing tasks in case the algorithmic components fail to come up with convincing results. We integrate all results from the inverted indices, from the graph database and from the crowd using a probabilistic framework in order to make sensible decisions about candidate matches and to identify unreliable human workers. In the following, we give an overview of the architecture of our system and describe in detail our novel three-stage blocking technique and our probabilistic decision framework. We also report on a series of experimental results on a standard data set, showing that our system can achieve a 95 % average accuracy on instance matching (as compared to the initial 88 % average accuracy of the purely automatic baseline) while drastically limiting the amount of work performed by the crowd. The experimental evaluation of our system on the entity linking task shows an average relative improvement of 14 % over our best automatic approach.     

On the hardness of solving edge matching puzzles as SAT or CSP problems

Edge matching puzzles have been amongst us for a long time now and traditionally they have been considered, both, a children’s game and an interesting mathematical divertimento. Their main characteristics have already been studied, and their worst-case complexity has been properly classified as a NP-complete problem. It is in recent times, specially after being used as the problem behind a money-prized contest, with a prize of 2US$ million for the first solver, that edge matching puzzles have attracted mainstream attention from wider audiences, including, of course, computer science people working on solving hard problems. We consider these competitions as an interesting opportunity to showcase SAT/CSP solving techniques when confronted to a real world problem to a broad audience, a part of the intrinsic, i.e. monetary, interest of such a contest. This article studies the NP-complete problem known as edge matching puzzle using SAT and CSP approaches for solving it. We will focus on providing, first and foremost, a theoretical framework, including a generalized definition of the problem. We will design and show algorithms for easy and fast problem instances generation, generators with easily tunable hardness. Afterwards we will provide with SAT and CSP models for the problems and we will study problem complexity, both typical case and worst-case complexity. We will also provide some specially crafted heuristics that result in a boost in solving time and study which is the effect of such heuristics.     

Estimation of soil clay and calcium carbonate using laboratory, field and airborne hyperspectral measurements

This paper examines how reflectance spectrometry used in the laboratory to estimate clay and calcium carbonate (CaCO₃) soil contents can be applied to field and airborne measurements for soil property mapping. A continuum removal (CR) technique quantifying specific absorption features of clay (2206 nm) and CaCO₃ (2341 nm) was applied to laboratory, field and airborne HYMAP reflectance measurements collected in 2003 (33 sites) and 2005 (19 sites) over bare soil sites of a few meters within the La Peyne Valley area, southern France. Nine intermediate stages from the laboratory up to HYMAP sensor measurements were considered for separately evaluating the possible degradation of estimation performances when going across scales and sensors, e.g. radiometric calibration, spectral resolution, spatial variability, illumination conditions, and surface status including roughness, soil moisture and presence and nature of pebbles.Significant relationships were observed between clay and CaCO₃ contents and CR values computed respectively at 2206 nm and 2341 nm from reflectance measurements at the laboratory level with an ASD spectrophotometer up to the HYMAP spectro-imaging sensor. Performances of clay and CaCO₃ estimations decreased from the laboratory to airborne scales. The main factors inducing uncertainties in the estimates were radiometric and wavelength calibration uncertainties of the HYMAP sensor as well as possible residual atmospheric effects.     

An efficient algorithm for positive realizations

We observe that successive applications of known results from the theory of positive systems lead to an efficient general algorithm for positive realizations of transfer functions. We give two examples to illustrate the algorithm, one of which complements an earlier result of [L. Benvenuti, L. Farina, An example of how positivity may force realizations of ‘large’ dimensions, Systems Control Lett. 36 (1999) 261–266]. Finally, we improve a lower-bound of [B. Nagy, M. Matolcsi, A lower-bound on the dimension of positive realizations, IEEE Trans. Circuits Syst. I 50 (2003) 782–784] to indicate that the algorithm is indeed efficient in general.     

Synchronized switch harvesting applied to self-powered smart systems: Piezoactive microgenerators for autonomous wireless receivers

This paper introduces the conceptual architecture of a fully integrated, truly self-powered structural health monitoring (SHM) scheme. The challenge here is to power an array of numerous distributed actuators and sensors as well as wireless data transmission modules without recurring to heavy and costly wiring. Based on microgenerators which directly convert ambient mechanical energy into electrical energy, using the synchronized switch harvesting (SSH) method, the proposed solution allows avoiding the periodic replacement or reloading of batteries. This addresses environmental and economic issues at the same time, knowing that such elements are heavy, polluting and might be installed in rather inaccessible locations. Indeed, especially in airborne structures saving weight and maintenance cost is of priority importance.Previous work showed that such microgenerators provide a stand-alone power source, whose performances meet the requirements of autonomous wireless transmitters (AWTs) that comprise an acoustic Lamb wave's actuator and a radio frequency (RF) emitter (D. Guyomar, Y. Jayet, L. Petit, E. Lefeuvre, T. Monnier, C. Richard, M. Lallart, Synchronized switch harvesting applied to self-powered smart systems: Piezoactive microgenerators for autonomous wireless transmitters, Sens Actuators A: Phys. 138 (1) (2007) 151–160, doi:10.1016/j.sna.2007.04.009). Following this work, the present contribution presents a further step towards the integration of the SHM technique. It shows the ability of our microgenerators to provide enough energy to give logical autonomy to each self-powered sensing node, named autonomous wireless receiver (AWR), and thus to provide some local (decentralized) pre-processing ability to the SHM system.A preliminary design of the device using off-the-shelf electronics and surface mounted piezoelectric patches will be presented. Since the existence of a positive energy balance between the harvesting capabilities of the SSH technique and the energy requirements of the proposed device will be proved, the system formed by the combination of the AWR with the previously developed AWT, is a proof of concept of truly self-powered smart systems for damage detection in simple structures, setting apart application-specific optimization or miniaturization concerns that will be addressed in future works.     

Improving the Behavior of Intelligent Tutoring Agents with Data Mining

This article presents a novel framework for adapting the behavior of intelligent agents. The framework consists of an extended sequential pattern mining algorithm that, in combination with association rule discovery techniques, is used to extract temporal patterns and relationships from the behavior of human agents executing a procedural task. The proposed framework has been integrated within the CanadarmTutor, an intelligent tutoring agent aimed at helping students solve procedural problems that involve moving a robotic arm in a complex virtual environment. We present the results of an evaluation that demonstrates the benefits of this integration to agents acting in ill-defined domains.     

Proteomic Helicobacter pylori biomarkers discriminative of low-grade gastric MALT lymphoma and duodenal ulcer

To date no reliable diagnostic method exists to predict, among the very large and clinically heterogeneous group of Helicobacter pylori‐infected patients, the extremely small group at risk for developing low‐grade gastric MALT lymphoma (LG‐MALT). Search of proteomic biomarkers holds promise for the classification of the H. pylori strains with regard to this severe clinical outcome. In the present study 69 H. pylori strains isolated from patients with two different H. pylori‐associated diseases, duodenal ulcer (DU, n=29) and LG‐MALT (n=40) were used. Protein expression patterns of the strains were analyzed by using the high‐throughput methodology SELDI. Selected proteins were purified by means of chromatographic and electrophoretic methods in view of further sequencing by LC‐MS/MS. Univariate analysis (Mann–Whitney test) of the protein expression patterns generated nine significant biomarkers that can discriminate between H. pylori strains from patients with DU and LG‐MALT. These biomarkers are of low molecular weight, ranging from 6 to 26.6 kDa. Among them, two are overexpressed in LG‐MALT strains and seven – in DU strains. Two biomarker proteins, one overexpressed in LG‐MALT strains (13.2 kDa) and another one – overexpressed in DU strains (26.6 kDa), were purified to homogeneity and identified by using LC‐MS/MS as a 50S ribosomal protein L7/L12 and a urease subunit, respectively. These biomarkers can be included in novel protein arrays for the differential diagnosis of H. pylori‐associated clinical outcomes.     

Exciton Formation Dynamics and Band-Like Free Charge-Carrier Transport in 2D Metal Halide Perovskite Semiconductors

Metal halide perovskite (MHP) semiconductors have driven a revolution in optoelectronic technologies over the last decade, in particular for high-efficiency photovoltaic applications. Low-dimensional MHPs presenting electronic confinement have promising additional prospects in light emission and quantum technologies. However, the optimisation of such applications requires a comprehensive understanding of the nature of charge carriers and their transport mechanisms. This study employs a combination of ultrafast optical and terahertz spectroscopy to investigate phonon energies, charge-carrier mobilities, and exciton formation in 2D (PEA)₂PbI₄ and (BA)₂PbI₄ (where PEA is phenylethylammonium and BA is butylammonium). Temperature-dependent measurements of free charge-carrier mobilities reveal band transport in these strongly confined semiconductors, with surprisingly high in-plane mobilities. Enhanced charge-phonon coupling is shown to reduce charge-carrier mobilities in (BA)₂PbI₄ with respect to (PEA)₂PbI₄. Exciton and free charge-carrier dynamics are disentangled by simultaneous monitoring of transient absorption and THz photoconductivity. A sustained free charge-carrier population is observed, surpassing the Saha equation predictions even at low temperature. These findings provide new insights into the temperature-dependent interplay of exciton and free-carrier populations in 2D MHPs. Furthermore, such sustained free charge-carrier population and high mobilities demonstrate the potential of these semiconductors for applications such as solar cells, transistors, and electrically driven light sources.     

Energy Efficient Hardware Loop Based Optimization for CGRAs

Journal of Signal Processing Systems - Research interest and industry investment in edge computing solutions have increased dramatically in recent years. Consequent quest for balanced performance,...     

3D Orientational Control in Self‐Assembled Thin Films with Sub‐5 nm Features by Light

While self‐assembled molecular building blocks could lead to many next‐generation functional organic nanomaterials, control over the thin‐film morphologies to yield monolithic sub‐5 nm patterns with 3D orientational control at macroscopic length scales remains a grand challenge. A series of photoresponsive hybrid oligo(dimethylsiloxane) liquid crystals that form periodic cylindrical nanostructures with periodicities between 3.8 and 5.1 nm is studied. The liquid crystals can be aligned in‐plane by exposure to actinic linearly polarized light and out‐of‐plane by exposure to actinic unpolarized light. The photoalignment is most efficient when performed just under the clearing point of the liquid crystal, at which the cylindrical nanostructures are reoriented within minutes. These results allow the generation of highly ordered sub‐5 nm patterns in thin films at macroscopic length scales, with control over the orientation in a noncontact fashion.