SCARA motako robot industrialaren simulazio birtuala eta interakzioa

[EU]Gradu amaierako lan honetan, Industria Ingenieritza graduan zehar emandako zenbait irakasgaietan landutako kontzeptuak oinarri bezala hartuta SCARA robot industrialaren analisia egin da. Lau askatasun gradu dituzten robot hauek oso erabiliak dira industrian beraien lan ziklo azkar, karga handiak jasateko kapazitate, errepikortasun eta aplikazio ugariengatik. Proiektua, bi zati nagusitan banandu da: SCARA motako robot baten analisi zinematikoa, robotaren irudikapena eta ibilbideen sorkuntza Matlab programa erabiliz. Adept Cobra e-Vario 600, SCARA motako prototipo errealarekin interakzioa. Proiektuan zehar garatuko diren edukien egitura ondorengoa izango da: Lehenik eta behin, proiektuko lehen atalean proiektua kokatuta dagoen testuinguruaren azalpena emango da, baita ere testuinguru horrek gaur egun, sail desberdinetan, duen garrantzia. Proiektuko bigarren atalean, lana egiterakoan proposatu diren helburuak eta proiektuak eskaintzen dituen onurak adieraziko dira. Bestetik, proiektuko hirugarren atalean, gaiaren egoeran, SCARA robotera heldu arte robotek historian zehar izan duten garapena eta hauen sailkapen desberdinak azalduko dira. Laugarren atalean, metodologian, proiektu honetan garatuko diren bi zati nagusien deskribapen zehatza emango da. Azkenik, proiektuko azken atalean, lana burutzeko bete behar izan diren ataza bakoitzaren deskribapena eta iraupena, aurrekontua, arriskuen analisia eta proiektu honetatik atera ditugun ondorioak ematen dira.

Is there a subgroup of long-term evolution among patients with advanced lung cancer?: Hints from the analysis of survival curves from cancer registry data

Background: Recently, with the access of low toxicity biological and targeted therapies, evidence of the existence of a long-term survival subpopulation of cancer patients is appearing. We have studied an unselected population with advanced lung cancer to look for evidence of multimodality in survival distribution, and estimate the proportion of long-term survivors. Methods: We used survival data of 4944 patients with non-small-cell lung cancer (NSCLC) stages IIIb-IV at diagnostic, registered in the National Cancer Registry of Cuba (NCRC) between January 1998 and December 2006. We fitted one-component survival model and two-component mixture models to identify short-and long-term survivors. Bayesian information criterion was used for model selection. Results: For all of the selected parametric distributions the two components model presented the best fit. The population with short-term survival (almost 4 months median survival) represented 64% of patients. The population of long-term survival included 35% of patients, and showed a median survival around 12 months. None of the patients of short-term survival was still alive at month 24, while 10% of the patients of long-term survival died afterwards. Conclusions: There is a subgroup showing long-term evolution among patients with advanced lung cancer. As survival rates continue to improve with the new generation of therapies, prognostic models considering short-and long-term survival subpopulations should be considered in clinical research.

Trend analysis in two standard growth models

This paper analyzes the trend processes characterized by two standard growth models using simple econometrics. The first model is the basic neoclassical growth model that postulates a deterministic trend for output. The second model is the Uzawa-Lucas model that postulates a stochastic trend for output. The aim is to understand how the different trend processes for output assumed by these two standard growth models determine the ability of each model to explain the observed trend processes of other macroeconomic variables such as consumption and investment. The results show that the two models reproduce the output trend process. Moreover, the results show that the basic growth model captures properly the consumption trend process, but fails in characterizing the investment trend process. The reverse is true for the Uzawa-Lucas model.

Failure detectors and communication efficiency in the crash and general omisión failure models

122 p.

On some new mathematical models for infective diseases: analysis, equilibrium, positivity and vaccination controls

196 p.

Stability analysis and observer design for discrete-time SEIR epidemic models

This paper applies Micken's discretization method to obtain a discrete-time SEIR epidemic model. The positivity of the model along with the existence and stability of equilibrium points is discussed for the discrete-time case. Afterwards, the design of a state observer for this discrete-time SEIR epidemic model is tackled. The analysis of the model along with the observer design is faced in an implicit way instead of obtaining first an explicit formulation of the system which is the novelty of the presented approach. Moreover, some sufficient conditions to ensure the asymptotic stability of the observer are provided in terms of a matrix inequality that can be cast in the form of a LMI. The feasibility of the matrix inequality is proved, while some simulation examples show the operation and usefulness of the observer.