2263 본문읽기 10
카테고리 없음2023. 5. 13. 20:47
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2263-23
Considerable work by cultural psychologists and anthropologists has shown that there are indeed large and sometimes surprising differences in the words and concepts that different cultures have for describing emotions, as well as in the social circumstances that draw out the expression of particular emotions. However, those data do not actually show that different cultures have different emotions, if we think of emotions as central, neutrally implemented states. As for, say, color vision, they just say that, despite the same internal processing architecture, how we interpret, categorize, and name emotions varies according to culture and that we learn in a particular culture the social context in which it is appropriate to express emotions. However, the emotional states themselves are likely to be quite invariant across cultures. In a sense, we can think of a basic, culturally universal emotion set that is shaped by evolution and implemented in the brain, but the links between such emotional states and stimuli, behavior, and other cognitive states are plastic and can be modified by learning in a specific cultural context.
2263-24
The approach, joint cognitive systems, treats a robot as part of a human-machine team where the intelligence is synergistic, arising from the contributions of each agent. The team consists of at least one robot and one human and is often called a mixed team because it is a mixture of human and robot agents. Self-driving cars, where a person turns on and off the driving, is an example of a joint cognitive system. Entertainment robots are examples of mixed teams as are robots for telecommuting. The design process concentrates on how the agents will cooperate and coordinate with each other to accomplish the team goals. Rather than treating robots as peer agents with their own completely independent agenda, joint cognitive systems approaches treat robots as helpers such as service animals or sheep dogs. In joint cognitive system designs, artificial intelligence is used along with human-robot interaction principles to create robots that can be intelligent enough to be good team members.
2263-25
The above tables show the resident patent applications per million population for the top 6 origins in 2009 and in 2019. The Republic of Korea, Japan, and Switzerland, the top three origins in 2009, maintained their rankings in 2019. Germany, which sat fourth on the 2009 list with 891 resident patent applications per million population, fell to fifth place on the 2019 list with 884 resident patent applications per million population. The U.S. fell from fifth place on the 2009 list to sixth place on the 2019 list, showing an increase in the number of resident patent applications per million population. Among the top 6 origins which made the list in 2009, Finland was the only origin which did not make it again in 2019. On the other hand, China, which did not make the list of the top 6 origins in 2009, sat fourth on the 2019 list with 890 resident patent applications per million population.
2263-26
William Buckland (1784-1856) was well known as one of the greatest geologists in his time. His birthplace, Axminster in Britain, was rich with fossils, and as a child, he naturally became interested in fossils while collecting them. In 1801, Buckland won a scholarship and was admitted to Corpus Christi College, Oxford. He developed his scientific knowledge there while attending John Kidd's lectures on mineralogy and chemistry. After Kidd resigned his position, Buckland was appointed his successor at the college. Buckland used representative samples and large-scale geological maps in his lectures, which made his lectures more lively. In 1824, he announced the discovery of the bones of a giant creature, and he named it Megalosaurus, or 'great lizard'. He won the prize from the Geological Society due to his achievements in geology.
2263-29
Ecosystems differ in composition and extent. They can be defined as ranging from the communities and interactions of organisms in your mouth or those in the canopy of a rain forest to all those in Earth's oceans. The processes governing them differ in complexity and speed. There are systems that turn over in minutes, and there are others whose rhythmic time extends to hundreds of years. Some ecosystems are extensive ('biomes', such as the African savanna); some cover regions (river basins); many involve clusters of villages (micro-watersheds); others are confined to the level of a single village (the village pond). In each example there is an element of indivisibility. Divide an ecosystem into parts by creating barriers, and the sum of the productivity of the parts will typically be found to be lower than the productivity of the whole, other things being equal. The mobility of biological populations is a reason. Safe passages, for example, enable migratory species to survive.
Considerable work by cultural psychologists and anthropologists has shown that there are indeed large and sometimes surprising differences in the words and concepts that different cultures have for describing emotions, as well as in the social circumstances that draw out the expression of particular emotions. However, those data do not actually show that different cultures have different emotions, if we think of emotions as central, neutrally implemented states. As for, say, color vision, they just say that, despite the same internal processing architecture, how we interpret, categorize, and name emotions varies according to culture and that we learn in a particular culture the social context in which it is appropriate to express emotions. However, the emotional states themselves are likely to be quite invariant across cultures. In a sense, we can think of a basic, culturally universal emotion set that is shaped by evolution and implemented in the brain, but the links between such emotional states and stimuli, behavior, and other cognitive states are plastic and can be modified by learning in a specific cultural context.
2263-24
The approach, joint cognitive systems, treats a robot as part of a human-machine team where the intelligence is synergistic, arising from the contributions of each agent. The team consists of at least one robot and one human and is often called a mixed team because it is a mixture of human and robot agents. Self-driving cars, where a person turns on and off the driving, is an example of a joint cognitive system. Entertainment robots are examples of mixed teams as are robots for telecommuting. The design process concentrates on how the agents will cooperate and coordinate with each other to accomplish the team goals. Rather than treating robots as peer agents with their own completely independent agenda, joint cognitive systems approaches treat robots as helpers such as service animals or sheep dogs. In joint cognitive system designs, artificial intelligence is used along with human-robot interaction principles to create robots that can be intelligent enough to be good team members.
2263-25
The above tables show the resident patent applications per million population for the top 6 origins in 2009 and in 2019. The Republic of Korea, Japan, and Switzerland, the top three origins in 2009, maintained their rankings in 2019. Germany, which sat fourth on the 2009 list with 891 resident patent applications per million population, fell to fifth place on the 2019 list with 884 resident patent applications per million population. The U.S. fell from fifth place on the 2009 list to sixth place on the 2019 list, showing an increase in the number of resident patent applications per million population. Among the top 6 origins which made the list in 2009, Finland was the only origin which did not make it again in 2019. On the other hand, China, which did not make the list of the top 6 origins in 2009, sat fourth on the 2019 list with 890 resident patent applications per million population.
2263-26
William Buckland (1784-1856) was well known as one of the greatest geologists in his time. His birthplace, Axminster in Britain, was rich with fossils, and as a child, he naturally became interested in fossils while collecting them. In 1801, Buckland won a scholarship and was admitted to Corpus Christi College, Oxford. He developed his scientific knowledge there while attending John Kidd's lectures on mineralogy and chemistry. After Kidd resigned his position, Buckland was appointed his successor at the college. Buckland used representative samples and large-scale geological maps in his lectures, which made his lectures more lively. In 1824, he announced the discovery of the bones of a giant creature, and he named it Megalosaurus, or 'great lizard'. He won the prize from the Geological Society due to his achievements in geology.
2263-29
Ecosystems differ in composition and extent. They can be defined as ranging from the communities and interactions of organisms in your mouth or those in the canopy of a rain forest to all those in Earth's oceans. The processes governing them differ in complexity and speed. There are systems that turn over in minutes, and there are others whose rhythmic time extends to hundreds of years. Some ecosystems are extensive ('biomes', such as the African savanna); some cover regions (river basins); many involve clusters of villages (micro-watersheds); others are confined to the level of a single village (the village pond). In each example there is an element of indivisibility. Divide an ecosystem into parts by creating barriers, and the sum of the productivity of the parts will typically be found to be lower than the productivity of the whole, other things being equal. The mobility of biological populations is a reason. Safe passages, for example, enable migratory species to survive.
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