Expressive power of binary relevance and chain classifiers based on Bayesian Networks for multi-label classification

Bayesian network classifiers are widely used in machine learning because they intuitively represent causal relations. Multi-label classification problems require each instance to be assigned a subset of a defined set of h labels. This problem is equivalent to finding a multi-valued decision function that predicts a vector of h binary classes. In this paper we obtain the decision boundaries of two widely used Bayesian network approaches for building multi-label classifiers: Multi-label Bayesian network classifiers built using the binary relevance method and Bayesian network chain classifiers. We extend our previous single-label results to multi-label chain classifiers, and we prove that, as expected, chain classifiers provide a more expressive model than the binary relevance method.

Estudio e implementación de estrategias de detección de objetos móviles mediante métodos basados en el uso de Local Binary Patterns

El objetivo de este Trabajo de Fin de Grado es el estudio e implementación de estrategias de detección de objetos móviles basadas en el uso de Local Binary Patterns. Para ello, en primer lugar se han analizado los métodos de substracción de fondos basados en información de textura propuestos durante los últimos años. Como resultado de este análisis, se ha implementado una estrategia basada en Local Binary Patterns a la que posteriormente se le han añadido las mejoras que se han considerado más apropiadas, las cuales están destinadas tanto a reducir el coste computacional de la estrategia como a mejorar la calidad de los resultados obtenidos. Por último se ha realizado un estudio comparativo entre las estrategias implementadas y otros métodos populares empleados para la substracción de fondos, como los basados en el uso de mezclas de gaussianas.

Efficient information reconciliation for Continuous-Variable QKD using Non-Binary Low-Density Parity-Check Codes

We present here an information reconciliation method and demonstrate for the first time that it can achieve efficiencies close to 0.98. This method is based on the belief propagation decoding of non-binary LDPC codes over finite (Galois) fields. In particular, for convenience and faster decoding we only consider power-of-two Galois fields.

Thermally tunable polarization by nanoparticle plasmonic resonance in photonic crystal fibers

A photonic crystal fiber selectively filled with silver nanoparticles dispersed in polydimethylsiloxane has been numerically studied via finite elements analysis. These nanoparticles possess a localized surface plasmon resonance in the visible region which depends on the refractive index of the surrounding medium. The refractive index of polydimethylsiloxane can be thermally tuned leading to the design of polarization tunable filters. Filters found with this setup show anisotropic attenuation of the x-polarization fundamental mode around ?x = 1200dB/cm remarkably higher than the y-polarization mode. Moreover, high fiber birefringence and birefringence reversal is observed in the spectral region of the plasmon.

Analysis of single and binary phases in cerium doped sodium bismuth titanate -Na0.5Bi0.5TiO3 materials

The pure and cerium doped sodium bismuth titanate inorganic powders were synthesized by solid state reaction method. The presence of rhombohedral phase was observed in cerium doped NBT compounds. At 1200 ºC, the 5% of cerium doped NBT compound forms single perovskite phase. The samples of x = 0.10 and 0.15 were heat treated to 1350 ºC, the binary phases with cerium and bismuth oxides were observed. The X-ray diffraction, fourier transform infrared spectroscopy, reflectance spectra, differential thermal analysis and thermo gravimetric analysis were used to analyze the various properties of samples. Moreover, the effects of cerium doping and calcining temperature on NBT samples were investigated. In this work we present our recent results on the synthesis and characterization of Ce doped sodium bismuth titanate materials.

Binary metal oxides for composite ultrafiltration membranes

A new ultrafiltration membrane was developed by the incorporation of binary metal oxides inside polyethersulfone. Physico-chemical characterization of the binary metal oxides demonstrated that the presence of Ti in the TiO2?ZrO2 system results in an increase of the size of the oxides, and also their dispersity. The crystalline phases of the synthesized binary metal oxides were identified as srilankite and zirconium titanium oxide. The effect of the addition of ZrO2 can be expressed in terms of the inhibition of crystal growth of anocrystalline TiO2 during the synthesis process. For photocatalytic applications the band gap of the synthesized semiconductors was determined, confirming a gradual increase (blue shift) in the band gap as the amount of Zr loading increases. Distinct distributions of binary metal oxides were found along the permeation axis for the synthesized membranes. Particles with Ti are more uniformly dispersed throughout the membrane cross-section. The physico-chemical characterization of membranes showed a strong correlation between some key membrane properties and the spatial particle distribution in the membrane structure. The proximity of metal oxide fillers to the membrane surface determines the hydrophilicity and porosity of modified membranes. Membranes incorporating binary metal oxides were found to be promising candidates for wastewater treatment by ultrafiltration, considering the observed improvement influx and anti-fouling properties of doped membranes. Multi-run fouling tests of doped membranes confirmed the stability of permeation through membranes embedded with binary TiO2?ZrO2 particles.

Human-computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns

A more natural, intuitive, user-friendly, and less intrusive Human–Computer interface for controlling an application by executing hand gestures is presented. For this purpose, a robust vision-based hand-gesture recognition system has been developed, and a new database has been created to test it. The system is divided into three stages: detection, tracking, and recognition. The detection stage searches in every frame of a video sequence potential hand poses using a binary Support Vector Machine classifier and Local Binary Patterns as feature vectors. These detections are employed as input of a tracker to generate a spatio-temporal trajectory of hand poses. Finally, the recognition stage segments a spatio-temporal volume of data using the obtained trajectories, and compute a video descriptor called Volumetric Spatiograms of Local Binary Patterns (VS-LBP), which is delivered to a bank of SVM classifiers to perform the gesture recognition. The VS-LBP is a novel video descriptor that constitutes one of the most important contributions of the paper, which is able to provide much richer spatio-temporal information than other existing approaches in the state of the art with a manageable computational cost. Excellent results have been obtained outperforming other approaches of the state of the art.

Multistability, chaos, and random signal generation in semiconductor superlattices

Peer reviewed

On the classification of binary shifts of finite commutant index

We provide a complete classification up to conjugacy of the binary shifts of finite commutant index on the hyperfinite II1, factor. There is a natural correspondence between the conjugacy classes of these shifts and polynomials over GF(2) satisfying a certain duality condition.

Extremely sensitive, background-free gene detection using binary probes and beta replicase.

We have developed a specific and sensitive nucleic acid amplification assay that is suitable for routine gene detection. The assay is based on a novel molecular genetic strategy in which two different RNA probes are hybridized to adjacent positions on a target nucleic acid and then ligated to form an amplifiable reporter RNA. The reporter RNA is then replicated up to a hundred billion-fold in a 30-min isothermal reaction that signals the presence of the target. The assay can detect fewer than 100 nucleic acid molecules; it provides quantitative results over a wide range of target concentrations and it employs a universal format that can detect any infectious agent.

Simultaneous optical and X-ray observations of flares and rotational modulation on the RS CVn binary HR 1099 (V711 Tau) from the MUSICOS 1998 campaign

We present simultaneous and continuous observations of the Hα, Hβ, He I D_3, Na I D_1,D_2 doublet and the Ca II H&K lines for the RS CVn system HR 1099. The spectroscopic observations were obtained during the MUSICOS 1998 campaign involving several observatories and instruments, both echelle and long-slit spectrographs. During this campaign, HR 1099 was observed almost continuously for more than 8 orbits of 2^d.8. Two large optical flares were observed, both showing an increase in the emission of Hα, Ca II H K, Hβ and He I D_3 and a strong filling-in of the Na I D_1, D_2 doublet. Contemporary photometric observations were carried out with the robotic telescopes APT-80 of Catania and Phoenix-25 of Fairborn Observatories. Maps of the distribution of the spotted regions on the photosphere of the binary components were derived using the Maximum Entropy and Tikhonov photometric regularization criteria. Rotational modulation was observed in Hα and He I D_3 in anti-correlation with the photometric light curves. Both flares occurred at the same binary phase (0.85), suggesting that these events took place in the same active region. Simultaneous X-ray observations, performed by ASM on board RXTE, show several flare-like events, some of which correlate well with the observed optical flares. Rotational modulation in the X-ray light curve has been detected with minimum flux when the less active G5 V star was in front. A possible periodicity in the X-ray flare-like events was also found.

Can fractal-like spectra be experimentally observed in aperiodic superlattices?

We numerically investigate the effects of inhomogeneities in the energy spectrum of aperiodic semiconductor superlattices, focusing our attention on Thue-Morse and Fibonacci sequences. In the absence of disorder, the corresponding electronic spectra are self-similar. The presence of a certain degree of randomness, due to imperfections occurring during the growth processes, gives rise to a progressive loss of quantum coherence, smearing out the finer details of the energy spectra predicted for perfect aperiodic superlattices and spurring the onset of electron localization. However, depending on the degree of disorder introduced, a critical size for the system exists, below which peculiar transport properties, related to the pre-fractal nature of the energy spectrum, may be measured.

A Hydrodynamic Method For Measuring Aqueous Nanoparticle Surface Interactions

The objectives of this research dissertation were to develop and present novel analytical methods for the quantification of surface binding interactions between aqueous nanoparticles and water-soluble organic solutes. Quantification of nanoparticle surface interactions are presented in this work as association constants where the solutes have interacted with the surface of the nanoparticles. By understanding these nanoparticle-solute interactions, in part through association constants, the scientific community will better understand how organic drugs and nanomaterials interact in the environment, as well as to understand their eventual environmental fate. The biological community, pharmaceutical, and consumer product industries also have vested interests in nanoparticle-drug interactions for nanoparticle toxicity research and in using nanomaterials as drug delivery vesicles. The presented novel analytical methods, applied to nanoparticle surface association chemistry, may prove to be useful in assisting the scientific community to understand the risks, benefits, and opportunities of nanoparticles. The development of the analytical methods presented uses a model nanoparticle, Laponite-RD (LRD). LRD was the proposed nanoparticle used to model the system and technique because of its size, 25 nm in diameter. The solutes selected to model for these studies were chosen because they are also environmentally important. Caffeine, oxytetracycline (OTC), and quinine were selected to use as models because of their environmental importance and chemical properties that can be exploited in the system. All of these chemicals are found in the environment; thus, how they interact with nanoparticles and are transported through the environment is important. The analytical methods developed utilize and a wide-bore hydrodynamic chromatography to induce a partial hydrodynamic separation between nanoparticles and dissolved solutes. Then, using deconvolution techniques, two separate elution profiles for the nanoparticle and organic solute can be obtained. Followed by a mass balance approach, association constants between LRD, our model nanoparticle, and organic solutes are calculated. These findings are the first of their kind for LRD and nanoclays in dilute dispersions.

Correlation of the liquid–liquid equilibrium data for specific ternary systems with one or two partially miscible binary subsystems

This paper presents the results of a liquid–liquid equilibrium data correlation for 11 ternary systems which have not been previously fitted using the NRTL model or, when they have, the results presented in the literature are inconsistent with the experimental behavior of the system. These ternary systems include mixtures with one or two partially miscible pairs. During the correlation process, new restrictions were imposed on the values for the NRTL binary parameters to ensure correct prediction of the total or partial miscibility for the binary pairs involved. In addition, topological concepts related to the Gibbs stability test have been applied in order to validate the results in the whole range of compositions.

An algorithm to hide information in binary images

The objective of this paper is to develop a method to hide information inside a binary image. An algorithm to embed data in scanned text or figures is proposed, based on the detection of suitable pixels, which verify some conditions in order to be not detected. In broad terms, the algorithm locates those pixels placed at the contours of the figures or in those areas where some scattering of the two colors can be found. The hidden information is independent from the values of the pixels where this information is embedded. Notice that, depending on the sequence of bits to be hidden, around half of the used pixels to keep bits of data will not be modified. The other basic characteristic of the proposed scheme is that it is necessary to take into consideration the bits that are modified, in order to perform the recovering process of the information, which consists on recovering the sequence of bits placed in the proper positions. An application to banking sector is proposed for hidding some information in signatures.