20 resultados para FINGERPRINTS


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In this chapter, we discuss four related areas of cryptology, namely, authentication, hashing, message authentication codes (MACs), and digital signatures. These topics represent active and growing research topics in cryptology. Space limitations allow us to concentrate only on the essential aspects of each topic. The bibliography is intended to supplement our survey. We have selected those items which providean overview of the current state of knowledge in the above areas. Authentication deals with the problem of providing assurance to a receiver that a communicated message originates from a particular transmitter, and that the received message has the same content as the transmitted message. A typical authentication scenario occurs in computer networks, where the identity of two communicating entities is established by means of authentication. Hashing is concerned with the problem of providing a relatively short digest–fingerprint of a much longer message or electronic document. A hashing function must satisfy (at least) the critical requirement that the fingerprints of two distinct messages are distinct. Hashing functions have numerous applications in cryptology. They are often used as primitives to construct other cryptographic functions. MACs are symmetric key primitives that provide message integrity against active spoofing by appending a cryptographic checksum to a message that is verifiable only by the intended recipient of the message. Message authentication is one of the most important ways of ensuring the integrity of information that is transferred by electronic means. Digital signatures provide electronic equivalents of handwritten signatures. They preserve the essential features of handwritten signatures and can be used to sign electronic documents. Digital signatures can potentially be used in legal contexts.

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A combination of laser plasma ablation and strain control in CdO/ZnO heterostructures is used to produce and stabilize a metastable wurtzite CdO nanophase. According to the Raman selection rules, this nanophase is Raman-active whereas the thermodynamically preferred rocksalt phase is inactive. The wurtzite-specific and thickness/strain-dependent Raman fingerprints and phonon modes are identified and can be used for reliable and inexpensive nanophase detection. The wurtzite nanophase formation is also confirmed by x-ray diffractometry. The demonstrated ability of the metastable phase and phonon mode control in CdO/ZnO heterostructures is promising for the development of next-generation light emitting sources and exciton-based laser diodes.

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Wi-Fi is a commonly available source of localization information in urban environments but is challenging to integrate into conventional mapping architectures. Current state of the art probabilistic Wi-Fi SLAM algorithms are limited by spatial resolution and an inability to remove the accumulation of rotational error, inherent limitations of the Wi-Fi architecture. In this paper we leverage the low quality sensory requirements and coarse metric properties of RatSLAM to localize using Wi-Fi fingerprints. To further improve performance, we present a novel sensor fusion technique that integrates camera and Wi-Fi to improve localization specificity, and use compass sensor data to remove orientation drift. We evaluate the algorithms in diverse real world indoor and outdoor environments, including an office floor, university campus and a visually aliased circular building loop. The algorithms produce topologically correct maps that are superior to those produced using only a single sensor modality.

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Samples of Forsythia suspensa from raw (Laoqiao) and ripe (Qingqiao) fruit were analyzed with the use of HPLC-DAD and the EIS-MS techniques. Seventeen peaks were detected, and of these, twelve were identified. Most were related to the glucopyranoside molecular fragment. Samples collected from three geographical areas (Shanxi, Henan and Shandong Provinces), were discriminated with the use of hierarchical clustering analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) models, but only PCA was able to provide further information about the relationships between objects and loadings; eight peaks were related to the provinces of sample origin. The supervised classification models-K-nearest neighbor (KNN), least squares support vector machines (LS-SVM), and counter propagation artificial neural network (CP-ANN) methods, indicated successful classification but KNN produced 100% classification rate. Thus, the fruit were discriminated on the basis of their places of origin.

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Change in temperature is often a major environmental factor in triggering waterborne disease outbreaks. Previous research has revealed temporal and spatial patterns of bacterial population in several aquatic ecosystems. To date, very little information is available on aquaculture environment. Here, we assessed environmental temperature effects on bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei (FASFL). Water samples were collected over a one-year period, and aquatic bacteria were characterized by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA pyrosequencing. Resulting DGGE fingerprints revealed a specific and dynamic bacterial population structure with considerable variation over the seasonal change, suggesting that environmental temperature was a key driver of bacterial population in the FASFL. Pyrosequencing data further demonstrated substantial difference in bacterial community composition between the water at higher (WHT) and at lower (WLT) temperatures in the FASFL. Actinobacteria, Proteobacteria and Bacteroidetes were the highest abundant phyla in the FASFL, however, a large number of unclassified bacteria contributed the most to the observed variation in phylogenetic diversity. The WHT harbored remarkably higher diversity and richness in bacterial composition at genus and species levels when compared to the WLT. Some potential pathogenenic species were identified in both WHT and WLT, providing data in support of aquatic animal health management in the aquaculture industry.