Chapter 9 A SURVEY OF SYNOPSIS CONSTRUCTION IN DATA STREAMS Abstract The large volume of data streams poses unique space and time constraints on the computation process. Many query processing, database operations, and mining algorithms require efficient execution which can be difficult to achieve with a fast data stream. In many cases, it may be acceptable to generate approximate solutions for such problems. In recent years a number of synopsis structures have been developed, which can
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the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analysed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data. Descriptive statistics are very important because if we simply presented our raw data it would be hard to visulize what the data was showing, especially if there was a lot of it. Descriptive statistics therefore enables us to present the data in a more meaningful way, which allows
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Finding out the cause of sales-stickiness Of Times of India published Bengali news daily Ei Samay By Saswata Biswas June, 2015 Finding out the cause of sales-stickiness Of Times of India published Bengali news daily Ei Samay By Saswata Biswas Under the guidance of Shri Rupak Sengupta Dr. Soma Arora AGM,RMD Assistant Professor Times Group IMT, Ghaziabad June, 2015 Certificate of Approval The following Summer Project Report titled
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is primarily described through his relations to others, as if he doesn’t matter or even exist on his own. In a way this applies to everyone; our relations define us as people. Right from the beginning of his life, Nick’s mother had defined him as a very special boy. He grew accustomed to the special treatment and expected it from his peers as well when he began in school. Nick however, did not appear special, and so the other children took him for being conceited, and next thing he knew, Nick’s social
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high-frequency carrier that may be varied by a low-frequency intelligence signal. amplitude, frequency, and phase 5. What are the frequency ranges included in the following frequency subdivisions: MF (medium frequency), HF (high frequency), VHF (very high frequency), UHF (ultra high frequency), and SHF (super high frequency)? MF:300 kHz–3 MHz, 3-30MHz: HF, 30–300 MHz: VHF, 300 MHz–3 GHz: UHF, 3–30 GHz: SHF 7. A microwave transmitter typically requires a +8-dBm audio level to
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way.” This quote, said by the motivational speaker Les Brown, can very well be applied the children’s story The Very Hungry Caterpillar. The Very Hungry Caterpillar was written by the American designer and illustrator Eric Carle. The title of this book is very self-explanatory. It tells the story of a caterpillar who is just what the title says, very hungry. When looking through the archetypal lens, an individual who is reading The Very Hungry Caterpillar will discover that when there is a struggle
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and thus mean reverting. Studies mainly focus on autocorrelation of returns in different time lengths. In finance theory it says when autocorrelation of stock prices is there, then prices are predictable. Therefore, it is evidence against the random walk hypothesis of stock prices. Objective of the study The objective of this research is to test the efficiency of stock prices in Sri Lanka studying autocorrelation of short and long term returns in the CSE. Significance of the study
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Probability- long run relative frequency. The proportion of times the outcome would occur in a very long series of repetitions Law of large numbers- the long run frequency of repeated events eventually produces the true relative frequency. This is called the empirical probability or objective probability. When we can’t repeat events the probability of an event is called subjective or personal probability. If A and B are disjoint, P(A or B)= P(A) + P(B) General addition rule- P(A or B) = P(A) +
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ω(q): fω (x) = ln(10) 10(x+ΥMP, dB )/10 fΥMP 10(x+ΥMP, dB )/10 . 10 Some experimental measurements have also suggested Gaussian to be a good enough yet simple fit for the distribution of ω(q) [17]. We will take advantage of this Gaussian simplification later in our framework. As for the shadowing variable, log-normal is shown to be a good match for the distribution of ΥSH (q). Then, we have the following zero-mean Gaussian pdf 2 1 for the distribution of ν(q): fν (x) = √2πα e−x /2α , where α is the
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person in the technical area – what is the probability that it will go to an woman given that the worker is in the technical area? Is this discrimination against male technical workers? What factors might enter into the awarding of bonus other than random selection? d) What is the probability that a professional person will be a winner to Hawaii? e) What is the probability that the winner will be either a man or a clerical worker? f) What is the probability that the winner will be an woman
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