There are seven confirmed hepatitis C virus (HCV) genotypes, with whole-genome nucleotide sequences differing by Ͼ30%, and each can be further subdivided into related subtypes (67 confirmed), with nucleotide sequence divergence of between 15% and 30% (1).Genotype identification has long been used in clinical practice, because major genotypes have different response rates and require different doses and durations of pegylated interferon and ribavirin (PR) treatment. In contrast, until recently, subtype identification was mainly used in epidemiological studies. However, both in vitro studies and clinical trials with different classes of direct-acting antiviral (DAA) agents (NS3 protease, NS5A-, and nucleos[t]ide and nonnucleos[t]ide NS5B-polymerase inhibitors), given with PR or in interferon-free combinations, have shown lower response rates for HCV genotype 1a than for HCV genotype 1b (2-8). Moreover, at least for HCV genotype 1, both the frequency and the pattern of resistance to different DAA classes are subtype specific (9). A striking example is the NS3-Q80K polymorphism, naturally found in Ͼ30% of naive subtype 1a patients but in Ͻ1% of subtype 1b patients (10), which conveys 30%-to-40%-lower sustained-virologic-response (SVR) rates to the macrocyclic protease inhibitor simeprevir (2). Similarly, all subtype 1g sequences identified naturally carry a mutation conferring resistance to linear NS3 protease inhibitors (11).Subtype-specific differences in the genetic barrier to resistance appear to correlate to the RNA-dependent RNA polymerase mu-

Abstract. The present paper describes the objectives, structure, present stage, results and future milestones of the project ELEVA. This project is aimed to control an autonomous helicopter in order to follow an overhead power cable by means of a stereo computer vision system. The helicopter is aimed to have always in sight the overhead power cable, to follow it by using it as an external visual reference guide and to record it for its ulterior visual inspection. These objectives are achieved by using a 3D computer vision system to generate the reference trajectory to be followed and by using internal sensors to control its stability and its trajectory. The paper presents the results obtained so far: visual detection and tracking of the power cable, robust under changing environments, and robust stationary control of the helicopter, now linked to a safety mechanical platform. Finally this paper describes the future challenges of the project and its temporal milestones.

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Security refers to the perceptions about an environment protection, it means without worry of suffer harm. This research offers a literature review about security subject, focused on autonomous surveillance, gathering in a single document the technical novelties about surveillance systems, their applications, and central components. During this research , we observe that deep learning its being applied for surveillance purpose, opening new research horizons, in an area which does not have been significant changes during about ten years, and we also found that new vast datasets are being produced to solve issues regarding security. We have also seen that, in terms of security, deep learning is highly viable to solve problems that have been implicit in security systems for a long time, this being able to turn deep learning into a new breakthrough with respect to systems programmed only by traditional vision algorithms, opening the possibility of becoming a mandatory accessory for security of systems. This research has been limited only on civil area surveillance systems, also we only use scientific articles for this, avoiding commercial technologies.