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compared to those sent on the weekend. Similarly, there are fewer email alerts on weekends; this is probably due to lower levels of work activity that occur on weekends relative to weekdays, resulting in fewer triggering events. For other categories, such as sports, weather, and horoscopes, the number of noti cation messages does not vary signi cantly from weekdays to weekends. We attribute these patterns to the fact that not many users personalize all aspects of their noti cation portfolio in a very ne-grained manner (for event types such as weather, the Web site allows users to select the frequency and the time of delivery). Message Popularity Analysis and Its Implications As described in Section 5.4, several studies on regular Web sites have shown that Web accesses follow a Zipf-like distribution. It is interesting to see whether noti cation messages exhibit a similar property. To study this, we take the following approach. For each noti cation document, we count the number of noti cation messages (i.e., copies) that were sent on a given day. We plot the total number of transmissions of a document (i.e., noti cation messages) versus the popularity ranking of the document on a log log scale. Figure 5.25 shows the plot for August 21, 2000. The plots for the other days are similar. If we ignore the rst few noti cation documents and the at tail in Figure 5.25 (as is done in the previous work [7,9,26]), we not that the curve ts a straight line reasonably well. The straight line on the log log scale implies that the noti cation documents follow a Zipf-like distribution. We compute the values of a using least-square tting, after excluding the top 20 documents and the at tail (the latter represents the noti cation documents that were sent only once or twice). We nd that for our complete dataset the value of a varies from 1.137 to 1.267 (in Fig. 5.25, the value of a is 1.146). These values are higher than the a in the Web proxy logs [9,14,24], and comparable to the a observed for popular Web server logs [26].
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Proof: We have 2 H (p) D(p||r) = 2 =2 =
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Strength of association: An average ES from several studies. Consistency: Effect seen in different places, by different people, at different times, and in different circumstances. Specificity: Limited to a single cause for a single effect, but if other criteria are met, lack of specificity is not a fatal f law. Temporal sequence: Does physical activity precede changes in mental health Dose-response gradient: Change in the dependent variable is dependent on increased dose or duration of exposure (e.g., exercise). Biological plausibility: Results are in harmony with understanding of the response to cells, tissues, organs, and organisms to stimuli. Coherence: Possible mechanisms should not conf lict with our understanding of the natural history and biology of mental illness. Experimental evidence: Several Grade A and B studies support the predicted relationship. Source: The Environment and Disease: Association or Causation by A. B. Hill, 1965, Proceedings of the Royal Society of Medicine, 58, pp. 295 300.
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Figure 9.8 In this diagram, a single unknown node with ranges to six different beacons localizes itself using multilateration. The ground truth position of the unknown node is circled. The X s mark the best estimate after each iteration of least squares, with darker shades indicating higher iterations.
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10.8 TOPOLOGY CONSTRUCTION AND CONNECTIVITY WITH CONSIDERATION OF FAULT TOLERANCE Since a wireless sensor network is usually composed of a large number of unreliable sensor nodes, fault tolerance is an important requirement for topology construction. In particular, the network connectivity should be preserved even when some of the sensor nodes fail or deplete their power. With the use of smaller transmission power, most topology control algorithms actually decrease the number of possible routing paths between any pair of nodes. The topology thus derived is more susceptible to node failure. For instance, if node v7 in Figure 10.3 fails, the network will be partitioned into three disconnected components. One way to construct fault-tolerant topology is to construct a k-vertex connected network. Note that a k-vertex connected network is k 2 1 fault-tolerant, that is, it can tolerate failure of at most k 2 1 nodes. A 3-vertex connected network is given in Figure 10.22. (For simplicity, the term k-connectivity is used to refer to k-vertex connectivity.) An alternate way to enhance fault tolerance in topology construction is to make data sinks or network controllers aware of critical nodes and links in the network, so that additional sensors can be woken up or deployed on demand in the network. A node is de ned to be critical if the subgraph of its p-hop neighbors (without the node itself) is disconnected [26]. Similar de nitions were given in ref. [26] for critical links. In this section, we rst discuss the properties of k-vertex connected topologies and present several algorithms that construct such topologies. Then we discuss localized algorithms that detect such nodes and links.
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print \n ; $label = $labels[ $num - 1 ]; if ($label) { $messages = $gmail->get_messages( label => $label ); labeled messages $id = 1; $num = 0; foreach ( @{$messages} ) { iterate through them print $id . \t . $_->{ sender_email } . \t . strip_bold( $_->{ subject } ) . \n ; message data $id++; }
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. . . .
exploit the fruitful possibilities he saw for a productive union of the two disciplines, his intellectual progeny, Harold Lasswell, was the rst to enter boldly into the psychological house of ill repute, establish a liaison, and sire a set of ideas and in uences of great vitality (p. 18). Machiavelli s famous treatise serves as testimony that, from the beginning, the study of personality in politics constituted an integral part of political-psychological inquiry. In the modern era, the tradition dates back to Sigmund Freud, who collaborated with William Bullitt on a psychological study of U.S. president Woodrow Wilson (Freud & Bullitt, 1967). Types of Personality-in-Politics Inquiry In examining the state of the personality-in-politics literature, Greenstein (1969) proposed three types of personalityin-politics inquiry: individual, typological, and aggregate. Individual inquiry (Greenstein, 1969, pp. 63 93), which is idiographic in orientation, involves single-case psychological analyses of individual political actors. Although the singlecase literature historically comprised mostly psychological biographies of public gures, such as Alexander and Juliette George s Woodrow Wilson and Colonel House (1956) and Erik Erikson s Gandhi s Truth (1969), it also encompassed in-depth studies of members of the general population, such as Robert Lane s Political Ideology (1962). With increasing specialization in political psychology since the 1960s, the focus has shifted progressively to the psychological examination of political leaders, while single-case studies of ordinary citizens have become increasingly peripheral to the main focus of contemporary political personality research. Typological inquiry (Greenstein, 1969, pp. 94 119), which is nomothetic in orientation, concerns multicase analyses of political actors. This line of inquiry encompasses the main body of work in political personality, including the in uential work of Harold Lasswell (1930, 1948), James David Barber (1965, 1972/1992), Margaret Hermann (1974, 1980, 1986, 1987), and David Winter (1987, 1998) with respect to high-level political leaders; however, part of this literature focuses more on followers (i.e., mass politics) than on leaders (i.e., elite politics) for example, Theodor Adorno, Else Frenkel-Brunswik, Daniel Levinson, and Nevitt Sanford s classic The Authoritarian Personality (1950) and Milton Rokeach s The Open and Closed Mind (1960). Greenstein (1992) has submitted that typological study is of potentially great importance: if political actors fall into types with known characteristics and propensities, the laborious task of analyzing them de novo can be obviated, and uncertainty is reduced about how they will perform in particular circumstances (p. 120).
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