A computer consist of: ?->(Show Answer!)

1. A computer consist of:

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MCQ-> Read the given passage carefully and select the best answer to each question out of the four given alternatives. Computers have become indispensable in the modern times. From information to having fun, you can possibly do everything with the help of this amazing machine. For the modern day child, computers are vital and the amount of time that they devote on them has constantly been on the rise. One of the most popular things with children when it comes to the computer are video games or the computer games. From puzzles to racing, action to sports, strategy to adventure, computer games are possibly the biggest addiction with most children. With companies such as Sony and Microsoft going all out to promote Xbox and Playstation to children worldwide, the allure to these games has only got better. These video games not only help in making child's brain sharper through mental stimulation but it also helps relieve them of anxiety or pain. In some cases, games have proved to aid in dyslexic kids reading better. Since adults also love playing games, it can be a time of bonding between adults and children, increasing the amount of time spent together especially when time spent by parents and children is very less nowadays. On the other hand, the addiction to these computer games can severely harm the child. Since children keep on playing for long hours, it can lead to eye damage. The impact of excessive visual medium is evident as a large number of children these days start wearing spectacles from an early age. Long hours of playing computer games can also result in headaches and dizziness.One of the most popular things with children when it comes to the computer?
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MCQ-> Read the passage carefully and answer the given questionsThe complexity of modern problems often precludes any one person from fully understanding them. Factors contributing to rising obesity levels, for example, include transportation systems and infrastructure, media, convenience foods, changing social norms, human biology and psychological factors. . . . The multidimensional or layered character of complex problems also undermines the principle of meritocracy: the idea that the ‘best person’ should be hired. There is no best person. When putting together an oncological research team, a biotech company such as Gilead or Genentech would not construct a multiple-choice test and hire the top scorers, or hire people whose resumes score highest according to some performance criteria. Instead, they would seek diversity. They would build a team of people who bring diverse knowledge bases, tools and analytic skills. . . .Believers in a meritocracy might grant that teams ought to be diverse but then argue that meritocratic principles should apply within each category. Thus the team should consist of the ‘best’ mathematicians, the ‘best’ oncologists, and the ‘best’ biostatisticians from within the pool. That position suffers from a similar flaw. Even with a knowledge domain, no test or criteria applied to individuals will produce the best team. Each of these domains possesses such depth and breadth, that no test can exist. Consider the field of neuroscience. Upwards of 50,000 papers were published last year covering various techniques, domains of enquiry and levels of analysis, ranging from molecules and synapses up through networks of neurons. Given that complexity, any attempt to rank a collection of neuroscientists from best to worst, as if they were competitors in the 50-metre butterfly, must fail. What could be true is that given a specific task and the composition of a particular team, one scientist would be more likely to contribute than another. Optimal hiring depends on context. Optimal teams will be diverse.Evidence for this claim can be seen in the way that papers and patents that combine diverse ideas tend to rank as high-impact. It can also be found in the structure of the so-called random decision forest, a state-of-the-art machine-learning algorithm. Random forests consist of ensembles of decision trees. If classifying pictures, each tree makes a vote: is that a picture of a fox or a dog? A weighted majority rules. Random forests can serve many ends. They can identify bank fraud and diseases, recommend ceiling fans and predict online dating behaviour. When building a forest, you do not select the best trees as they tend to make similar classifications. You want diversity. Programmers achieve that diversity by training each tree on different data, a technique known as bagging. They also boost the forest ‘cognitively’ by training trees on the hardest cases - those that the current forest gets wrong. This ensures even more diversity and accurate forests.Yet the fallacy of meritocracy persists. Corporations, non-profits, governments, universities and even preschools test, score and hire the ‘best’. This all but guarantees not creating the best team. Ranking people by common criteria produces homogeneity. . . . That’s not likely to lead to breakthroughs.Which of the following conditions, if true, would invalidate the passage’s main argument?
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MCQ->A computer consist of:....