The Effectiveness of Feedback Control in a HCI System Using Biological Features of Human Beings

Author(s):  
Mariko Funada ◽  
Miki Shibukawa ◽  
Yoshihide Igarashi ◽  
Takashi Shimizu ◽  
Tadashi Funada ◽  
...  
Adeptus ◽  
2021 ◽  
Author(s):  
Magdalena Baer

The White Stork as a Linguistic Specimen, or Croatian-Polish Linguistic WanderingsThe analysis, presented in the article aims to present the white stork as a linguistic specimen, i.e. biological species as perceived through the prism of linguistic realisations, in this instance – in the Polish and Croatian languages. The linguistic specimen is closely connected with the linguistic picture of the world; however, in the chain that is the process of acquiring information by human beings of their surrounding reality, the specimen is an earlier link. The basics of definition of the linguistic specimen are linked to biological features that are extralinguistic, while in the linguistic picture of the world designations are linguistically and culturally transformed. The linguistic specimen can therefore be a more objective tool for describing linguistic reality in a more conscious fashion. Bocian biały jako okaz językowy, czyli polsko-chorwackie wędrówki lingwistyczneW artykule została zaprezentowana nowatorska koncepcja wprowadzająca pojęcie okazu językowego, czyli gatunku biologicznego, zjawiska przyrodniczego, fizycznego, chemicznego widzianego przez pryzmat realizacji językowych. Jako podstawę analizy przyjęto języki polski i chorwacki, a definicja okazu językowego została zaprezentowana na podstawie bardzo popularnego w Europie gatunku ptaka, jakim jest bocian biały (łac. Ciconia ciconia). Proponowane pojęcie jest ściśle powiązane z językowym obrazem świata, jednak może stanowić wobec niego wcześniejsze ogniwo w procesie pozyskiwania przez człowieka informacji przetwarzanych później w interpretacje językowe i kulturowe. Okaz językowy ma swoje źródło bezpośrednio w cechach desygnatu, ponieważ by go zdefiniować, korzysta z informacji pozajęzykowych.


2019 ◽  
Vol 4 (28) ◽  
pp. eaaw1975 ◽  
Author(s):  
Nathan A. Spielberg ◽  
Matthew Brown ◽  
Nitin R. Kapania ◽  
John C. Kegelman ◽  
J. Christian Gerdes

Automated vehicles navigate through their environment by first planning and subsequently following a safe trajectory. To prove safer than human beings, they must ultimately perform these tasks as well or better than human drivers across a broad range of conditions and in critical situations. We show that a feedforward-feedback control structure incorporating a simple physics-based model can be used to track a path up to the friction limits of the vehicle with performance comparable with a champion amateur race car driver. The key is having the appropriate model. Although physics-based models are useful in their transparency and intuition, they require explicit characterization around a single operating point and fail to make use of the wealth of vehicle data generated by autonomous vehicles. To circumvent these limitations, we propose a neural network structure using a sequence of past states and inputs motivated by the physical model. The neural network achieved better performance than the physical model when implemented in the same feedforward-feedback control architecture on an experimental vehicle. More notably, when trained on a combination of data from dry roads and snow, the model was able to make appropriate predictions for the road surface on which the vehicle was traveling without the need for explicit road friction estimation. These findings suggest that the network structure merits further investigation as the basis for model-based control of automated vehicles over their full operating range.


1954 ◽  
Vol 27 (5) ◽  
pp. 565-577 ◽  
Author(s):  
John F. Scholer ◽  
Charles F. Code

1949 ◽  
Vol 12 (6) ◽  
pp. 970-977 ◽  
Author(s):  
John M. McMahon ◽  
Charles F. Code ◽  
Willtam G. Saver ◽  
J. Arnold Bargen
Keyword(s):  

Author(s):  
Charles A. Doan ◽  
Ronaldo Vigo

Abstract. Several empirical investigations have explored whether observers prefer to sort sets of multidimensional stimuli into groups by employing one-dimensional or family-resemblance strategies. Although one-dimensional sorting strategies have been the prevalent finding for these unsupervised classification paradigms, several researchers have provided evidence that the choice of strategy may depend on the particular demands of the task. To account for this disparity, we propose that observers extract relational patterns from stimulus sets that facilitate the development of optimal classification strategies for relegating category membership. We conducted a novel constrained categorization experiment to empirically test this hypothesis by instructing participants to either add or remove objects from presented categorical stimuli. We employed generalized representational information theory (GRIT; Vigo, 2011b , 2013a , 2014 ) and its associated formal models to predict and explain how human beings chose to modify these categorical stimuli. Additionally, we compared model performance to predictions made by a leading prototypicality measure in the literature.


2015 ◽  
Vol 223 (3) ◽  
pp. 151-156 ◽  
Author(s):  
Nina Schweinfurth ◽  
Undine E. Lang

Abstract. In the development of new psychiatric drugs and the exploration of their efficacy, behavioral testing in mice has always shown to be an inevitable procedure. By studying the behavior of mice, diverse pathophysiological processes leading to depression, anxiety, and sickness behavior have been revealed. Moreover, laboratory research in animals increased at least the knowledge about the involvement of a multitude of genes in anxiety and depression. However, multiple new possibilities to study human behavior have been developed recently and improved and enable a direct acquisition of human epigenetic, imaging, and neurotransmission data on psychiatric pathologies. In human beings, the high influence of environmental and resilience factors gained scientific importance during the last years as the search for key genes in the development of affective and anxiety disorders has not been successful. However, environmental influences in human beings themselves might be better understood and controllable than in mice, where environmental influences might be as complex and subtle. The increasing possibilities in clinical research and the knowledge about the complexity of environmental influences and interferences in animal trials, which had been underestimated yet, question more and more to what extent findings from laboratory animal research translate to human conditions. However, new developments in behavioral testing of mice involve the animals’ welfare and show that housing conditions of laboratory mice can be markedly improved without affecting the standardization of results.


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