Advanced Biometrics with Deep Learning

Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others

Privacy-Preserving Biometric Authentication

Biometric-based authentication provides a highly accurate means of authentication without requiring the user to memorize or possess anything. However, there are three disadvantages to the use of biometrics in authentication; any compromise is permanent as it is impossible to revoke biometrics; there are significant privacy concerns with the loss of biometric data; and humans possess only a limited number of biometrics, which limits how many services can use or reuse the same form of authentication. As such, enhancing biometric template security is of significant research interest. One of the methodologies is called cancellable biometric template which applies an irreversible transformation on the features of the biometric sample and performs the matching in the transformed domain. Yet, this is itself susceptible to specific classes of attacks, including hill-climb, pre-image, and attacks via records multiplicity. This work has several outcomes and contributions to the knowledge of privacy-preserving biometric authentication. The first of these is a taxonomy structuring the current state-of-the-art and provisions for future research. The next of these is a multi-filter framework for developing a robust and secure cancellable biometric template, designed specifically for fingerprint biometrics. This framework is comprised of two modules, each of which is a separate cancellable fingerprint template that has its own matching and measures. The matching for this is based on multiple thresholds. Importantly, these methods show strong resistance to the above-mentioned attacks. Another of these outcomes is a method that achieves a stable performance and can be used to be embedded into a Zero-Knowledge-Proof protocol. In this novel method, a new strategy was proposed to improve the recognition error rates which is privacy-preserving in the untrusted environment. The results show promising performance when evaluated on current datasets

Biometric Systems

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study

Human and Biological Skin-Inspired Electronic Skins for Advanced Sensory Functions and Multifunctionality

Department of Energy Engineering (Energy Engineering)The electronic skin (e-skin) technology is an exciting frontier to drive next generation of wearable electronics owing to its high level of wearability to curved human body, enabling high accuracy to harvest information of users and their surroundings. Altough various types of e-skins, based on several signal-transduction modes, including piezoresistive, capacitive, piezoelectric, triboelectric modes, have been developed, their performances (i.e. sensitivity, working range, linearity, multifunctionality, etc.) should be improved for the wearable applications. Recently, biomimicry of the human and biological skins has become a great inspiration for realizing novel wearable e-skin systems with exceptional multifunctionality as well as advanced sensory functions. As an ideal sensory organ, tactile sensing capabilities of human skin was emulated for the development of e-skins with enhanced sensor performances. In particular, the unique geometry and systematic sensory system of human skin have driven new opportunities in multifunctional and highly sensitive e-skin applications. In addition, extraordinary architectures for protection, locomotion, risk indication, and camouflage in biological systems provide great possibilities for second skin applications on user-interactive, skin-attachable, and ultrasensitive e-skins, as well as soft robots. Benefitting from their superior perceptive functions and multifunctionality, human and biological skins-inspired e-skins can be considered to be promising candidates for wearable device applications, such as body motion tracking, healthcare devices, acoustic sensor, and human machine interfaces (HMI). This thesis covers our recent studies about human and biological skin-inspired e-skins for advanced sensory functions and multifunctionality. First, chapter 1 highlights various types of e-skins and recent research trends in bioinspired e-skins mimicking perceptive features of human and biological skins. In chapter 2, we demonstrate highly sensitive and tactile-direction-sensitive e-skin based on human skin-inspired interlocked microdome structures. Owing to the stress concentration effect, the interlocked e-skin experiences significant change of contact area between the interlocked microdomes, resulting in high pressure sensitivity. In addition, because of the different deformation trends between microstructures in mutual contact, the interlocked e-skin can differentiate and decouple sensor signals under different directional forces, such as pressure, tensile strain, shear, and bending. In chapter 3, interlocked e-skins were designed with multilayered geometry. Although interlocked e-skin shows highly sensitive pressure sensing performances, their pressure sensing range is narrow and pressure sensitivity continuously decreases with increasing pressure level. The multilayer interlocked microdome geometry can enhance the pressure-sensing performances of e-skins, such as sensitivity, working range, and linearity. As another approach of e-skin with multilayered geometry, we demonstrate multilayered e-skin based on conductivity-gradient conductive materials in chapter 4. The conducive polymer composites with different conductivity were coated on the microdome pattern and designed as interlocked e-skin with coplanar electrode design, resulting in exceptionally high pressure-sensing performances compared with previous literatures. In chapter 5, inspired by responsive color change in biological skins, we developed mechanochromic e-skin with a hierarchical nanoparticle-in-micropore architecture. The novel design of hierarchical structure enables effective stress concentration at the interface between nanoparticle and porous structure, resulting in impressive color change under mechanical stimuli. In chapter 6, we emulate ultrahigh temperature sensitivity of human and snake skin for temperature-sensitive e-skin. The thermoresponsive composite based on semi-crystalline polymer, temperature sensor shows ultrahigh temperature sensitivity near the melting point of semi-crystalline polymer. In addition, integration of thermochromic composite, mimicking biological skins, enables dual-mode temperature sensors by electrical and colorimetric sensing capabilities. Finally, in chapter 7, we summarize this thesis along with future perspective that should be considered for next-generation e-skin electronics. Our e-skins, inspired by human and biological skin, can provide a new paradigm for realizing novel wearable electronic systems with exceptional multifunctionality as well as advanced sensory functions.clos

Value of Mineralogical Monitoring for the Mining and Minerals Industry In memory of Prof. Dr. Herbert Pöllmann

This Special Issue, focusing on the value of mineralogical monitoring for the mining and minerals industry, should include detailed investigations and characterizations of minerals and ores of the following fields for ore and process control: Lithium ores—determination of lithium contents by XRD methods; Copper ores and their different mineralogy; Nickel lateritic ores; Iron ores and sinter; Bauxite and bauxite overburden; Heavy mineral sands. The value of quantitative mineralogical analysis, mainly by XRD methods, combined with other techniques for the evaluation of typical metal ores and other important minerals, will be shown and demonstrated for different minerals. The different steps of mineral processing and metal contents bound to different minerals will be included. Additionally, some processing steps, mineral enrichments, and optimization of mineral determinations using XRD will be demonstrated. Statistical methods for the treatment of a large set of XRD patterns of ores and mineral concentrates, as well as their value for the characterization of mineral concentrates and ores, will be demonstrated. Determinations of metal concentrations in minerals by different methods will be included, as well as the direct prediction of process parameters from raw XRD data

Evaluation of dendritic polyglycerol sulfate as inhibitor of sonic hedgehog and further protumorigenic factors

In the context of drug development for the treatment of complex diseases such as cancer, it might be necessary to interfere with multiple targets. Inspired by the multiple functions of heparan sulfate proteoglycans (HSPGs) several compounds have been developed in the past. Here the fully synthetic dendritic polyglycerol sulfates dPGS and dPGTPS were evaluated with respect to their overall anti-tumorigenic properties. Primarily focused on the sonic hedgehog (Shh) pathway, which is upregulated in several aggressive tumors, it was found that both compounds reduce pathway activation. Shh binding was analyzed via SPR and gave the following KD values: 88.7 nM for dPGS and 37 nM for dPGTPS. The inhibition of the Shh-signaling pathway was further evaluated in two reporter cell-based systems: a luciferase reporter and an alkaline phosphatase (ALP) assay. While dPGTPS showed consistently strong pathway inhibitory activity (IC50 of 72 nM in the ALP and 111 nM in the luciferase assay), dPGS displayed a different behavior (IC50 of 81 nM in ALP and 6.5 µM in luciferase assay), which might be attributed to the different architecture of the polysulfates. Cancer cell line proliferation also mediated by the Shh pathway was further analyzed in 2D cultures and 3D spheroid-based assays. In monolayer 2D studies, dPGS did not show any influence, while dPGTPS at µM concentrations reduced cell proliferation. By contrast, in 3D spheroid-based cultures, both dPGS and dPGTPS, significantly arrested the growth of A549 spheroids, although the latter compound to a lower extent. At the molecular level growth factors mediate cell proliferation. Therefore, binding of FGF1, FGF2, and VEGF165 to the polysulfates was analyzed, again via SPR. All proteins bound tightly to the sulfated compounds (i.e., KD of 25 nM for FGF2-dPGS interaction). Further, the capacity of dPGS to hamper angiogenic processes was confirmed in case of inhibition of HUVECs proliferation. FGF2-induced HUVECs proliferation was reduced upon dPGS treatment (IC50=21 µM) and cell differentiation to initiate three-dimensional capillary-like tube formation dose-dependently blocked. Heparanase is an essential enzyme to initiate remodeling of the extracellular matrix (ECM) during tumorigenesis. The polysulfate dPGS displayed a remarkable affinity to the protein (KD of 3.11 nM) and blocked its enzymatic activity (IC50 = 2 nM). To conclude, these findings emphasize the potential of synthetic polysulfates and should inspire future studies to explore their anti-tumorigenic efficacy.Für die Entwicklung von Medikamenten die zur Behandlung komplexer Krankheiten eingesetzt werden sollen, kann es hilfreich sein multiple Zielstrukturen zu adressieren. Inspiriert durch die zahlreichen Funktionen der Heparansulfat-Proteoglykane (HSPG) wurden in der Vergangenheit zahlreiche Verbindungen synthetisiert. In dieser Arbeit wurden die vollsynthetisch hergestellten dendritischen Polyglycerinsulfate dPGS und dPGTPS hinsichtlich ihrer antitumorgenen Wirkung untersucht. Zunächst fokussiert auf den Sonic Hedgehog (Shh)-Signalweg, der in vielen agressiven Tumoren reaktiviert wird, konnte gezeigt werden, dass beide Verbindungen die Aktivität vermindern. Bindung des Proteins Shh wurde mittels Oberflächenplasmonresonanz Spektroskopie untersucht und ergab KD Werte von 88,7 nM für dPGS und 37 nM für dPGTPS. Die Inhibition des Shh-Signalweges wurde weiterhin in zwei zellbasierten Systemen evaluiert: einem Luciferase Reportertest und einem Alkalischer Phosphatase (ALP) Reportertest. Während dPGTPS übereinstimmend eine ausgeprägte Hemmung in beiden Reportersystemen zeigte (IC50 von 72 nM im ALP Test und 111 nM im Luciferase-basierten Test), ergab der Einsatz von dPGS ein anderes Bild (IC50 von 81 nM in ALP Test und 6.5 µM in Luciferase-basierten Test), was möglicherweise auf die unterschiedliche Architektur der beiden Polysulfate zurückzuführen ist. Da die Proliferation von Krebszelllinien ebenfalls durch den Shh-Signalweg vermittelt werden kann, wurde dies in 2D-Zellkulturen und im 3D-Spheroid Modell untersucht. In Monolagen wachsender 2D Zellkultur zeigte dPGS keinen Einfluss, während dPGTPS in µM Konzentration eine Reduktion der Zellproliferation ergab. Ein anderes Verhalten ergab sich im 3D-Spheroid Modell. Hier zeigte sich, dass sowohl dPGS als auch dPGTPS signifikant das Wachstum von A549 Spheroiden verzögerte, wobei dPGTPS sich als weniger effektiv erwies. Auf molekularer Ebene vermitteln Wachstumsfaktoren die Zellproliferation. Daher wurde die Bindung von FGF1, FGF2 und VEGF165 an die Polysulfate mittels Oberflächenplasmonresonanz Spektroskopie untersucht. Hierbei zeigten alle Proteine eine hochaffine Bindung an die sulfatierten Verbindungen (z. B. KD von 25 nM für die FGF2-dPGS Bindung). Weiterhin wurde die Fähigkeit von dPGS die Angiogenese zu beeinflussen durch Hemmung der Proliferation am Beispiel von HUVECs bestätigt. FGF2-induzierte Proliferation von HUVECs wurde durch dPGS gehemmt (IC50=21 µM) und Zelldifferenzierung, hin zu einem dreidimensionalem kapillar-ähnlichen Netzwerk, blockiert. Heparanase ist ein essentielles Enzym, das Remodelierungsprozesse der extrazellulären Matrix (ECM) in der Tumorgenese einleitet. Das Polysulfat dPGS zeigte eine bemerkenswerte Bindungsaffinität an das Protein (KD von 3.11 nM) und blockierte dessen enzymatische Aktivität (IC50=2 nM). Zusammenfassend weisen die Befunde auf das hohe Potential der synthetischen Polysulfate hin, die in weitere Studien zur Wirksamkeit ihrer antitumorgenen Eigenschaften untersucht werden sollte

Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement

Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method