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Register a new userLearning to Drive on the Wrong Side of the Road: How American Computing Came to Rely on Conferences for Primary Publication
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Added by
Elijah Bouma-Sims
Publication date
2021
fields
Informatics Engineering
and research's language is
English
Authors
Elijah Bouma-Sims
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In contrast to other fields where conferences are typically for less polished or in-progress research, computing has long relied on referred conference papers as a venue for the final publication of completed research. While frequently a topic of informal discussion, debates about its efficacy, or library science research, the development of this phenomena has not been historically analyzed. This paper presents the first systematic investigation of the development of modern computing publications. It relies on semi-structured interviews with eight computing professors from diverse backgrounds to understand how researchers experienced changes in publication culture over time. Ultimately, the article concludes that the early presence of non-academic practitioners in research and a degree of path dependenceor a tendency to continue on the established path rather than the most economically optimal one allowed conferences to gain and hold prominence as the field exploded in popularity during the 1980s.
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On social media platforms, like Twitter, users are often interested in gaining more influence and popularity by growing their set of followers, aka their audience. Several studies have described the properties of users on Twitter based on static snapshots of their follower network. Other studies have analyzed the general process of link formation. Here, rather than investigating the dynamics of this process itself, we study how the characteristics of the audience and follower links change as the audience of a user grows in size on the road to users popularity. To begin with, we find that the early followers tend to be more elite users than the late followers, i.e., they are more likely to have verified and expert accounts. Moreover, the early followers are significantly more similar to the person that they follow than the late followers. Namely, they are more likely to share time zone, language, and topics of interests with the followed user. To some extent, these phenomena are related with the growth of Twitter itself, wherein the early followers tend to be the early adopters of Twitter, while the late followers are late adopters. We isolate, however, the effect of the growth of audiences consisting of followers from the growth of Twitters user base itself. Finally, we measure the engagement of such audiences with the content of the followed user, by measuring the probability that an early or late follower becomes a retweeter.
We analyse the famous Baxters $T-Q$ equations for $XXX$ ($XXZ$) spin chain and show that apart from its usual polynomial (trigonometric) solution, which provides the solution of Bethe-Ansatz equations, there exists also the second solution which should corresponds to Bethe-Ansatz beyond $N/2$. This second solution of Baxters equation plays essential role and together with the first one gives rise to all fusion relations.
With the rapid evolution of cross-strait situation, Mainland China as a subject of social science study has evoked the voice of Rethinking China Study among intelligentsia recently. This essay tried to apply an automatic content analysis tool (CATAR) to the journal Mainland China Studies (1998-2015) in order to observe the research trends based on the clustering of text from the title and abstract of each paper in the journal. The results showed that the 473 articles published by the journal were clustered into seven salient topics. From the publication number of each topic over time (including volume of publications, percentage of publications), there are two major topics of this journal while other topics varied over time widely. The contribution of this study includes: 1. We could group each independent study into a meaningful topic, as a small scale experiment verified that this topic clustering is feasible. 2. This essay reveals the salient research topics and their trends for the Taiwan journal Mainland China Studies. 3. Various topical keywords were identified, providing easy access to the past study. 4. The yearly trends of the identified topics could be viewed as signature of future research directions.
Rapidly oscillating Ap stars consitute a unique class of pulsators to study nonradial oscillations under some - even for stars - unusual physical conditions. These stars are chemically peculiar, they have strong magnetic fields, and they often pulsate in several high-order acoustic modes simultaneously. We discuss here an excitation mechanism for short-period oscillation modes based on the classical kappa mechanism. We particularly stress the conditions that must be fulfilled for successful driving. Specifically, we discuss the roles of chemical peculiarity and strong magnetic field on the oscillation modes and what separates these pulsators from delta Scuti and Am-type stars.
Given a sequence of possibly sparse and noisy GPS traces and a map of the road network, map matching algorithms can infer the most accurate trajectory on the road network. However, if the road network is wrong (for example due to missing or incorrectly mapped roads, missing parking lots, misdirected turn restrictions or misdirected one-way streets) standard map matching algorithms fail to reconstruct the correct trajectory. In this paper, an algorithm to tracking vehicles able to move both on and off the known road network is formulated. It efficiently unifies existing hidden Markov model (HMM) approaches for map matching and standard free-space tracking methods (e.g. Kalman smoothing) in a principled way. The algorithm is a form of interacting multiple model (IMM) filter subject to an additional assumption on the type of model interaction permitted, termed here as semi-interacting multiple model (sIMM) filter. A forward filter (suitable for real-time tracking) and backward MAP sampling step (suitable for MAP trajectory inference and map matching) are described. The framework set out here is agnostic to the specific tracking models used, and makes clear how to replace these components with others of a similar type. In addition to avoiding generating misleading map matching trajectories, this algorithm can be applied to learn map features by detecting unmapped or incorrectly mapped roads and parking lots, incorrectly mapped turn restrictions and road directions.
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