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Register a new userOrganizing Virtual Conferences through Mirrors: The ACM e-Energy 2020 Experience
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Added by
Dan Wang
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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The emergence of the world-wide COVID-19 pandemic has forced academic conferences to be held entirely in a virtual manner. While prior studies have advocated the merits of virtual conferences in terms of energy and cost savings, organizers are increasingly facing the prospect of planning and executing them systematically, in order to deliver a rich conference-attending-experience for all participants. Starting from March 2020, tens of conferences have been held virtually. Past conferences have revealed numerous challenges, from budget planning, to selecting the supporting virtual platforms. Among these, two special challenges were identified: 1) how to deliver talks to geo-distributed attendees and 2) how to stimulate social interactions among attendees. These are the two important goals of an academic conference. In this paper, we advocate a mirror program approach for academic conferences. More specifically, the conference program is executed in multiple parallel (mirrored) programs, so that each mirror program can fit a different time zone. This can effectively address the first challenge.
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The 15th European Conference on Computer Systems (EuroSys20) was organized as a virtual (online) conference on April 27-30, 2020. The main EuroSys20 track took place April 28-30, 2020, preceded by five workshops (EdgeSys20, EuroDW20, EuroSec20, PaPoC20, SPMA20) on April 27, 2020. The decision to hold a virtual (online) conference was taken in early April 2020, after consultations with the EuroSys community and internal discussions about potential options, eventually allowing about three weeks for the organization. This paper describes the choices we made to organize EuroSys20 as a virtual (online) conference, the challenges we addressed, and the lessons learned.
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Inclusive Astronomy 2 Local Organizing Committee: Brian Brooks
, Keiran Brooks
, Lea Hagen
2020
The Inclusive Astronomy (IA) conference series aims to create a safe space where community members can listen to the experiences of marginalized individuals in astronomy, discuss actions being taken to address inequities, and give recommendations to the community for how to improve diversity, equity, and inclusion in astronomy. The first IA was held in Nashville, TN, USA, 17-19 June, 2015. The Inclusive Astronomy 2 (IA2) conference was held in Baltimore, MD, USA, 14-15 October, 2019. The Inclusive Astronomy 2 (IA2) Local Organizing Committee (LOC) has put together a comprehensive document of recommendations for planning future Inclusive Astronomy conferences based on feedback received and lessons learned. While these are specific to the IA series, many parts will be applicable to other conferences as well. Please find the recommendations and accompanying letter to the community here: https://outerspace.stsci.edu/display/IA2/LOC+Recommendations.
The new ACM Code of Ethics is a much-needed update, but introduced changes to a central principle that have not been discussed widely enough. This commentary aims to contribute to an improvement of the ethical standards we want computing professionals to aspire to by analyzing how changes introduced to Principle 1.2, Avoid Harm, affect the Code as a whole. The analysis shows that the principle is now internally inconsistent in structure and externally inconsistent with Principle 2.3. It condones intentional harm too broadly and does not oblige those responsible to seek external justification. The existing Principle 2.3 clearly suggests that Principle 1.2 is unethical. As a consequence, the change introduced to Principle 1.2 in the new Code of Ethics nullifies the good intention of the code; counteracts the many good changes introduced in all three drafts; and places the ACM in a dangerous moral position. This short paper explains why and recommends concrete actions.
Virtual Reality (VR) games that feature physical activities have been shown to increase players motivation to do physical exercise. However, for such exercises to have a positive healthcare effect, they have to be repeated several times a week. To maintain player motivation over longer periods of time, games often employ Dynamic Difficulty Adjustment (DDA) to adapt the games challenge according to the players capabilities. For exercise games, this is mostly done by tuning specific in-game parameters like the speed of objects. In this work, we propose to use experience-driven Procedural Content Generation for DDA in VR exercise games by procedurally generating levels that match the players current capabilities. Not only finetuning specific parameters but creating completely new levels has the potential to decrease repetition over longer time periods and allows for the simultaneous adaptation of the cognitive and physical challenge of the exergame. As a proof-of-concept, we implement an initial prototype in which the player must traverse a maze that includes several exercise rooms, whereby the generation of the maze is realized by a neural network. Passing those exercise rooms requires the player to perform physical activities. To match the players capabilities, we use Deep Reinforcement Learning to adjust the structure of the maze and to decide which exercise rooms to include in the maze. We evaluate our prototype in an exploratory user study utilizing both biodata and subjective questionnaires.
We use sequential large-scale crawl data to empirically investigate and validate the dynamics that underlie the evolution of the structure of the web. We find that the overall structure of the web is defined by an intricate interplay between experience or entitlement of the pages (as measured by the number of inbound hyperlinks a page already has), inherent talent or fitness of the pages (as measured by the likelihood that someone visiting the page would give a hyperlink to it), and the continual high rates of birth and death of pages on the web. We find that the web is conservative in judging talent and the overall fitness distribution is exponential, showing low variability. The small variance in talent, however, is enough to lead to experience distributions with high variance: The preferential attachment mechanism amplifies these small biases and leads to heavy-tailed power-law (PL) inbound degree distributions over all pages, as well as over pages that are of the same age. The balancing act between experience and talent on the web allows newly introduced pages with novel and interesting content to grow quickly and surpass older pages. In this regard, it is much like what we observe in high-mobility and meritocratic societies: People with entitlement continue to have access to the best resources, but there is just enough screening for fitness that allows for talented winners to emerge and join the ranks of the leaders. Finally, we show that the fitness estimates have potential practical applications in ranking query results.
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