Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Direct in vitro comparison of six three-dimensional positive contrast methods for susceptibility marker imaging.

PURPOSE: To compare different techniques for positive contrast imaging of susceptibility markers with MRI for three-dimensional visualization. As several different techniques have been reported, the choice of the suitable method depends on its properties with regard to the amount of positive contrast and the desired background suppression, as well as other imaging constraints needed for a specific application. MATERIALS AND METHODS: Six different positive contrast techniques are investigated for their ability to image at 3 Tesla a single susceptibility marker in vitro. The white marker method (WM), susceptibility gradient mapping (SGM), inversion recovery with on-resonant water suppression (IRON), frequency selective excitation (FSX), fast low flip-angle positive contrast SSFP (FLAPS), and iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) were implemented and investigated. RESULTS: The different methods were compared with respect to the volume of positive contrast, the product of volume and signal intensity, imaging time, and the level of background suppression. Quantitative results are provided, and strengths and weaknesses of the different approaches are discussed. CONCLUSION: The appropriate choice of positive contrast imaging technique depends on the desired level of background suppression, acquisition speed, and robustness against artifacts, for which in vitro comparative data are now available.

Free-breathing 3D steady-state free precession coronary MR angiography with radial k-space sampling: comparison with cartesian k-space sampling and cartesian gradient-echo coronary MR angiography--pilot study.

The authors compared radial steady-state free precession (SSFP) coronary magnetic resonance (MR) angiography, cartesian k-space sampling SSFP coronary MR angiography, and gradient-echo coronary MR angiography in 16 healthy adults and four pilot study patients. Standard gradient-echo MR imaging with a T2 preparatory pulse and cartesian k-space sampling was the reference technique. Image quality was compared by using subjective motion artifact level and objective contrast-to-noise ratio and vessel sharpness. Radial SSFP, compared with cartesian SSFP and gradient-echo MR angiography, resulted in reduced motion artifacts and superior vessel sharpness. Cartesian SSFP resulted in increased motion artifacts (P <.05). Contrast-to-noise ratio with radial SSFP was lower than that with cartesian SSFP and similar to that with the reference technique. Radial SSFP coronary MR angiography appears preferable because of improved definition of vessel borders.

Direct comparison of 3D spiral vs. Cartesian gradient-echo coronary magnetic resonance angiography.

While 3D thin-slab coronary magnetic resonance angiography (MRA) has traditionally been performed using a Cartesian acquisition scheme, spiral k-space data acquisition offers several potential advantages. However, these strategies have not been directly compared in the same subjects using similar methodologies. Thus, in the present study a comparison was made between 3D coronary MRA using Cartesian segmented k-space gradient-echo and spiral k-space data acquisition schemes. In both approaches the same spatial resolution was used and data were acquired during free breathing using navigator gating and prospective slice tracking. Magnetization preparation (T(2) preparation and fat suppression) was applied to increase the contrast. For spiral imaging two different examinations were performed, using one or two spiral interleaves, during each R-R interval. Spiral acquisitions were found to be superior to the Cartesian scheme with respect to the signal-to-noise ratio (SNR) and contrast-to-noise-ratio (CNR) (both P < 0.001) and image quality. The single spiral per R-R interval acquisition had the same total scan duration as the Cartesian acquisition, but the single spiral had the best image quality and a 2.6-fold increase in SNR. The double-interleaf spiral approach showed a 50% reduction in scanning time, a 1.8-fold increase in SNR, and similar image quality when compared to the standard Cartesian approach. Spiral 3D coronary MRA appears to be preferable to the Cartesian scheme. The increase in SNR may be "traded" for either shorter scanning times using multiple consecutive spiral interleaves, or for enhanced spatial resolution.

Comparison of 3D segmented gradient-echo and steady-state free precession coronary MRI sequences in patients with coronary artery disease.

OBJECTIVE: Our objective was to compare two state-of-the-art coronary MRI (CMRI) sequences with regard to image quality and diagnostic accuracy for the detection of coronary artery disease (CAD). SUBJECTS AND METHODS: Twenty patients with known CAD were examined with a navigator-gated and corrected free-breathing 3D segmented gradient-echo (turbo field-echo) CMRI sequence and a steady-state free precession sequence (balanced turbo field-echo). CMRI was performed in a transverse plane for the left coronary artery and a double-oblique plane for the right coronary artery system. Subjective image quality (1- to 4-point scale, with 1 indicating excellent quality) and objective image quality parameters were independently determined for both sequences. Sensitivity, specificity, and accuracy for the detection of significant (> or = 50% diameter) coronary artery stenoses were determined as defined in invasive catheter X-ray coronary angiography. RESULTS: Subjective image quality was superior for the balanced turbo field-echo approach (1.8 +/- 0.9 vs 2.3 +/- 1.0 for turbo field-echo; p < 0.001). Vessel sharpness, signal-to-noise ratio, and contrast-to-noise ratio were all superior for the balanced turbo field-echo approach (p < 0.01 for signal-to-noise ratio and contrast-to-noise ratio). Of the 103 segments, 18% of turbo field-echo segments and 9% of balanced turbo field-echo segments had to be excluded from disease evaluation because of insufficient image quality. Sensitivity, specificity, and accuracy for the detection of significant coronary artery stenoses in the evaluated segments were 92%, 67%, 85%, respectively, for turbo field-echo and 82%, 82%, 81%, respectively, for balanced turbo field-echo. CONCLUSION: Balanced turbo field-echo offers improved image quality with significantly fewer nondiagnostic segments when compared with turbo field-echo. For the detection of CAD, both sequences showed comparable accuracy for the visualized segments.

Ant species distribution along a topographic gradient in a "terra-firme" forest reserve in Central Amazonia

In Amazonia, topographical variations in soil and forest structure within "terra-firme" ecosystems are important factors correlated with terrestrial invertebrates' distribution. The objective of this work was to assess the effects of soil clay content and slope on ant species distribution over a 25 km² grid covering the natural topographic continuum. Using three complementary sampling methods (sardine baits, pitfall traps and litter samples extracted in Winkler sacks), 300 subsamples of each method were taken in 30 plots distributed over a wet tropical forest in the Ducke Reserve (Manaus, AM, Brazil). An amount of 26,814 individuals from 11 subfamilies, 54 genera, 85 species and 152 morphospecies was recorded (Pheidole represented 37% of all morphospecies). The genus Eurhopalothrix was registered for the first time for the reserve. Species number was not correlated with slope or clay content, except for the species sampled from litter. However, the Principal Coordinate Analysis indicated that the main pattern of species composition from pitfall and litter samples was related to clay content. Almost half of the species were found only in valleys or only on plateaus, which suggests that most of them are habitat specialists. In Central Amazonia, soil texture is usually correlated with vegetation structure and moisture content, creating different microhabitats, which probably account for the observed differences in ant community structure.

On the diurnal soil water content dynamics during evaporation using dielectric methods

The water content dynamics in the upper soil surface during evaporation is a key element in land-atmosphere exchanges. Previous experimental studies have suggested that the soil water content increases at the depth of 5 to 15 cm below the soil surface during evapo- ration, while the layer in the immediate vicinity of the soil surface is drying. In this study, the dynamics of water content profiles exposed to solar radiative forcing was monitored at a high temporal resolution using dielectric methods both in the presence and absence of evaporation. A 4-d comparison of reported moisture content in coarse sand in covered and uncovered buckets using a commercial dielectric-based probe (70 MHz ECH2O-5TE, Decagon Devices, Pullman, WA) and the standard 1-GHz time domain reflectometry method. Both sensors reported a positive correlation between temperature and water content in the 5- to 10-cm depth, most pronounced in the morning during heating and in the afternoon during cooling. Such positive correlation might have a physical origin induced by evaporation at the surface and redistribution due to liquid water fluxes resulting from the temperature- gradient dynamics within the sand profile at those depths. Our experimental data suggest that the combined effect of surface evaporation and temperature-gradient dynamics should be considered to analyze experimental soil water profiles. Additional effects related to the frequency of operation and to protocols for temperature compensation of the dielectric sensors may also affect the probes' response during large temperature changes.

Minimization of Nyquist ghosting for echo-planar imaging at ultra-high fields based on a "negative readout gradient" strategy.

PURPOSE: To improve the traditional Nyquist ghost correction approach in echo planar imaging (EPI) at high fields, via schemes based on the reversal of the EPI readout gradient polarity for every other volume throughout a functional magnetic resonance imaging (fMRI) acquisition train. MATERIALS AND METHODS: An EPI sequence in which the readout gradient was inverted every other volume was implemented on two ultrahigh-field systems. Phantom images and fMRI data were acquired to evaluate ghost intensities and the presence of false-positive blood oxygenation level-dependent (BOLD) signal with and without ghost correction. Three different algorithms for ghost correction of alternating readout EPI were compared. RESULTS: Irrespective of the chosen processing approach, ghosting was significantly reduced (up to 70% lower intensity) in both rat brain images acquired on a 9.4T animal scanner and human brain images acquired at 7T, resulting in a reduction of sources of false-positive activation in fMRI data. CONCLUSION: It is concluded that at high B(0) fields, substantial gains in Nyquist ghost correction of echo planar time series are possible by alternating the readout gradient every other volume.

Improved SNR efficiency in gradient echo coronary MRA with high temporal resolution using parallel imaging.

Contemporary coronary magnetic resonance angiography techniques suffer from signal-to-noise ratio (SNR) constraints. We propose a method to enhance SNR in gradient echo coronary magnetic resonance angiography by using sensitivity encoding (SENSE). While the use of sensitivity encoding to improve SNR seems counterintuitive, it can be exploited by reducing the number of radiofrequency excitations during the acquisition window while lowering the signal readout bandwidth, therefore improving the radiofrequency receive to radiofrequency transmit duty cycle. Under certain conditions, this leads to improved SNR. The use of sensitivity encoding for improved SNR in three-dimensional coronary magnetic resonance angiography is investigated using numerical simulations and an in vitro and an in vivo study. A maximum 55% SNR enhancement for coronary magnetic resonance angiography was found both in vitro and in vivo, which is well consistent with the numerical simulations. This method is most suitable for spoiled gradient echo coronary magnetic resonance angiography in which a high temporal and spatial resolution is required.

Dispersal ability modulates the strength of the latitudinal richness gradient in European beetles.

Aim A debate exists as to whether present-day diversity gradients are governed by current environmental conditions or by changes in environmental conditions through time. Recent studies have shown that latitudinal richness gradients might be partially caused by incomplete post-glacial recolonization of high-latitude regions; this leads to the prediction that less mobile taxa should have steeper gradients than more mobile taxa. The aim of this study is to test this prediction. Location Europe. Methods We first assessed whether spatial turnover in species composition is a good surrogate for dispersal ability by measuring the proportion of wingless species in 19 European beetle clades and relating this value to spatial turnover (beta sim) of the clade. We then linearly regressed beta sim values of 21 taxa against the slope of their respective diversity gradients. Results A strong relationship exists between the proportion of wingless species and beta sim, and beta sim was found to be a good predictor of latitudinal richness gradients. Main conclusions Results are consistent with the prediction that poor dispersers have steeper richness gradients than good dispersers, supporting the view that current beetle diversity gradients in Europe are affected by post-glacial dispersal lags.

Obese, smoker, and obese smoker : is there a general lifestyle gradient?

Aim: Obesity and smoking are major CVD risk factors and may be associated with other unfavourable lifestyle behaviours. Our aim was to investigate the significance of obesity, heavy smoking, and both combined in terms of prevalence trends and their relationship with other lifestyle factors. Methods: We used data from the population-based cross-sectional Swiss Health Survey (5 waves, 1992-2012) comprising 85,575 individuals aged 18 years. Height, weight, and smoking status were self-reported. We used multinomial logistic regression to analyse differences in lifestyle for the combinations of BMI category and smoking status, focusing on obese and heavy smokers. We defined normal-weight never smokers as reference.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Heat flux measurement inside internal combustion engine with gradient heat flux sensor.

This master’s thesis is devoted to study different heat flux measurement techniques such as differential temperature sensors, semi-infinite surface temperature methods, calorimetric sensors and gradient heat flux sensors. The possibility to use Gradient Heat Flux Sensors (GHFS) to measure heat flux in the combustion chamber of compression ignited reciprocating internal combustion engines was considered in more detail. A. Mityakov conducted an experiment, where Gradient Heat Flux Sensor was placed in four stroke diesel engine Indenor XL4D to measure heat flux in the combustion chamber. The results which were obtained from the experiment were compared with model’s numerical output. This model (a one – dimensional single zone model) was implemented with help of MathCAD and the result of this implementation is graph of heat flux in combustion chamber in relation to the crank angle. The values of heat flux throughout the cycle obtained with aid of heat flux sensor and theoretically were sufficiently similar, but not identical. Such deviation is rather common for this type of experiment.

Stochastic approximation methods in stochastic optimization

Stochastic approximation methods for stochastic optimization are considered. Reviewed the main methods of stochastic approximation: stochastic quasi-gradient algorithm, Kiefer-Wolfowitz algorithm and adaptive rules for them, simultaneous perturbation stochastic approximation (SPSA) algorithm. Suggested the model and the solution of the retailer's profit optimization problem and considered an application of the SQG-algorithm for the optimization problems with objective functions given in the form of ordinary differential equation.

The development of automated methods for the determination of trace concentrations of carbomate pesticides in water using solid sorbent pre-concentration methods and high performance liquid chromatography /

Several automated reversed-phase HPLC methods have been developed to determine trace concentrations of carbamate pesticides (which are of concern in Ontario environmental samples) in water by utilizing two solid sorbent extraction techniques. One of the methods is known as on-line pre-concentration'. This technique involves passing 100 milliliters of sample water through a 3 cm pre-column, packed with 5 micron ODS sorbent, at flow rates varying from 5-10 mUmin. By the use of a valve apparatus, the HPLC system is then switched to a gradient mobile phase program consisting of acetonitrile and water. The analytes, Propoxur, Carbofuran, Carbaryl, Propham, Captan, Chloropropham, Barban, and Butylate, which are pre-concentrated on the pre-column, are eluted and separated on a 25 cm C-8 analytical column and determined by UV absorption at 220 nm. The total analytical time is 60 minutes, and the pre-column can be used repeatedly for the analysis of as many as thirty samples. The method is highly sensitive as 100 percent of the analytes present in the sample can be injected into the HPLC. No breakthrough of any of the analytes was observed and the minimum detectable concentrations range from 10 to 480 ng/L. The developed method is totally automated for the analysis of one sample. When the above mobile phase is modified with a buffer solution, Aminocarb, Benomyl, and its degradation product, MBC, can also be detected along with the above pesticides with baseline resolution for all of the analytes. The method can also be easily modified to determine Benomyl and MBC both as solute and as particulate matter. By using a commercially available solid phase extraction cartridge, in lieu of a pre-column, for the extraction and concentration of analytes, a completely automated method has been developed with the aid of the Waters Millilab Workstation. Sample water is loaded at 10 mL/min through a cartridge and the concentrated analytes are eluted from the sorbent with acetonitrile. The resulting eluate is blown-down under nitrogen, made up to volume with water, and injected into the HPLC. The total analytical time is 90 minutes. Fifty percent of the analytes present in the sample can be injected into the HPLC, and recoveries for the above eight pesticides ranged from 84 to 93 percent. The minimum detectable concentrations range from 20 to 960 ng/L. The developed method is totally automated for the analysis of up to thirty consecutive samples. The method has proven to be applicable to both purer water samples as well as untreated lake water samples.