A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models

This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

Extraction of Caffeine from Energy Drinks

A simple procedure for the isolation of caffeine from energy drinks by solid phase extraction on a C18 cartridge. Quantitative analysis of the amount of caffeine by LC/MS is determined by referencing a standard curve.

Extraction and Clustering of Motion Trajectories in Video

A system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3D trajectories. The system then finds hierarchical clusters of similar trajectories in the video dataset. Objects' motion trajectories are extracted via an EKF formulation that provides each object's 3D trajectory up to a constant factor. To increase accuracy when occlusions occur, multiple tracking hypotheses are followed. For trajectory-based clustering and retrieval, a modified version of edit distance, called longest common subsequence (LCSS) is employed. Similarities are computed between projections of trajectories on coordinate axes. Trajectories are grouped based, using an agglomerative clustering algorithm. To check the validity of the approach, experiments using real data were performed.

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.

Rule Extraction, Fuzzy ARTMAP, and Medical Databases

This paper shows how knowledge, in the form of fuzzy rules, can be derived from a self-organizing supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning removes those recognition nodes whose confidence index falls below a selected threshold; and quantization of continuous learned weights allows the final system state to be translated into a usable set of rules. Simulations on a medical prediction problem, the Pima Indian Diabetes (PID) database, illustrate the method. In the simulations, pruned networks about 1/3 the size of the original actually show improved performance. Quantization yields comprehensible rules with only slight degradation in test set prediction performance.

Application of mesoporous silica for the oral delivery of poorly water-soluble drugs

The objective of this thesis was to improve the dissolution rate of the poorly waters-soluble drug, fenofibrate by processing it with a high surface area carrier, mesoporous silica. The subsequent properties of the drug – silica composite were studied in terms of drug distribution within the silica matrix, solid state and release properties. Prior to commencing any experimental work, the properties of unprocessed mesoporous silica and fenofibrate were characterised (chapter 3), this allowed for comparison with the processed samples studied in later chapters. Fenofibrate was a highly stable, crystalline drug that did not adsorb moisture, even under long term accelerated storage conditions. It maintained its crystallinity even after SC-CO2 processing. Its dissolution rate was limited and dependent on the characteristics of the particular in vitro media studied. Mesoporous silica had a large surface area and mesopore volume and readily picked up moisture when stored under long term accelerated storage conditions (75% RH, 40 oC). It maintained its mesopore character after SC-CO2 processing. A variety of methods were employed to process fenofibrate with mesoporous silica including physical mixing, melt method, solvent impregnation and novel methods such as liquid and supercritical carbon dioxide (SC-CO2) (chapter 4). It was found that it was important to break down the fenofibrate particulate structure to a molecular state to enable drug molecules enter into the silica mesopores. While all processing methods led to some increase in fenofibrate release properties; the impregnation, liquid and SC-CO2 methods produced the most rapid release rates. SC-CO2 processing was further studied with a view to optimising the processing parameters to achieve the highest drug-loading efficiency possible (chapter 5). In this thesis, it was that SC-CO2 processing pressure had a bearing on drug-loading efficiency. Neither pressure, duration or depressurisation rate affected drug solid state or release properties. The amount of drug that could be loaded onto to the mesoporous silica successfully was also investigated at different ratios of drug mass to silica surface area under constant SC-CO2 conditions; as the drug – silica ratio increased, the drug-loading efficiency decreased, while there was no effect on drug solid state or release properties. The influence of the number of drug-loading steps was investigated (chapter 6) with a view to increasing the drug-loading efficiency. This multiple step approach did not yield an increase in drug-loading efficiency compared to the single step approach. It was also an objective in this chapter to understand how much drug could be loaded into silica mesopores; a method based on the known volume of the mesopores and true density of drug was investigated. However, this approach led to serious repercussions in terms of the subsequent solid state nature of the drug and its release performance; there was significant drug crystallinity and reduced release extent. The impact of in vitro release media on fenofibrate release was also studied (chapter 6). Here it was seen that media containing HCl led to reduced drug release over time compared to equivalent media not containing HCl. The key findings of this thesis are discussed in chapter 7 and included: 1. Drug – silica processing method strongly influenced drug distribution within the silica matrix, drug solid state and release. 2. The silica surface area and mesopore volume also influenced how much drug could be loaded. It was shown that SC-CO2 processing variables such as processing pressure (13.79 – 41.37 MPa), duration time (4 – 24 h) and depressurisation rate (rapid or controlled) did not influence the drug distribution within the SBA- 15 matrix, drug solid state form or release. Possible avenues of research to be considered going forward include the development and application of high resolution imaging techniques to visualise drug molecules within the silica mesopores. Also, the issues surrounding SBA-15 usage in a pharmaceutical manufacturing environment should be addressed.

Silica bonded stationary phases: Innovative functionalization methods and novel chromatographic separations based on molecular recognition

The research work included in this thesis examines the synthesis, characterization and chromatographic evaluation of novel bonded silica stationary phases. Innovative methods of preparation of silica hydride intermediates and octadecylsilica using a “green chemistry” approach eliminate the use of toxic organic solvents and exploit the solvating power and enhanced diffusivity of supercritical carbon dioxide to produce phases with a surface coverage of bonded ligands which is comparable to, or exceeds, that achieved using traditional organic solvent-based methods. A new stationary phase is also discussed which displays chromatographic selectivity based on molecular recognition. Chapter 1 introduces the chemistry of silica stationary phases, the retention mechanisms and theories on which reversed-phase liquid chromatography and hydrophilic interaction chromatograpy are based, the art and science of achieving a well packed liquid chromatography column, the properties of supercritical carbon dioxide and molecular recognition chemistry. Chapter 2 compares the properties of silica hydride materials prepared using supercritical carbon dioxide as the reaction medium with those synthesized in an organic solvent. A higher coverage of hydride groups on the silica surface is seen when a monofunctional silane is reacted in supercritical carbon dioxide while trifunctional silanes result in a phase which exhibits different properties depending on the reaction medium used. The differing chromatographic behaviour of these silica hydride materials prepared using supercritical carbon dioxide and using organic solvent are explored in chapter 3. Chapter 4 focusses on the preparation of octadecylsilica using mono-, di- and trifunctional alkoxysilanes in supercritical carbon dioxide and in anhydrous toluene. The surface coverage of octadecyl groups, as calculated using thermogravimetric analysis and elemental analysis, is highest when a trifunctional alkoxysilane is reacted with silica in supercritical carbon dioxide. A novel silica stationary phase is discussed in chapter 5 which displays selectivity for analytes based on their hydrogen bonding capabilities. The phase is also highly selective for barbituric acid and may have a future application in the solid phase extraction of barbiturates from biological samples.

Novel co-crystals of the nutraceutical sinapic acid

Sinapic acid (SA) is a nutraceutical with known anti-oxidant, anti-microbial, anti-inflammatory, anti-cancer, and anti-anxiety properties. Novel co-crystals of SA were prepared with co-formers belonging to the category of GRAS [isonicotinic acid (INC), nicotinamide (NIA)], non-GRAS [4-pyridinecarbonitrile (PYC)], and active pharmaceutical ingredients (APIs) [6-propyl-2-thiouracil (PTU)] list of compounds. Structural study based on the X-ray crystal structures revealed the intermolecular hydrogen-bonded interactions and molecular packing. The crystal structure of sinapic acid shows the anticipated acid-acid homodimer along with discrete hydrogen bonds between the acid carbonyl and the phenolic moiety. The robust acid-acid homodimer appears to be very stable and is retained in the structures of two co-crystals (SA[middle dot]NIA and SA[middle dot]PYC). In these cases, co-crystallization occurs via intermolecular phenol O-H[three dots, centered]Naromatic hydrogen bonds between the co-formers. In the SA[middle dot]PTU[middle dot]2MeCN co-crystal the acid-acid homodimer gives way to the anticipated acid-amide heterodimer, with the phenolic moiety of SA hydrogen-bonded to acetonitrile. Attempts at obtaining the desolvated co-crystal led to lattice breakdown, thus highlighting the importance of acetonitrile in the formation of the co-crystal. Among the co-crystals examined, SA[middle dot]INC (5 weeks), SA[middle dot]NIA (8 weeks) and SA[middle dot]PYC (5 weeks) were found to be stable under accelerated humidity conditions (40 [degree]C, 75% RH), whereas SA[middle dot]PTU[middle dot]2MeCN decomposed after one week into individual components due to solvent loss.

Short-lived alpha-helical intermediates in the folding of beta-sheet proteins.

Several lines of evidence point strongly toward the importance of highly alpha-helical intermediates in the folding of all globular proteins, regardless of their native structure. However, experimental refolding studies demonstrate no observable alpha-helical intermediate during refolding of some beta-sheet proteins and have dampened enthusiasm for this model of protein folding. In this study, beta-sheet proteins were hypothesized to have potential to form amphiphilic helices at a period of <3.6 residues/turn that matches or exceeds the potential at 3.6 residues/turn. Hypothetically, such potential is the basis for an effective and unidirectional mechanism by which highly alpha-helical intermediates might be rapidly disassembled during folding and potentially accounts for the difficulty in detecting highly alpha-helical intermediates during the folding of some proteins. The presence of this potential was confirmed, indicating that a model entailing ubiquitous formation of alpha-helical intermediates during the folding of globular proteins predicts previously unrecognized features of primary structure. Further, the folding of fatty acid binding protein, a predominantly beta-sheet protein that exhibits no apparent highly alpha-helical intermediate during folding, was dramatically accelerated by 2,2,2-trifluoroethanol, a solvent that stabilizes alpha-helical structure. This observation suggests that formation of an alpha-helix can be a rate-limiting step during folding of a predominantly beta-sheet protein and further supports the role of highly alpha-helical intermediates in the folding of all globular proteins.

Elucidating solvent contributions to solution reactions with ab initio QM/MM methods.

Computer simulations of reaction processes in solution in general rely on the definition of a reaction coordinate and the determination of the thermodynamic changes of the system along the reaction coordinate. The reaction coordinate often is constituted of characteristic geometrical properties of the reactive solute species, while the contributions of solvent molecules are implicitly included in the thermodynamics of the solute degrees of freedoms. However, solvent dynamics can provide the driving force for the reaction process, and in such cases explicit description of the solvent contribution in the free energy of the reaction process becomes necessary. We report here a method that can be used to analyze the solvent contributions to the reaction activation free energies from the combined QM/MM minimum free-energy path simulations. The method was applied to the self-exchange S(N)2 reaction of CH(3)Cl + Cl(-), showing that the importance of solvent-solute interactions to the reaction process. The results were further discussed in the context of coupling between solvent and solute molecules in reaction processes.

Phase transfer catalysts drive diverse organic solvent solubility of single-walled carbon nanotubes helically wrapped by ionic, semiconducting polymers.

Use of phase transfer catalysts such as 18-crown-6 enables ionic, linear conjugated poly[2,6-{1,5-bis(3-propoxysulfonicacidsodiumsalt)}naphthylene]ethynylene (PNES) to efficiently disperse single-walled carbon nanotubes (SWNTs) in multiple organic solvents under standard ultrasonication methods. Steady-state electronic absorption spectroscopy, atomic force microscopy (AFM), and transmission electron microscopy (TEM) reveal that these SWNT suspensions are composed almost exclusively of individualized tubes. High-resolution TEM and AFM data show that the interaction of PNES with SWNTs in both protic and aprotic organic solvents provides a self-assembled superstructure in which a PNES monolayer helically wraps the nanotube surface with periodic and constant morphology (observed helical pitch length = 10 ± 2 nm); time-dependent examination of these suspensions indicates that these structures persist in solution over periods that span at least several months. Pump-probe transient absorption spectroscopy reveals that the excited state lifetimes and exciton binding energies of these well-defined nanotube-semiconducting polymer hybrid structures remain unchanged relative to analogous benchmark data acquired previously for standard sodium dodecylsulfate (SDS)-SWNT suspensions, regardless of solvent. These results demonstrate that the use of phase transfer catalysts with ionic semiconducting polymers that helically wrap SWNTs provide well-defined structures that solubulize SWNTs in a wide range of organic solvents while preserving critical nanotube semiconducting and conducting properties.

3D refraction correction and extraction of clinical parameters from spectral domain optical coherence tomography of the cornea.

Capable of three-dimensional imaging of the cornea with micrometer-scale resolution, spectral domain-optical coherence tomography (SDOCT) offers potential advantages over Placido ring and Scheimpflug photography based systems for accurate extraction of quantitative keratometric parameters. In this work, an SDOCT scanning protocol and motion correction algorithm were implemented to minimize the effects of patient motion during data acquisition. Procedures are described for correction of image data artifacts resulting from 3D refraction of SDOCT light in the cornea and from non-idealities of the scanning system geometry performed as a pre-requisite for accurate parameter extraction. Zernike polynomial 3D reconstruction and a recursive half searching algorithm (RHSA) were implemented to extract clinical keratometric parameters including anterior and posterior radii of curvature, central cornea optical power, central corneal thickness, and thickness maps of the cornea. Accuracy and repeatability of the extracted parameters obtained using a commercial 859nm SDOCT retinal imaging system with a corneal adapter were assessed using a rigid gas permeable (RGP) contact lens as a phantom target. Extraction of these parameters was performed in vivo in 3 patients and compared to commercial Placido topography and Scheimpflug photography systems. The repeatability of SDOCT central corneal power measured in vivo was 0.18 Diopters, and the difference observed between the systems averaged 0.1 Diopters between SDOCT and Scheimpflug photography, and 0.6 Diopters between SDOCT and Placido topography.

Analysis of ocean power extraction capabilites of a rotary wave energy conversion system

Gemstone Team WAVES (Water and Versatile Energy Systems)

Extraction of polydispersity information from photon correlation data

Photon correlation spectroscopy (PCS) is a light-scattering technique for particle size diagnosis. It has been used mainly in the investigation of hydrosol particles since it is based on the measurement of the correlation function of the light scattered from the Brownian motion of suspended particles. Recently this technique also proved useful for studying soot particles in flames and similar aerosol systems. In the case of a polydispersed system the problem of recovering the particle size distribution can be reduced to the problem of inverting the Laplace transform. In this paper we review several methods introduced by the authors for the solution of this problem. We present some numerical results and we discuss the resolution limits characterizing the reconstruction of the size distributions. © 1989.

Extraction of polydispersity information in photon correlation spectroscopy

info:eu-repo/semantics/published