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The portal thing doesn’t have much thematic backbone, but it’s a good excuse for very creative and clever gimmicks – just when you think the episode has run out of ideas, it reveals another, in the form of a joke or an action beat or both. There’s no denying that, as weird as this is, the sincerity both ideas are treated with helps to elevate the entire episode. The second is that Morty, thanks to an accident with a portal gun, ends up with a portal on his hand that connects to one in the leg of a guy named Nick, whom he springs from an asylum for a spiteful anti-Rick adventure. The first is that Rick, thanks to a wheel of random things he could theoretically replace Morty with, replaces his grandson with two crows who teach him not only about empathy but a dense hierarchy of crow society and history, which Rick becomes rather taken with, realizing, in the process, that his relationship with Morty has historically been predicated almost entirely on abuse and exploitation. “Forgetting Sarick Mortshall” feels more like classic Rick and Morty fare, with a pointless argument about Morty’s usefulness spinning out into a couple of deranged ideas. By and large, and taken together, I think the two work as a fun outing of Rick and Morty, but I’m not sure they do as any kind of meaningful coda to such a bizarrely inconsistent season. Both are peppered with funny gags, some clever ideas, and some cool visuals, but even the worst episodes have those things. The whole thing’s a mess of contradictions and mixed messages making us wait a month for the two-part finale just seemed like further proof that the audience getting to enjoy the episodes is something of an afterthought.Įven the finale barely resembles one, comprising two episodes, “Forgetting Sarick Mortshall” and “Rickmurai Jack”, that are kind of connected through a plot thread but don’t have much resemblance to one another, thematically. You love its enthusiastic rejection of formulaic storytelling norms and then realize in some instances it’d work better for abiding by them you want the grand madness of a constantly escalating sci-fi premise until you realize it’s too convoluted and out-there for any actual drama to exist within it. This season of Rick and Morty has had its fair share of ups and downs, and sometimes it’s difficult to know what to even make of the show, let alone where to stand on it. This recap of the Rick and Morty Season 5 finale, two episodes titled “Forgetting Sarick Mortshall” and “Rickmurai Jack”, contains spoilers. Rick and Morty’s fifth season bows out with a two-parter that challenges some of the show’s long-held ideas, even if it can’t quite escape its newfound inconsistency. What is the most common neurological disorder? It can also be used to confirm brain death. The test is used to help diagnose conditions such as seizures, epilepsy, head injuries, dizziness, headaches, brain tumors and sleeping problems. Many normal variants and artifacts can look like epileptiform discharges to neurologists who are inexperienced in reading EEG.Īn electroencephalogram (EEG) is a noninvasive test that records electrical patterns in your brain. “If you are not experienced in looking at, you will overread and think that everything is abnormal,” said Dr. Slowing may be intermittent or persistent, with more persistent or consistently slower activity generally indicating more severe underlying focal cerebral dysfunction. What does slow brain waves on an EEG mean?įocal slow wave activity on the EEG is indicative of focal cerebral pathology of the underlying brain region. What do seizure spikes look like on EEG?.
This trend has earned pattern recognition a central place in research and engineering applications. Technological advances in our society have enhanced industrial production automation and the need for handling information in fields of great importance. Received: March 23rd 2012 Accepted: March 12th 2013 Palabras clave: Algoritmos Genéticos, Vector De Características, Redes Neuronales, Reconocimiento de Patrones. Los resultados obtenidos muestran un mejor desempeño del sistema propuesto frente a otros métodos. La red neuronal se compara con el clasificador de los k-vecinos. Se implementan redes neuronales en la clasificación usando las características seleccionadas por el algoritmo genético. Para evaluar la propuesta con algoritmos genéticos se utilizan dos funciones de evaluación: tasa de error y coeficiente Kappa. En el siguiente artículo se presenta un enfoque para selección de características utilizando un algoritmo genético aplicado a procesos de reconocimiento y control de calidad en imágenes. Keywords: Feature vector, genetic algorithm, neural network, pattern recognition.Įl desempeño en el reconocimiento de patrones depende de las variaciones en las etapas de extracción, selección y clasificación. The proposed approach performed better than the other methods. The neural network approach was compared to a K-nearest neighbour classifier. Error rate and kappa coefficient were used for evaluating the genetic algorithm approach Neural networks were used for classification, involving the features selected by the genetic algorithms. This paper presents an approach to feature selection by using genetic algorithms with regard to digital image recognition and quality control. Pattern recognition performance depends on variations during extraction, selection and classification stages. G., Using genetic algorithm feature selection in neural classification systems for image pattern recognition., Ingeniería e Investigación. Affiliation: Full time professor in the Electrical and Electronics Engineering Department and Program Coordinator for the Master's degree in Electronics Engineering at Universidad del Norte, Barranquilla (Colombia). Tecnologías de la Información, Universidad de Girona. Electronics and Telecommunications Research Group Coordinator, Universidad Autónoma del Caribe, Barranquilla (Colombia). Affiliation: Lecturer in the Electrical and Electronics Engineering Department, Universidad del Norte. Ingeniería Electrónica - Ingeniería Eléctrica Universidad del Norte. Ingeniería Electrónica Universidad del Norte. 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