Refine
H-BRS Bibliography
- yes (93) (remove)
Departments, institutes and facilities
- Institut für Sicherheitsforschung (ISF) (93) (remove)
Document Type
- Article (43)
- Conference Object (34)
- Report (5)
- Doctoral Thesis (3)
- Patent (3)
- Contribution to a Periodical (2)
- Part of a Book (1)
- Conference Proceedings (1)
- Research Data (1)
Year of publication
Keywords
- Chemometrics (4)
- DNA typing (3)
- Raman spectroscopy (3)
- Classification (2)
- Cooperative Awareness Message (2)
- Discriminant analysis (2)
- Hyperspectral image (2)
- Intelligent Transport System (2)
- Principal Components Analysis (2)
- Privacy (2)
Forensic DNA profiles are established by multiplex PCR amplification of a set of highly variable short tandem repeat (STR) loci followed by capillary electrophoresis (CE) as a means to assign alleles to PCR products of differential length. Recently, CE analysis of STR amplicons has been supplemented by high-throughput next generation sequencing (NGS) techniques that are able to detect isoalleles bearing sequence polymorphisms and allow for an improved analysis of degraded DNA. Several such assays have been commercialised and validated for forensic applications. However, these systems are cost-effective only when applied to high numbers of samples. We report here an alternative, cost-efficient shallow-sequence output NGS assay called maSTR assay that, in conjunction with a dedicated bioinformatics pipeline called SNiPSTR, can be implemented with standard NGS instrumentation. In a back-to-back comparison with a CE-based, commercial forensic STR kit, we find that for samples with low DNA content, with mixed DNA from different individuals, or containing PCR inhibitors, the maSTR assay performs equally well, and with degraded DNA is superior to CE-based analysis. Thus, the maSTR assay is a simple, robust and cost-efficient NGS-based STR typing method applicable for human identification in forensic and biomedical contexts.
The application of Raman and infrared (IR) microspectroscopy is leading to hyperspectral data containing complementary information concerning the molecular composition of a sample. The classification of hyperspectral data from the individual spectroscopic approaches is already state-of-the-art in several fields of research. However, more complex structured samples and difficult measuring conditions might affect the accuracy of classification results negatively and could make a successful classification of the sample components challenging. This contribution presents a comprehensive comparison in supervised pixel classification of hyperspectral microscopic images, proving that a combined approach of Raman and IR microspectroscopy has a high potential to improve classification rates by a meaningful extension of the feature space. It shows that the complementary information in spatially co-registered hyperspectral images of polymer samples can be accessed using different feature extraction methods and, once fused on the feature-level, is in general more accurately classifiable in a pattern recognition task than the corresponding classification results for data derived from the individual spectroscopic approaches.
Durch Dotierung eines nematischen Flüssigkristalles mit einer chiralen Substanz wird eine helikal strukturierte Phase induziert, die in der Lage ist, einfallendes Licht wellenlängenselektiv zu reflektieren. Bei der Reaktion des Dotiermittels mit einem gasförmigen Analyten verändern sich die Ganghöhe dieser Struktur und damit die reflektierte Wellenlänge. Liegt diese im Bereich des sichtbaren Lichts, ist eine Farbänderung mit dem menschlichen Auge zu beobachten. Es ist dabei sinnvoll den Flüssigkristall z.B. in einem Polymer einzukapseln, um ihn vor mechanischen Einflüssen und Umwelteinflüssen zu schützen. Eine Möglichkeit zur Einkapselung ist das koaxiale Elektrospinnen. Vorteile sind unter anderem die Realisierung einer großen Oberfläche und einer sehr geringen Wanddicke der schützenden Schale, die die Diffusion von Gasen durch die Wand hindurch ermöglicht. Um die Funktionsfähigkeit eines solchen Sensors zu testen, wurde ein CO2-sensitiver Flüssigkristall verwendet. Dieser wurde in eine Schale aus Polyvinylpyrrolidon (PVP) versponnen und die Reaktion mit CO2 spektroskopisch analysiert.
Optical gas sensors based on chiral-nematic liquid crystals (N* LCs) forming one-dimensional photonic crystals do not require electrical energy and have a considerable potential to supplement established types of sensors. A chiral-nematic phase with tunable selective reflection is induced in a nematic host LC by adding reactive chiral dopants. The selective chemical reaction between dopant and analyte is capable to vary the pitch length (the lattice constant) of the soft, self-assembled, one-dimensional photonic crystal. The progress of the ongoing chemical reaction can be observed even by naked eye because the color of the samples varies. In this work, we encapsulate the responsive N* LC in microscale polyvinylpyrrolidone (PVP) fibers via coaxial electrospinning. The sensor is, thus, given a solid form and has an improved stability against nonavoidable environmental influences. The reaction behavior of encapsulated and nonencapsulated N* LC toward a gaseous analyte is compared, systematically. Making use of the encapsulation is an important step to improve the applicability.
Due to their user-friendliness and reliability, biometric systems have taken a central role in everyday digital identity management for all kinds of private, financial and governmental applications with increasing security requirements. A central security aspect of unsupervised biometric authentication systems is the presentation attack detection (PAD) mechanism, which defines the robustness to fake or altered biometric features. Artifacts like photos, artificial fingers, face masks and fake iris contact lenses are a general security threat for all biometric modalities. The Biometric Evaluation Center of the Institute of Safety and Security Research (ISF) at the University of Applied Sciences Bonn-Rhein-Sieg has specialized in the development of a near-infrared (NIR)-based contact-less detection technology that can distinguish between human skin and most artifact materials. This technology is highly adaptable and has already been successfully integrated into fingerprint scanners, face recognition devices and hand vein scanners. In this work, we introduce a cutting-edge, miniaturized near-infrared presentation attack detection (NIR-PAD) device. It includes an innovative signal processing chain and an integrated distance measurement feature to boost both reliability and resilience. We detail the device’s modular configuration and conceptual decisions, highlighting its suitability as a versatile platform for sensor fusion and seamless integration into future biometric systems. This paper elucidates the technological foundations and conceptual framework of the NIR-PAD reference platform, alongside an exploration of its potential applications and prospective enhancements.