Economic benefit of the National Broadband Network

This paper argues that all regions benefit from the NBN but the economic effects are greater in the major cities because of their larger economic activity. Executive summary This paper is a partial summary of a study undertaken in the Centre for Energy-Efficient Telecommunications (CEET) at the University of Melbourne. The study focuses on the potential economic impact of Australia’s NBN. The NBN affects the economy by making online services more widely available. Taking a conservative approach, we have considered just six categories of online services (cloud computing, electronic commerce, online higher education, telehealth practice, teleworking, and entertainment) from which there are documented economic benefits. We have attributed to the NBN only the additional benefit derived from its deployment over and above what we estimate would have been the broadband situation in Australia without the NBN. That is, we have not assumed that broadband availability would have stagnated without the NBN. We do expect, however, that future services will require higher access speeds, generally in the range 10-25 Mb/s. With this assumption and using a well-attested model of the Australian economy, we show that, in the long term, real GDP can be boosted by about 1.8% and real household consumption (a measure of national welfare) by about 2.0%. When we take into account the need to repay the cost of the NBN, GDP increases slightly but the benefit to real household consumption is reduced to 1.4%. Most of the benefit comes from telehealth and teleworking. Because the access speeds (downstream and upstream) required for the services are quite uncertain, we have looked at the effects of access speeds. If all the services except entertainment can be provided with no more than 2.5 Mb/s down and up (typical of implementations today), then the costs of the NBN outweigh the benefits. Real GDP increases by less than 0.2% but real household consumption declines by 0.4%. That is, building an NBN just for entertainment is not economically viable. An analysis of the regional distribution of benefits shows that all regions benefit from the NBN but the economic effects are greater in the major cities because of their larger economic activity

Using Bad Learners to find Good Configurations

Finding the optimally performing configuration of a software system for a given setting is often challenging. Recent approaches address this challenge by learning performance models based on a sample set of configurations. However, building an accurate performance model can be very expensive (and is often infeasible in practice). The central insight of this paper is that exact performance values (e.g. the response time of a software system) are not required to rank configurations and to identify the optimal one. As shown by our experiments, models that are cheap to learn but inaccurate (with respect to the difference between actual and predicted performance) can still be used rank configurations and hence find the optimal configuration. This novel \emph{rank-based approach} allows us to significantly reduce the cost (in terms of number of measurements of sample configuration) as well as the time required to build models. We evaluate our approach with 21 scenarios based on 9 software systems and demonstrate that our approach is beneficial in 16 scenarios; for the remaining 5 scenarios, an accurate model can be built by using very few samples anyway, without the need for a rank-based approach.Comment: 11 pages, 11 figure

Strongly Refuting Random CSPs Below the Spectral Threshold

Random constraint satisfaction problems (CSPs) are known to exhibit threshold phenomena: given a uniformly random instance of a CSP with $n$ variables and $m$ clauses, there is a value of $m = \Omega(n)$ beyond which the CSP will be unsatisfiable with high probability. Strong refutation is the problem of certifying that no variable assignment satisfies more than a constant fraction of clauses; this is the natural algorithmic problem in the unsatisfiable regime (when $m/n = \omega(1)$). Intuitively, strong refutation should become easier as the clause density $m/n$ grows, because the contradictions introduced by the random clauses become more locally apparent. For CSPs such as $k$-SAT and $k$-XOR, there is a long-standing gap between the clause density at which efficient strong refutation algorithms are known, $m/n \ge \widetilde O(n^{k/2-1})$, and the clause density at which instances become unsatisfiable with high probability, $m/n = \omega (1)$. In this paper, we give spectral and sum-of-squares algorithms for strongly refuting random $k$-XOR instances with clause density $m/n \ge \widetilde O(n^{(k/2-1)(1-\delta)})$ in time $\exp(\widetilde O(n^{\delta}))$ or in $\widetilde O(n^{\delta})$ rounds of the sum-of-squares hierarchy, for any $\delta \in [0,1)$ and any integer $k \ge 3$. Our algorithms provide a smooth transition between the clause density at which polynomial-time algorithms are known at $\delta = 0$, and brute-force refutation at the satisfiability threshold when $\delta = 1$. We also leverage our $k$-XOR results to obtain strong refutation algorithms for SAT (or any other Boolean CSP) at similar clause densities. Our algorithms match the known sum-of-squares lower bounds due to Grigoriev and Schonebeck, up to logarithmic factors. Additionally, we extend our techniques to give new results for certifying upper bounds on the injective tensor norm of random tensors

Measured unsteady transonic aerodynamic characteristics of an elastic supercritical wing with an oscillating control surface

Transonic steady and unsteady aerodynamic data were measured on a large elastic wing in the NASA Langley Transonic Dynamics Tunnel. The wing had a supercritical airfoil shape and a leading-edge sweepback of 28.8 deg. The wing was heavily instrumented to measure both static and dynamic pressures and deflections. A hydraulically driven outboard control surface was oscillated to generate unsteady airloads on the wing. Representative results from the wind tunnel tests are presented and discussed, and the unexpected occurrence of an unusual dynamic wing instability, which was sensitive to angle of attack, is reported

CMU-Penn T-SET UTC Researcher Creates Smarter Parking in Pittsburgh

The Technologies for Safe and Efficient Transportation (T-SET) UTC, a partnership between Carnegie Mellon University (CMU) and the University of Pennsylvania, is working to increase both efficiency and safety in transportation using advanced intelligent transportation systems (ITS) technologies. One of T-SET's recent award-winning collaborations is the ParkPGH project\u2014a smart parking system that uses historical parking and event data to show the availability of parking in eight parking facilities operated by private (Alco Parking) and public (Pittsburgh Parking Authority) partners within the Pittsburgh cultural district

FERSC Data Management Plan

FERSC is a Tier 1 University Transportation Center consortium led by the University of Tennessee, Knoxville. Its focus is the Infrastructure Investment and Jobs Act (IIJA)\u2019s research priority, Improving Mobility of People and Goods as its primary area. The consortium supports the DOT Strategic Goals of Economic Strength and Global Competitiveness as the primary focus and Equity and Transformation as the secondaries

Overlapping Community Discovery Methods: A Survey

The detection of overlapping communities is a challenging problem which is gaining increasing interest in recent years because of the natural attitude of individuals, observed in real-world networks, to participate in multiple groups at the same time. This review gives a description of the main proposals in the field. Besides the methods designed for static networks, some new approaches that deal with the detection of overlapping communities in networks that change over time, are described. Methods are classified with respect to the underlying principles guiding them to obtain a network division in groups sharing part of their nodes. For each of them we also report, when available, computational complexity and web site address from which it is possible to download the software implementing the method.Comment: 20 pages, Book Chapter, appears as Social networks: Analysis and Case Studies, A. Gunduz-Oguducu and A. S. Etaner-Uyar eds, Lecture Notes in Social Networks, pp. 105-125, Springer,201