Face Recognition Based on Texture Descriptors

In this chapter, the performance of different texture descriptor algorithms used in face feature extraction tasks are analyzed. These commonly used algorithms to extract texture characteristics from images, with quite good results in this task, are also expected to provide fairly good results when used to characterize the face in an image. To perform the testing task, an AR face database, which is a standard database that contains images of 120 people, was used, including 70 images with different facial expressions and 30 with sunglasses, and all of them with different illumination intensity. To train the recognition system from one to seven images were used for each person. Different classifiers like Euclidean distance, cosine distance, and support vector machine (SVM) were also used, and the results obtained were higher than 98% for classification, achieving a good performance in verification task. This chapter was also compared with other schemes, showing the effectiveness of all of them

Aneurisma sintomático de arteria carótida interna

Los aneurismas de la arteria carótida extracraneal son raros y representan una minoría de la cirugía carotídea en la mayoría de las unidades vasculares. Se presenta un caso clínico de un aneurisma sacular de la arteria carótida interna en un paciente joven, sin causa aparente. La mayoría de estos aneurismas son asintomáticos, aunque, en este paciente debutó como ictus por embolización distal. El manejo consistió en un abordaje quirúrgico abierto a las 4 semanas tras el episodio inicial. En la intervención se extirpó el aneurisma con sutura termino-terminal de la arteria carótida interna. Aneurysms of the extracranial carotid artery are rare and represent a minority of the carotid surgery in most vascular units. A clinical case of a saccular aneurism of the internal carotid artery, in a young patient without apparent cause, is showcased. They are often asymptomatic, but they also may show (as it was in this patient) stroke from distal embolisation as a debut. The management consisted in an open surgical approach (by meaning, aneurysm excision with termino-terminal. suture of the internal carotid artery, without shunt), 4 weeks after the initial episode

A dense neural network approach for detecting clone ID attacks on the RPL protocol of the IoT

At present, new data sharing technologies, such as those used in the Internet of Things (IoT) paradigm, are being extensively adopted. For this reason, intelligent security controls have become imperative. According to good practices and security information standards, particularly those regarding security in depth, several defensive layers are required to protect information assets. Within the context of IoT cyber-attacks, it is fundamental to continuously adapt new detection mechanisms for growing IoT threats, specifically for those becoming more sophisticated within mesh networks, such as identity theft and cloning. Therefore, current applications, such as Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS), and Security Information and Event Management Systems (SIEM), are becoming inadequate for accurately handling novel security incidents, due to their signature-based detection procedures using the matching and flagging of anomalous patterns. This project focuses on a seldom-investigated identity attack—the Clone ID attack—directed at the Routing Protocol for Low Power and Lossy Networks (RPL), the underlying technology for most IoT devices. Hence, a robust Artificial Intelligence-based protection framework is proposed, in order to tackle major identity impersonation attacks, which classical applications are prone to misidentifying. On this basis, unsupervised pre-training techniques are employed to select key characteristics from RPL network samples. Then, a Dense Neural Network (DNN) is trained to maximize deep feature engineering, with the aim of improving classification results to protect against malicious counterfeiting attempts

Quantification of Signal-to-Noise Ratio in Cerebral Cortex Recordings Using Flexible MEAs With Co-localized Platinum Black, Carbon Nanotubes, and Gold Electrodes

Developing new standardized tools to characterize brain recording devices is critical to evaluate neural probes and for translation to clinical use. The signal-to-noise ratio (SNR) measurement is the gold standard for quantifying the performance of brain recording devices. Given the drawbacks with the SNR measure, our first objective was to devise a new method to calculate the SNR of neural signals to distinguish signal from noise. Our second objective was to apply this new SNR method to evaluate electrodes of three different materials (platinum black, Pt; carbon nanotubes, CNTs; and gold, Au) co-localized in tritrodes to record from the same cortical area using specifically designed multielectrode arrays. Hence, we devised an approach to calculate SNR at different frequencies based on the features of cortical slow oscillations (SO). Since SO consist in the alternation of silent periods (Down states) and active periods (Up states) of neuronal activity, we used these as noise and signal, respectively. The spectral SNR was computed as the power spectral density (PSD) of Up states (signal) divided by the PSD of Down states (noise). We found that Pt and CNTs electrodes have better recording performance than Au electrodes for the explored frequency range (5–1500 Hz). Together with two proposed SNR estimators for the lower and upper frequency limits, these results substantiate our SNR calculation at different frequency bands. Our results provide a new validated SNR measure that provides rich information of the performance of recording devices at different brain activity frequency bands (<1500 Hz)

P1 and P2 protein heterodimer binding to the P0 protein of Saccharomyces cerevisiae is relatively non-specific and a source of ribosomal heterogeneity

The ribosomal stalk is formed by four acidic phosphoproteins in Saccharomyces cerevisiae, P1α, P1β, P2α and P2β, which form two heterodimers, P1α/P2β and P1β/P2α, that preferentially bind to sites A and B of the P0 protein, respectively. Using mutant strains carrying only one of the four possible P1/P2 combinations, we found a specific phenotype associated to each P1/P2 pair, indicating that not all acidic P proteins play the same role. The absence of one P1/P2 heterodimer reduced the rate of cell growth by varying degrees, depending on the proteins missing. Synthesis of the 60S ribosomal subunit also decreased, particularly in strains carrying the unusual P1α–P2α or P1β–P2β heterodimers, although the distinct P1/P2 dimers are bound with similar affinity to the mutant ribosome. While in wild-type strains the B site bound P1β/P2α in a highly specific manner and the A site bound the four P proteins similarly, both the A and B binding sites efficiently bound practically any P1/P2 pair in mutant strains expressing truncated P0 proteins. The reported results support that while most ribosomes contain a P1α/P2β–P0–P1β/P2α structure in normal conditions, the stalk assembly mechanism can generate alternative compositions, which have been previously detected in the cell