Relevant bibliographies by topics / Analytical fingerprint

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Academic literature on the topic 'Analytical fingerprint'

Author: Grafiati
Published: 3 June 2023

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Journal articles on the topic "Analytical fingerprint"

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Kirfel, Alexander, Tobias Scheer, Norbert Jung, and Christoph Busch. "Robust Identification and Segmentation of the Outer Skin Layers in Volumetric Fingerprint Data." Sensors 22, no. 21 (October 27, 2022): 8229. http://dx.doi.org/10.3390/s22218229.

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Despite the long history of fingerprint biometrics and its use to authenticate individuals, there are still some unsolved challenges with fingerprint acquisition and presentation attack detection (PAD). Currently available commercial fingerprint capture devices struggle with non-ideal skin conditions, including soft skin in infants. They are also susceptible to presentation attacks, which limits their applicability in unsupervised scenarios such as border control. Optical coherence tomography (OCT) could be a promising solution to these problems. In this work, we propose a digital signal processing chain for segmenting two complementary fingerprints from the same OCT fingertip scan: One fingerprint is captured as usual from the epidermis (“outer fingerprint”), whereas the other is taken from inside the skin, at the junction between the epidermis and the underlying dermis (“inner fingerprint”). The resulting 3D fingerprints are then converted to a conventional 2D grayscale representation from which minutiae points can be extracted using existing methods. Our approach is device-independent and has been proven to work with two different time domain OCT scanners. Using efficient GPGPU computing, it took less than a second to process an entire gigabyte of OCT data. To validate the results, we captured OCT fingerprints of 130 individual fingers and compared them with conventional 2D fingerprints of the same fingers. We found that both the outer and inner OCT fingerprints were backward compatible with conventional 2D fingerprints, with the inner fingerprint generally being less damaged and, therefore, more reliable.
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Alotaibi, Ashwaq, Muhammad Hussain, Hatim AboAlSamh, Wadood Abdul, and George Bebis. "Cross-Sensor Fingerprint Enhancement Using Adversarial Learning and Edge Loss." Sensors 22, no. 18 (September 15, 2022): 6973. http://dx.doi.org/10.3390/s22186973.

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A fingerprint sensor interoperability problem, or a cross-sensor matching problem, occurs when one type of sensor is used for enrolment and a different type for matching. Fingerprints captured for the same person using various sensor technologies have various types of noises and artifacts. This problem motivated us to develop an algorithm that can enhance fingerprints captured using different types of sensors and touch technologies. Inspired by the success of deep learning in various computer vision tasks, we formulate this problem as an image-to-image transformation designed using a deep encoder–decoder model. It is trained using two learning frameworks, i.e., conventional learning and adversarial learning based on a conditional Generative Adversarial Network (cGAN) framework. Since different types of edges form the ridge patterns in fingerprints, we employed edge loss to train the model for effective fingerprint enhancement. The designed method was evaluated on fingerprints from two benchmark cross-sensor fingerprint datasets, i.e., MOLF and FingerPass. To assess the quality of enhanced fingerprints, we employed two standard metrics commonly used: NBIS Fingerprint Image Quality (NFIQ) and Structural Similarity Index Metric (SSIM). In addition, we proposed a metric named Fingerprint Quality Enhancement Index (FQEI) for comprehensive evaluation of fingerprint enhancement algorithms. Effective fingerprint quality enhancement results were achieved regardless of the sensor type used, where this issue was not investigated in the related literature before. The results indicate that the proposed method outperforms the state-of-the-art methods.
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Sun, Jie, Fang Tian, Ying Zhang, Menghua Wu, Runqian Mao, Zhiyong Le, Dongjin Xu, Hui Cao, and Zhiguo Ma. "Chromatographic Fingerprint and Quantitative Analysis of CommercialPheretima aspergillum(Guang Dilong) and Its Adulterants by UPLC-DAD." International Journal of Analytical Chemistry 2019 (January 9, 2019): 1–10. http://dx.doi.org/10.1155/2019/4531092.

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Guang Dilong is a Traditional Chinese Medicine prepared from the dried body ofPheretima aspergillum(E. Perrier), a species of earthworm. However, preparations of Guang Dilong may be adulterated by other species and a method of quality control is needed. A method was developed to analyze and authenticate commercial Guang Dilong, utilizing ultra-high performance liquid chromatography (UHPLC) coupled with diode array detection (DAD). Equipment included an Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm). The mobile phase consisted of acetonitrile and 0.01% formic acid, pumped at 0.3 mL/min. Wavelength detection was at 260 nm. Twenty-two batches of confirmedP. aspergillumsamples (reference) from different sources and 20 batches of adulterated samples were analyzed to establish a reference fingerprint for commercial Guang Dilong. Five peaks in the fingerprints of the reference batches were identified as characteristic; six characteristic peaks in the fingerprints of the adulterants were identified by comparing their retention time with those of the references. The total 42 batches of samples were compared with the reference fingerprint, and the fingerprints of theP. aspergillumsamples were similar. The UHPLC-DAD method can simultaneously determine the contents of six compounds (hypoxanthine, xanthine, uridine, inosine, guanosine, and adenosine) in the reference and adulterated batches. The six compounds showed good regression (r> 0.9999) within test ranges. The recovery (accuracy) was 98.25 to 101.68%, with relative standard deviation <2.67%. In summary, this UHPLC-DAD method combines chromatographic fingerprint with quantification analysis and could be readily used as an efficient quality control method for Guang Dilong.
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Zhang, Huiqing, and Yueqing Li. "LightGBM Indoor Positioning Method Based on Merged Wi-Fi and Image Fingerprints." Sensors 21, no. 11 (May 25, 2021): 3662. http://dx.doi.org/10.3390/s21113662.

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Smartphones are increasingly becoming an efficient platform for solving indoor positioning problems. Fingerprint-based positioning methods are popular because of the wide deployment of wireless local area networks in indoor environments and the lack of model propagation paths. However, Wi-Fi fingerprint information is singular, and its positioning accuracy is typically 2–10 m; thus, it struggles to meet the requirements of high-precision indoor positioning. Therefore, this paper proposes a positioning algorithm that combines Wi-Fi fingerprints and visual information to generate fingerprints. The algorithm involves two steps: merged-fingerprint generation and fingerprint positioning. In the merged-fingerprint generation stage, the kernel principal component analysis feature of the Wi-Fi fingerprint and the local binary pattern features of the scene image are fused. In the fingerprint positioning stage, a light gradient boosting machine (LightGBM) is trained with mutually exclusive feature bundling and histogram optimization to obtain an accurate positioning model. The method is tested in an actual environment. The experimental results show that the positioning accuracy of the LightGBM method is 90% within a range of 1.53 m. Compared with the single-fingerprint positioning method, the accuracy is improved by more than 20%, and the performance is improved by more than 15% compared with other methods. The average locating error is 0.78 m.
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Gäbler, Hans-Eike, Wilhelm Schink, Simon Goldmann, Andreas Bahr, and Timo Gawronski. "Analytical Fingerprint of Wolframite Ore Concentrates." Journal of Forensic Sciences 62, no. 4 (June 6, 2017): 881–88. http://dx.doi.org/10.1111/1556-4029.13373.

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Qiao, Yan-Ling, Ying-Hao Zhang, Wei Zhang, and Jin-Lan Zhang. "A Rapid Resolution Liquid Chromatographic Method for Fingerprint Analysis of Raw and Processed Caowu (Aconitum kusnezoffii)." Journal of AOAC INTERNATIONAL 92, no. 2 (March 1, 2009): 653–62. http://dx.doi.org/10.1093/jaoac/92.2.653.

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Abstract A sensitive and reliable rapid resolution liquid chromatographic (RRLC) method coupled with diode array detection has been developed for the fingerprint analysis of raw and processed caowu (Aconitum kusnezoffii). The RRLC fingerprints were established with a Zorbax Extend C18 analytical column (4.6 50 mm, 1.8 m) and gradient elution. Analysis run time was &lt;10 min. The method displayed good precision, stability, and repeatability in fingerprint analysis. Characteristic RRLC fingerprints of caowu were generated and used to assess the consistency and differences in the products. Raw and processed caowu from different sources were analyzed under the developed RRLC conditions, yielding contrasting RRLC fingerprints. Comparison of the RRLC fingerprints of processed and raw caowu indicated that the major constituents changed during processing. Meanwhile, a peak area ratio analysis method was applied to assess their chromatographic fingerprints. In characterizing the constituents of caowu, 11 major chromatographic peaks were identified by mass spectrometry and compared with reference standards and reference data. In summary, RRLC fingerprinting is a rapid and useful way to evaluate the quality of raw and processed caowu.
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Kokkinis, Akis, Loizos Kanaris, Antonio Liotta, and Stavros Stavrou. "RSS Indoor Localization Based on a Single Access Point." Sensors 19, no. 17 (August 27, 2019): 3711. http://dx.doi.org/10.3390/s19173711.

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This research work investigates how RSS information fusion from a single, multi-antenna access point (AP) can be used to perform device localization in indoor RSS based localization systems. The proposed approach demonstrates that different RSS values can be obtained by carefully modifying each AP antenna orientation and polarization, allowing the generation of unique, low correlation fingerprints, for the area of interest. Each AP antenna can be used to generate a set of fingerprint radiomaps for different antenna orientations and/or polarization. The RSS fingerprints generated from all antennas of the single AP can be then combined to create a multi-layer fingerprint radiomap. In order to select the optimum fingerprint layers in the multilayer radiomap the proposed methodology evaluates the obtained localization accuracy, for each fingerprint radio map combination, for various well-known deterministic and probabilistic algorithms (Weighted k-Nearest-Neighbor—WKNN and Minimum Mean Square Error—MMSE). The optimum candidate multi-layer radiomap is then examined by calculating the correlation level of each fingerprint pair by using the “Tolerance Based—Normal Probability Distribution (TBNPD)” algorithm. Both steps take place during the offline phase, and it is demonstrated that this approach results in selecting the optimum multi-layer fingerprint radiomap combination. The proposed approach can be used to provide localisation services in areas served only by a single AP.
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Liu, Zhenyu, Bin Dai, Xiang Wan, and Xueyi Li. "Hybrid Wireless Fingerprint Indoor Localization Method Based on a Convolutional Neural Network." Sensors 19, no. 20 (October 22, 2019): 4597. http://dx.doi.org/10.3390/s19204597.

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In the indoor location field, the quality of received-signal-strength-indicator (RSSI) fingerprints plays a key role in the performance of indoor location services. However, changes in an indoor environment may lead to the decline of location accuracy. This paper presents a localization method employing a Hybrid Wireless fingerprint (HW-fingerprint) based on a convolutional neural network (CNN). In the proposed scheme, the Ratio fingerprint was constructed by calculating the ratio of different RSSIs from important contribution access points (APs). The HW-fingerprint combined the Ratio fingerprint and the RSSI to enhance the expression of indoor environment characteristics. Moreover, a CNN architecture was constructed to learn important features from the complex HW-fingerprint for indoor locations. In the experiment, the HW-fingerprint was tested in an actual indoor scene for 15 days. Results showed that the average daily location accuracy of the K-Nearest Neighbor (KNN), Support Vector Machines (SVMs), and CNN was improved by 3.39%, 8.03% and 9.03%, respectively, when using the HW-fingerprint. In addition, the deep-learning method was 4.19% and 16.37% higher than SVM and KNN in average daily location accuracy, respectively.
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Li, Zhuojun, Cui Wu, Bo Xu, Huijun Wang, Pingping Song, Zhenying Liu, and Zhimao Chao. "Gender Discrimination of Flower Buds of Mature Populus tomentosa by HPLC Fingerprint Combined with Chemometrics." International Journal of Analytical Chemistry 2022 (September 29, 2022): 1–10. http://dx.doi.org/10.1155/2022/1281521.

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A high performance liquid chromatography-diode array detector (HPLC-DAD) was used to establish the HPLC fingerprint. Chemometrics methods were used to discriminate against the gender of flower buds of Populus tomentosa based on areas of common peaks calibrated with the HPLC fingerprint. The score plot of principal component analysis (PCA) showed a clear grouping trend (R2X, 0.753; Q2, 0.564) between female and male samples. Two groups were also well discriminated with orthogonal partial least squares-discriminant analysis (OPLS-DA) (R2X, 0.741; R2Y, 0.980; Q2, 0.970). As the hierarchical clustering analysis (HCA) heatmap showed, all samples were separated into two groups. Four compounds were screened out by S-plot and variable importance in projection (VIP > 1.0). Two of them were identified as siebolside B and tremulacin. This study demonstrated that HPLC fingerprints combined with chemometrics can be applied to discriminate against dioecious plants and screen differences, providing a reference for identifying the gender of dioecious plants.
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Grant, Ashleigh, T. J. Wilkinson, Derek R. Holman, and Michael C. Martin. "Identification of Recently Handled Materials by Analysis of Latent Human Fingerprints Using Infrared Spectromicroscopy." Applied Spectroscopy 59, no. 9 (September 2005): 1182–87. http://dx.doi.org/10.1366/0003702055012618.

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Analysis of fingerprints has predominantly focused on matching the pattern of ridges to a specific person as a form of identification. The present work focuses on identifying extrinsic materials that are left within a person's fingerprint after recent handling of such materials. Specifically, we employed infrared spectromicroscopy to locate and positively identify microscopic particles from a mixture of common materials in the latent human fingerprints of volunteer subjects. We were able to find and correctly identify all test substances based on their unique infrared spectral signatures. Spectral imaging is demonstrated as a method for automating recognition of specific substances in a fingerprint. We also demonstrate the use of attenuated total reflectance (ATR) and synchrotron-based infrared spectromicroscopy for obtaining high-quality spectra from particles that were too thick or too small, respectively, for reflection/absorption measurements. We believe the application of this rapid, nondestructive analytical technique to the forensic study of latent human fingerprints has the potential to add a new layer of information available to investigators. Using fingerprints to not only identify who was present at a crime scene, but also to link who was handling key materials, will be a powerful investigative tool.
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Dissertations / Theses on the topic "Analytical fingerprint"

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Goldmann, Simon [Verfasser]. "Mineralogical-geochemical characterisation of cassiterite and wolframite ores for an analytical fingerprint / Simon Goldmann." Hannover : Technische Informationsbibliothek (TIB), 2016. http://d-nb.info/1170364144/34.

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Radspinner, David Andrew 1965. "Developments in atomic analysis and imaging utilizing scientific charge-transfer devices: Axial viewing of the inductively coupled plasma, advanced hollow cathode designs, and latent fingerprint imaging." Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/282524.

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This document describes the development of spectroscopic techniques which benefit from the use of charge-transfer devices. Both charge-coupled devices (CCD's) and charge-injection devices (CID's) are used in the techniques presented here such as atomic emission spectroscopy and latent fingerprint imaging. The use of a CID echelle system for axial viewing of the inductively coupled plasma (ICP) demonstrates the enhancement in sensitivity that can be obtained over tangential viewing. More importantly though, are the advantages afforded by simultaneous multi-element detection. Axial viewing of the ICP has shown to not only improve upon the detection limits of several metals by, in some cases, a half order of magnitude, but also to increase the amount of light collected and thus reduce the time of analysis. Along with this, the effect of interferences upon the detection of various metals is, at worst, equivalent to that of an ICP with tangential viewing. Further enhancement of sensitivity in atomic analysis can be achieved by atomic fluorescence with an ICP. Although in the past, hollow cathode lamps have proven to be insufficient, advanced designs of hollow cathode lamps presented here have demonstrated an increase in the intensity of lines of copper best suited for use in ICP atomic fluorescence. Lastly, a latent fingerprint has been imaged with the use of a scientific CCD and a flashlight where in the past such a technique was accomplished with high power lasers. By using a CCD, the immediate digitization of information combined with the sensitivity and image processing capabilities offer a portable means by which to image latent fingerprints on poor surfaces.
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Yang, Kundi. "Assessing and Evaluating Biomarkers and Chemical Markers by Targeted and Untargeted Mass Spectrometry-based Metabolomics." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1605044640528563.

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Radović, Jagoš. "Comprehensive analytical approaches to determine the sources, fate and effects of marine oil spills." Doctoral thesis, Universitat de Barcelona, 2014. http://hdl.handle.net/10803/283088.

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In the past two decades we witnessed a decrease in both the number of oil spill incidents, and of the quantity of oil released in these incidents, which led to a diminished interest for basic oil spill science. With the introduction of more stringent oil spill legislation, much of the spill response, assessment and restoration activities were passed to governmental agencies and other stakeholders. Their capabilities were perhaps sufficient to deal with the most frequently occurring small-scale spills, however, recent large, catastrophic incidents such as the sinking of Prestige in 2002, or the Deepwater Horizon blowout in 2010, renewed the need for fundamental science in order to be able to fully understand and estimate the scope of the impacts such spills can have on the environment, economy and society. This is particularly important in the context of new explorations and discoveries of hydrocarbon resources in pristine regions such as Arctic, where extreme weather and the lack of infrastructure emphasize even more the need for a comprehensive assessment of all of the possible effects the future oil production could cause. The objectives of this thesis were set to provide new approaches and methodologies, and to improve and reevaluate the previously existing ones, in a way which can contribute to this comprehensive and proactive strategy. Their scope is comprehensive because it covers all the important aspects of marine oil spills – the sources, environmental fate and possible toxic effects. In addition, particular relevance of this thesis is drawn from the fact that the studies presented here include the investigation of real major oil spills (Prestige, DWH), and of a broad range of oils and oil products that are currently produced and transported worldwide. In order to fulfill the abovementioned general objectives, the following specific objectives had to be accomplished: Firstly, a physicochemical database of frequently transported crude and refined oils was created using elemental analysis, thin-layer liquid chromatography (TLC) with flame ionization detector (FID) analysis of principal oil compound groups, gas chromatography-mass spectrometry (GC-MS) fingerprinting of polycyclic aromatic hydrocarbons (PAHs) and biomarkers, and available oil assays. This database was then applied to assess their possible fate in the case of a spill, and to model three spill scenarios in different European regional seas using ADIOS2 software from NOAA (National Oceanic and Atmospheric Administration). Fingerprints of selected oils were assessed and statistically compared to discover the most relevant compositional differences that could facilitate the identification of oil spill sources. Secondly, the GC-MS methodology used to create the fingerprint database of selected oils was evaluated in an international interlaboratory ring test. The objective was to test the capability of this fingerprinting methodology to identify the type and source of weathered (biodegraded) oil samples. Thirdly, the weathering of oil samples from Prestige and Deepwater Horizon spills, in particular the photooxidation, was studied. Samples weathered in field and in laboratory experiments were analyzed using TLC-FID, GC-MS, comprehensive two dimensional gas chromatography (GCxGC) with FID, and Fourier transform infrared spectrometry (FT-IR) to discover compositional changes on the bulk level as well as on the molecular level. PAHs and triaromatic steranes (TAS) were of particular interest, as well as the effects of the photooxidation on the robustness of the oil fingerprinting methodology. Finally, the effects of selected fresh and weathered (evaporated, photooxidized) crude and refined oils were studied, using the effect-directed analysis (EDA). The samples were sequentially fractionated using open-column liquid chromatography and normal-phase semipreparative HPLC, and the obtained fractions were subjected to bioassays to test their AhR agonist and AR antagonist activity. The most active fractions were then analyzed using GCxGC coupled to time-of-flight mass spectrometry (TOFMS), and this data was related to bioassay results using N-way partial least square (N-PLS) chemometric model, in order to identify the compounds responsible for the observed effects.
A pesar de las tendencias positivas en las últimas décadas, los vertidos ocasionados por la exploración, extracción y transporte de petróleo siguen siendo una importante amenaza para los ecosistemas marinos y especialmente costeros. Esta Tesis se ocupa de todos los aspectos importantes sobre los vertidos marinos de petróleo: el origen, el destino ambiental y sus posibles efectos. Para permitir su comprensión global, se utilizaron diferentes metodologías complementarias. En primer lugar, se ha creado una base de datos físico-químicos de diferentes petróleos (crudos y refinados) que se transportan frecuentemente usando el análisis elemental, la cromatografía en capa fina (TLC) acoplada a un detector de ionización de llama (FID) de los principales grupos de compuestos de petróleo, la toma de huellas químicas de los hidrocarburos aromáticos policíclicos (HAP) y los biomarcadores mediante cromatografía de gases acoplada a espectrometría de masas (GC-MS), y ensayos de petróleo disponibles. A continuación, se aplicó esta base de datos para evaluar su posible destino en el caso de un vertido, y para modelar tres escenarios de vertidos en diferentes mares regionales europeos usando el software ADIOS2 de la Administración Nacional Oceánica y Atmosférica (NOAA). Las huellas químicas de los petróleos seleccionados fueron evaluadas y comparadas estadísticamente para investigar las diferencias de composición más relevantes que podrían facilitar la identificación del origen de vertido. En segundo lugar, la metodología de GC-MS utilizada para crear la base de datos de las huellas químicas de los petróleos seleccionados se ha evaluado en una prueba interlaboratorio internacional. El objetivo fue investigar la capacidad que tiene esta metodología de toma de huellas químicas para identificar el tipo y el origen de las muestras envejecidas (biodegradadas) de petróleo. En tercer lugar, se ha estudiado el envejecimiento de las muestras de petróleo de los vertidos de Prestige (2002) y de la plataforma Deepwater Horizon (2010), en particular, debido a la fotooxidación. Se analizaron muestras envejecidas en el campo y en experimentos de laboratorio mediante TLC-FID, GCMS, cromatografía de gases bidimensional integrada (GCxGC) acoplada a un FID, y espectroscopia infrarroja por transformada de Fourier (FT-IR) para investigar los cambios de composición tanto a nivel global como a nivel molecular. Los HAP y esteranos triaromáticos fueron de especial interés, así como los efectos de la fotooxidación en la robustez de la metodología de toma de huellas químicas de petróleo. Finalmente, se estudiaron los efectos de las muestras no tratadas y envejecidas (evaporadas, fotooxidadas) de los petróleos crudos y refinados seleccionados, utilizando el análisis dirigido por los efectos tóxicos (EDA). Las muestras se fraccionaron secuencialmente usando la cromatografía líquida en columna abierta y la cromatografía líquida de alta eficacia (HPLC) semipreparativa en fase normal. Las fracciones obtenidas se sometieron a bioensayos para investigar su actividad agonista de los receptores AhR y la actividad antagonista de los receptores AR. En el siguiente paso, las fracciones más activas fueron analizadas mediante GCxGC acoplada a espectrometría de masas en tiempo de vuelo (TOFMS), y estos datos se relacionaron con los resultados de los bioensayos utilizando un modelo quimiométrico de regresión por mínimos cuadrados parciales en N direcciones (N-PLS), con el fin de identificar los compuestos responsables de los efectos observados.
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Kassouf, Amine. "Sécurité sanitaire des denrées au contact de matériau d'emballage : proposition d'une démarche méthodologique." Electronic Thesis or Diss., Paris, AgroParisTech, 2015. http://www.theses.fr/2015AGPT0006.

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L’aptitude des matériaux plastiques au contact alimentaire (FCMs) et le besoin de les évaluer selon les règlementations en vigueur, nécessitent une meilleure connaissance de leur composition et de leurs phénomènes d’interaction avec les denrées alimentaires au contact. Inspiré des approches globales appliquées en métabolomique, le traitement d’empreintes spectrales et chromatographiques par des méthodes chimiométriques constitue une approche prometteuse en chimie analytique. Nous avons utilisé cette approche pour l’évaluation de la sécurité sanitaire des FCMs par la spectrométrie moyen-infrarouge (MIR), les chromatographies en phases gazeuse et liquide couplées à la spectrométrie de masse (GC-MS et LC-MS) et la fluorescence frontale 3D, couplées à des outils chimiométriques innovants, en particulier l’analyse en composantes indépendantes (ICA). Les traitements chimiométriques ont permis d’extraire l’information pertinente concernant la composition de ces matériaux pour les molécules intentionnellement ajoutées (IAS), figurant dans le règlement UE Nº10/2011, mais également pour des molécules non-intentionnellement ajoutées issues de réactivité et de contaminations. Ceci a été montré en particulier pour le suivi du procédé de mise en forme des bouteilles de polyéthylène téréphtalate ainsi que pour la quantification des plastifiants du polylactide. Par ailleurs, ces méthodologies analytiques non-ciblées ont permis la mise en évidence de la réactivité de molécules migrantes à partir des FCMs vers des milieux complexes tels que l’huile d’olive. Le champ d’application des approches développées ne se limite pas à l’étude de la sécurité sanitaire des FCMs et des aliments en contact. Ainsi, une approche par MIR couplée à l’ICA nous a permis d’assurer une séparation efficace entre les principales familles de matériaux d’emballages plastiques, en vue de leur recyclage
Compliance of plastic food contact materials (FCMs) with current legal specifications requires a better knowledge of their composition as well as their interaction phenomena with food in contact. Inspired by non-hypothesis driven metabolomics approaches, mining useful information in spectral and chromatographic fingerprints such as those generated by mid-infrared spectroscopy (MIR), gas and liquid chromatography coupled to mass spectrometry (GCMS and LC-MS) and 3D front face fluorescence spectroscopy, is becoming a key step in recent advancements in analytical chemistry, which we applied for the safety evaluation of FCMs. Innovative chemometric tools were used especially independent components analysis (ICA). In fact, the developed analytical approaches, that combine analytical fingerprints with chemometrics, helped to extract relevant information about the composition of these materials, such as intentionally added substances, listed in the EU regulations Nº10/2011, and also unknown molecules resulting from chemical reactivity and contamination. This approach was validated in particular for monitoring polyethylene terephthalate bottles manufacturing process as well as for the quantification of plasticizers in polylactide. Moreover, the proposed non-targeted methodologies proved their efficiency in highlighting the reactivity of migrating compounds from FCMs into complex foodstuffs such as olive oils. The scope of the developed approaches is not limited to the study of FCMs safety. The combination of MIR fingerprints with ICA allowed us to ensure an effective separation of the main plastic packaging materials. This approach could easily find applications in the sorting of plastic wastes prior to recycling
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Bäckström, Daniel. "Managing and Exploring Large Data Sets Generated by Liquid Separation - Mass Spectrometry." Doctoral thesis, Uppsala University, Analytical Chemistry, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8223.

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A trend in natural science and especially in analytical chemistry is the increasing need for analysis of a large number of complex samples with low analyte concentrations. Biological samples (urine, blood, plasma, cerebral spinal fluid, tissue etc.) are often suitable for analysis with liquid separation mass spectrometry (LS-MS), resulting in two-way data tables (time vs. m/z). Such biological 'fingerprints' taken for all samples in a study correspond to a large amount of data. Detailed characterization requires a high sampling rate in combination with high mass resolution and wide mass range, which presents a challenge in data handling and exploration. This thesis describes methods for managing and exploring large data sets made up of such detailed 'fingerprints' (represented as data matrices).

The methods were implemented as scripts and functions in Matlab, a wide-spread environment for matrix manipulations. A single-file structure to hold the imported data facilitated both easy access and fast manipulation. Routines for baseline removal and noise reduction were intended to reduce the amount of data without loosing relevant information. A tool for visualizing and exploring single runs was also included. When comparing two or more 'fingerprints' they usually have to be aligned due to unintended shifts in analyte positions in time and m/z. A PCA-like multivariate method proved to be less sensitive to such shifts, and an ANOVA implementation made it easier to find systematic differences within the data sets.

The above strategies and methods were applied to complex samples such as plasma, protein digests, and urine. The field of application included urine profiling (paracetamole intake; beverage effects), peptide mapping (different digestion protocols) and search for potential biomarkers (appendicitis diagnosis) . The influence of the experimental factors was visualized by PCA score plots as well as clustering diagrams (dendrograms).

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Hantoush, Raafat. "Evaluating Wi-Fi indoor positioning approaches in a real world environment." Master's thesis, 2016. http://hdl.handle.net/10362/19782.

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Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
Global positioning system(GPS) does not provide generally a good positioning performance in an indoor location because of many reasons (Henniges, 2012). On the other hand, other alternatives such as the WI-FI technology has become recently in a popular use to provide indoor localization. And that is due to many reasons, such as the wide spread of WI-FI infrastructure in the indoor environments and the low cost of this technology. This study attempts to evaluate different WI-FI indoor positioning approaches in a real world environment. In particular, in retail stores and shopping malls. The pros and cons of each one of these approaches are pointed out. The main purpose of this study from the company perspective is to explore the state of the art methods and the cutting edge technologies of the WI-FI IPS and to come up with an improvement of their indoor localization system. This system forms the core of the company`s retail-analytics product that uses a Wi-Fi positioning technology to provide indoor location based services for the customers and helps retailers to better understanding their businesses.
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Lauzon, Nidia. "Imagerie moléculaire d’empreintes digitales par spectrométrie de masse : potentiels et applications en science forensique." Thèse, 2018. http://hdl.handle.net/1866/21579.

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Books on the topic "Analytical fingerprint"

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Entomology & palynology. Philadelphia, Pa: Mason Crest Publishers, 2014.

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Walker, Maryalice. Entomology and palynology: Evidence from the natural world. Philadelphia: Mason Crest Publishers, 2006.

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Herbal Drugs And Fingerprints Evidence Based Herbal Drugs. Springer, 2012.

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Book chapters on the topic "Analytical fingerprint"

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Anand, Dama, G. Rama Krishna Srinivas, and Amara S. A. L. G. Gopala Gupta. "Fingerprint Identification and Matching." In Learning and Analytics in Intelligent Systems, 528–36. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24322-7_64.

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Thomas, Tony, Athira P. Vijayaraghavan, and Sabu Emmanuel. "Nearest Neighbor and Fingerprint Classification." In Machine Learning Approaches in Cyber Security Analytics, 107–28. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-1706-8_6.

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Khokher, Rohit, and Ram Chandra Singh. "A Graphical User Interface-Based Fingerprint Recognition." In Mathematical Modelling, Optimization, Analytic and Numerical Solutions, 379–98. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0928-5_19.

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Mishra, Annapurna, Satchidananda Dehuri, and Pradeep Kumar Mallick. "Classification of Real Time Noisy Fingerprint Images Using Flann." In Learning and Analytics in Intelligent Systems, 62–68. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39033-4_6.

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Lennard, C. "FORENSIC SCIENCES | Fingerprint Techniques." In Encyclopedia of Analytical Science, 414–23. Elsevier, 2005. http://dx.doi.org/10.1016/b0-12-369397-7/00200-4.

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van der Heide, Susan, and David A. Russell. "Latent Fingerprints for Drug Screening." In Detection of Drug Misuse: Biomarkers, Analytical Advances and Interpretation, 190–211. The Royal Society of Chemistry, 2017. http://dx.doi.org/10.1039/9781782621577-00190.

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The recent discovery that exogenous compounds, such as drugs or their metabolites, can be detected in the sweat deposited in latent fingerprints has led to the development of methods that provide additional information from a fingerprint beyond personal identification. Fingerprints offer considerable advantages for drug screening since they are non-invasive and straightforward to obtain. However, the use of fingerprints for drug screening does present a challenge for analytical measurements due to their small sample size and concentration. Here, we describe the considerable advances that have recently been made in this field of research, yielding high-throughput, non-destructive, highly sensitive, selective, image-based methods for the detection of drugs and drug metabolites in latent fingerprints.
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Cozzolino, Daniel, Heather E. Smyth, and Yasmina Sultanbawa. "Advances in fingerprint and rapid methods for improved traceability in agri-food supply chains." In Developing smart agri-food supply chains: Using technology to improve safety and quality, 29–42. Burleigh Dodds Science Publishing, 2021. http://dx.doi.org/10.19103/as.2021.0097.21.

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Agri-food supply and value chain markets have become increasingly complex due to the changes in consumers demands, the development of complex food standards associated with food safety and quality, advances in technology (e.g. big data, machine learning), and changes in the food industry structure. However, recent issues related to food authenticity, adulteration, fraud, mislabelling, traceability and provenance have added a new dimension to consumers’ concerns, and food industry and regulatory bodies worldwide. The incorporation of sensing technologies combined with data analytics, are determining a paradigm shift in the way food ingredients and foods are both evaluated and monitored. This chapter discusses the utilisation of data analytics and sensing technologies to address issues related with food authenticity, adulteration, fraud, traceability and provenance in the food supply and value chains. In particular, this chapter will focus on the use of rapid analytical methods based in vibrational spectroscopy in combination with data analytics.
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Hossen, Md Imran, Md Abdullah Al Momin, and Xiali Hei. "Generating Device Fingerprints for Smart Device Pairing Using the Unique Spectrum Characteristic From LEDs." In Security, Data Analytics, and Energy-Aware Solutions in the IoT, 111–24. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7323-5.ch007.

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Currently, the vast majority of smart devices with LEDs are on the rise. It has been observed that the lights emitted by each LED have unique spectral characteristics. Despite the fact that there are a number of methods out there to generate fingerprints, none seem to explore the possibility of generating fingerprints using this unique feature. In this chapter, the method to perform device fingerprinting using the unique spectrum emitted from the LED lights is discussed. The generated fingerprint is then used in device pairing.
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Nicoletti, Marcello, Valentina Petitto, Francesca R. Gallo, Giuseppina Multari, Elena Federici, and Giovanna Palazzino. "The Modern Analytical Determination of Botanicals and Similar Novel Natural Products by the HPTLC Fingerprint Approach." In Studies in Natural Products Chemistry Volume 37, 217–58. Elsevier, 2012. http://dx.doi.org/10.1016/b978-0-444-59514-0.00008-0.

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Donno, D., G. L. Beccaro, A. K. Cerutti, M. G. Mellano, and G. Bounous. "Bud Extracts as New Phytochemical Source for Herbal Preparations — Quality Control and Standardization by Analytical Fingerprint." In Phytochemicals - Isolation, Characterisation and Role in Human Health. InTech, 2015. http://dx.doi.org/10.5772/59759.

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Conference papers on the topic "Analytical fingerprint"

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Ballinger, Robert S., and David W. Herrin. "Structural Health Monitoring Using Modal Strain Energy." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0151.

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Abstract This research combines analytical and experimental modal analysis techniques to verify the structural integrity or monitor the “health” of a dynamic structure. Central to the procedure is the development of a baseline dynamic fingerprint model of the structure. The dynamic fingerprint is verified with experimental modal analysis and correlation. After the structure is placed into service, damage can be determined by comparing the current dynamic response with the baseline dynamic fingerprint response. The unique aspect of this procedure is that the current dynamic response is enforced on the undamaged baseline dynamic fingerprint model. Should damage exist, the structure is forced to deform in an unnatural manner, and high strain energy results. Significant differences in the normalized modal or operating strain energy density identify structural regions where a loss of stiffness, weakening of the structure, and/or damage has occurred. This identification of a potentially “unhealthy” structural region allows a quick visual inspection of the region or further analytical and/or experimental submodelling of the area to precisely identify the damage. The method is ideally suited to CAE application. The method is demonstrated analytically and experimentally for two structures: an eight-bay cantilevered truss structure and a rectangular plate with various boundary conditions.
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Patil, Ashwini R., and Mukesh A. Zaveri. "A Novel Approach for Fingerprint Matching Using Minutiae." In 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation. IEEE, 2010. http://dx.doi.org/10.1109/ams.2010.70.

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Kaushal, Himanshi, Anit Kaur, and Amit Verma. "An analytical framework design for latent fingerprint reconstruction, enhancement and recognition." In 2016 International Conference System Modeling & Advancement in Research Trends (SMART). IEEE, 2016. http://dx.doi.org/10.1109/sysmart.2016.7894506.

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Oshilike, Ishioma, Bella Mmata, Paschal Ugwu, Martins Otokpa, Chidinma Ibekwe, Okeke Hilary, and Mike Onyekonwu. "Fingerprint Analysis of Light Crude Oils from Niger Delta." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/212002-ms.

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Abstract Crude oil fingerprinting is a term applied to techniques that utilize geochemical analysis of hydrocarbon fluids composition to provide valuable information for well, reservoir and spill management. Analysis of crude oil fingerprints reveals a typical oil profile. Such a profile can provide information on formation history, type of carbon number preference during formation and route of migration. This study was undertaken using whole oil fingerprint and biomarkers of oils from twenty well strings from an onshore field in the Niger Delta Region. The aim was to evaluate light crude oils and determine thermal maturity, source rock quality, depositional environment and condensate correlation. The crude oil samples were analyzed using two major analytical techniques namely Gas Chromatography-Flame Ionization Detector (GC-FID) and Gas Chromatography-Mass Spectrometry (GC-MS). Evaluation of light hydrocarbon components was done using Mango parameters K1, K2, P2, P3 and N2 and the results revealed terrigenous organic matter input. Biomarker composition and pristane/phytane ratios in the range of 3.51 to 6.83 derived from GC results show that the source rock of the oils is made up of majorly terrestrial (type III) organic matter, deposited in a deltaic setting with prevailing oxic conditions. Maturity parameters calculated from Carbon Preference Indices between the range of 0.87 and 1.44 indicate the source is matured. The study provides key information on source characteristics that are applied to describe the type of petroleum prospects of a region. This study also provides information on condensate correlation, which has production implications such as application to production allocation.
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Fried, Alan, and Robert Sams. "Analytical Applications of High Resolution Infrared Tunable Diode Laser Spectroscopy." In Laser Applications to Chemical Analysis. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/laca.1987.tha3.

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Measurement techniques based upon absorption of mid-infrared radiation (2.5 - 25 μm) have proven to be extremely attractive in numerous research, environmental and industrial applications. Studies of atmospheric trace gases in both the laboratory and the ambient environment (1-3); as well as studies of flame (4), combustion (5), and laser diagnostics (6); studies of emissions from cigarette smoke (7), automobiles (8) and power plants (9); analysis of industrial process stream compounds (10); and moisture determinations in integrated circuit packages (11) are but a few examples of the broad range of such applications. This diversity is a direct result of the fact that many constituents exhibit moderate to strong absorption features in the mid- infrared, sometimes referred to as the "fingerprint region". Obviously, to cover all such applications is well beyond the scope of this paper, and we will therefore restrict our discussion of analytical applications of high resolution IR spectroscopy to one of the fasted growing and widespread areas: laboratory and ambient environmental studies of important atmospheric trace gases. In particular, we will focus our discussion on studies utilizing tunable diode lasers (TDLs) as the infrared radiation source, although one example of measurements utilizing another IR source will also be given. Even this specific topic is too extensive to comprehensively cover in such a short review, and we thus only attempt to give a broad overview of some of the more recent analytical applications of TDLs in studying atmospheric gases. Purely spectroscopic applications, which are equally numerous and very important, are not covered here.
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van Kuilenburg, Julien, Marc A. Masen, and Emile van der Heide. "A Mechanistic Approach to Predicting the Friction Behaviour of Human Skin." In ASME/STLE 2012 International Joint Tribology Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/ijtc2012-61164.

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In this work, analytical models available from contact mechanics theory having a proven record in mechanical engineering were used to develop a model predicting the friction behavior of human skin. A multi-scale contact model was developed in which the contact parameters are calculated at three levels, each level characterized by its elastic behavior and geometry. For a product part in contact with the so-called hairy skin the skin topography can be described as being composed of spherical contacts, whereas for the finger in contact with a product surface the fingerprint ridges are modeled as annulus shaped line contacts. Sliding friction was measured in vivo between the skin and different surface textures produced using ultra-short pulsed laser technology. The results observed during in vivo experiments are very well explained by the developed model, which predicts the friction as a function of product geometry, asperity geometry and normal load.
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Lieberman, R. A. "Fiber-optic sensors for environmental applications." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1993. http://dx.doi.org/10.1364/oam.1993.thp.1.

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The use of optical fibers for chemical monitoring predates communications uses. In recent years, advances in fiber optic and semiconductor technology, as well as in analytical chemistry and biochemistry, have made fiber optic chemical sensors very attractive for a wide variety of environmental applications. Remote spectroscopic measurements via optical fibers (passive fiber optic chemical sensing), including fluorescence and Raman spectroscopy, and often multiplexing many fibers to provide simultaneous multipoint chemical information, have become well accepted in the process control and environmental monitoring industries. Active techniques, in which chemically sensitive devices, or “optrodes”, are attached to fibers, are being intensively studied, and a few sensor systems based on these are beginning to appear as commercial products. Intrinsic sensors, in which optical fibers are the actual chemical transduction devices, have begun to attract wide attention, because of their potential for continuous long-path monitoring. Chemical sensing requirements challenge fiber optic researchers: new optical fiber designs (D-fibers, hollow waveguides, multi-core, off-center core, tapered geometries, and others) are being investigated to enhance fiber chemical sensitivity. New fiber materials (fluorozirconate, chalcogenide, sapphire, silver halide, and others) are being developed to extend transmission into the infrared “chemical fingerprint” region of the electromagnetic spectrum.
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Havlova´, Va´clava, Radek Cˇervinka, Ulrich Noseck, Thomas Brasser, and Josef Havel. "The Ruprechtov Natural Analogue Site (CZ) Study: Mobile Natural Organic Matter Identification, Characterisation and Link to PA Relevant Processes." In ASME 2009 12th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2009. http://dx.doi.org/10.1115/icem2009-16341.

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The Ruprechtov Natural Analogue (CZ) Programme has been focused on studying real system processes, relevant to performance assessment (PA) of sediment formations that can form the overburden of geological repository host rocks. The site has been extensively studied due to its geological constitution (granite – kaolin – clay – U mineralisation – organic matter). The presented study used Ruprechtov unique but well-described geological conditions in order to identify and characterise mobile organic matter (MOM) that can be easily released into groundwater and can influence PA relevant specie migration due to complexation/sorption reaction. The modern analytical method MALDI-TOF MS was used for characterisation. It was found that only a small fraction of sedimentary natural organic matter (NOM) from the site was easily releasable (max. 5%) as MOM, resulting in low organic substance concentration in natural groundwater. MOM amount released was decreasing with increasing NOM content. MALDI-TOF MS proved to be a useful tool to characterize organic substances, either natural ones or artificially released from natural organic matter samples. A noticeable fingerprint for all the MOM compounds analysed was found at MALDI-TOF MS spectra. This showed that MOM from the Ruprechtov site was in all cases composed of molecules with low molecular weight (under 1000 Da). As determined by the consequent geochemical analyses, despite groundwater reducing conditions MOM compounds would be mainly interacting with U(VT) in the groundwater, being present as more abundant U specie. Good correspondence of results enabled to consider the extracted humic acid HA 12/3 as a mobile organic matter fraction representative.
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Lazimul, Limnd T. P., and D. L. Binoy. "Fingerprint liveness detection using convolutional neural network and fingerprint image enhancement." In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). IEEE, 2017. http://dx.doi.org/10.1109/icecds.2017.8389533.

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Herrmann, Markus, Jörg Petzold, and Vivek Bombatkar. "Blockchain-backed analytics. Adding blockchain-based quality gates to data science projects." In CARMA 2018 - 2nd International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica València, 2018. http://dx.doi.org/10.4995/carma2018.2018.8292.

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A typical analytical lifecycle in data science projects starts with the process of data generation and collection, continues with data preparation and preprocessing and heads towards project specific analytics, visualizations and presentations. In order to ensure high quality trusted analytics, every relevant step of the data-model-result linkage needs to meet certain quality standards that furthermore should be certified by trusted quality gate mechanisms.We propose “blockchain-backed analytics”, a scalable and easy-to-use generic approach to introduce quality gates to data science projects, backed by the immutable records of a blockchain. For that reason, data, models and results are stored as cryptographically hashed fingerprints with mutually linked transactions in a public blockchain database.This approach enables stakeholders of data science projects to track and trace the linkage of data, applied models and modeling results without the need of trust validation of escrow systems or any other third party.
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Reports on the topic "Analytical fingerprint"

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Libert, John M., Shahram Orandi, John D. Grantham, and Michael D. Garris. A Spectral Analytic Method for Fingerprint Image Sample Rate Estimation. National Institute of Standards and Technology, February 2014. http://dx.doi.org/10.6028/nist.ir.7968.

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Honey authenticity: collaborative data sharing feasibility study. Food Standards Agency, January 2023. http://dx.doi.org/10.46756/sci.fsa.fbt231.

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According to the UN,1 there are more than 90 million managed beehives around the world producing about 1.9 million tonnes of honey worth more than £5 billion a year. That honey will then be packaged, as single origin or a blend of honey from different sources, and sold for consumption. Given the size of the market and the immense environmental benefits of beekeeping – three out of four crops depend on pollination by bees – it is an industry on which both livelihoods and lives depend. Target for adulteration As a labour-intensive, high-value expensive product with an often complex supply chain, honey is subject to internationally and nationally agreed definitions – and is a target for adulteration. Testing honey is therefore critical, but there is no single universal analytical method available which is capable of detecting all types of adulteration with adequate sensitivity. A variety of methods are used to detect honey adulteration, each test has strengths and weaknesses, and there are issues with interpretation. NMR analysis Testing for honey adulterated with added sugars may be based on analytical techniques using analytical tools, such as those using nuclear magnetic resonance spectroscopy (NMR). This is especially helpful in detecting certain types of adulteration, such as the addition of cane or beet sugars. Bees generally forage on plants that use the same photosynthetic pathway as beet sugars. This makes it difficult for traditional tests based on isotopic differences to provide effective results. The ‘chemical fingerprint’ provided by NMR is specific to the sample that has been tested and can be compared with the fingerprint from other sample results enabling the user to assess consistency. Reference databases Interpretation of results depends on comparison against a reference database of authenticated samples. The reference database needs to be representative of the variation that can occur, which includes differing beekeeping practices, origins, seasonality and variations in climate. Information is also needed on the collection of reference samples, curation of databases, interpretation and reporting of data. The nature of the reference databases is key to understanding how the results have been interpreted. However, these reference databases are owned by and commercially sensitive for the testing laboratories that have developed them. How can such data be shared in a trustworthy way between key stakeholders along the honey and analytical supply chain so that all parties can have confidence in honey authenticity test results? This research is looking into the implications of these hidden databases, especially in terms of the trust related to the validation certificates and the value that they have in the honey supply chain.
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