Understanding Algorithm Performance on an Oversubscribed Scheduling Application

The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet, through careful experimentation and modeling of performance in real problem instances, we can relate characteristics of the best algorithms to characteristics of the application. In particular, we find that plateaus dominate the search spaces (thus favoring algorithms that make larger changes to solutions) and that some randomization in exploration is critical to good performance (due to the lack of gradient information on the plateaus). Based on our explanations of algorithm performance, we develop a new algorithm that combines characteristics of the best performers; the new algorithms performance is better than the previous best. We show how hypothesis driven experimentation and search modeling can both explain algorithm performance and motivate the design of a new algorithm

Shock-Driven Periodic Variability in a Low-Mass-Ratio Supermassive Black Hole Binary

We investigate the time-varying electromagnetic emission of a low-mass-ratio supermassive black hole binary (SMBHB) embedded in a circumprimary disk, with a particular interest in variability of shocks driven by the binary. We perform a 2D, locally isothermal hydrodynamics simulation of a SMBHB with mass ratio $q=0.01$ and separation $a=100\;R_g$, using a physically self-consistent steady disk model. We estimate the electromagnetic variability from the system by monitoring accretion onto the secondary and using an artificial viscosity scheme to capture shocks and monitor the energy dissipated. The SMBHB produces a wide, eccentric gap in the disk, previously only observed for larger mass ratios, which we attribute to our disk model being much thinner ($H/R\approx0.01$ near the secondary) than is typical of previous works. The eccentric gap drives periodic accretion onto the secondary SMBH on a timescale matching the orbital period of the binary, $t_{\rm{bin}}\approx0.1\;\rm{yr}$, implying that the variable accretion regime of the SMBHB parameter space extends to lower mass ratios than previously established. Shocks driven by the binary are periodic, with a period matching the orbital period, and the shocks are correlated with the accretion rate, with peaks in the shock luminosity lagging peaks in the accretion rate by $0.43\;t_{\rm{bin}}$. We propose that the correlation of these quantities represents a useful identifier of SMBHB candidates, via observations of correlated variability in X-ray and UV monitoring of AGN, rather than single-waveband periodicity alone.Comment: 12 pages, 8 figures, accepted by MNRA

Towards 'engagement 2.0': insights from a study of dynamic consent with biobank participants

Web 2.0 technologies have enabled new methods of engagement, moving from static mono-directional sources of information to interactive user-led experiences. Use of Web 2.0 technologies for engagement is gaining momentum within the health sector however this is still in its infancy in biobanking research. This paper reports on findings from focus groups with biobank participants to gauge their views on a Web 2.0 dynamic consent interface. The findings from this study suggest that participants would welcome more interactive engagement with biobanks, and the opportunity to hear more about how their data and samples are being used in research. We propose that by adopting Web 2.0 tools for dynamic consent, we can move towards an ‘Engagement 2.0’ model whereby research participants have the opportunity for more interactive engagement with medical research, setting up a two-way communication channel between participants and researchers, for the benefit of both

Investigating Differences between Graphical and Textual Declarative Process Models

Declarative approaches to business process modeling are regarded as well suited for highly volatile environments, as they enable a high degree of flexibility. However, problems in understanding declarative process models often impede their adoption. Particularly, a study revealed that aspects that are present in both imperative and declarative process modeling languages at a graphical level-while having different semantics-cause considerable troubles. In this work we investigate whether a notation that does not contain graphical lookalikes, i.e., a textual notation, can help to avoid this problem. Even though a textual representation does not suffer from lookalikes, in our empirical study it performed worse in terms of error rate, duration and mental effort, as the textual representation forces the reader to mentally merge the textual information. Likewise, subjects themselves expressed that the graphical representation is easier to understand

Open data as an anticorruption tool? Using distributed cognition to understand breakdowns in the creation of transparency data

One of the drivers for pushing for open data as a form of corruption control stems from the belief that in making government operations more transparent, it would be possible to hold public officials accountable for how public resources are spent. These large datasets would then be open to the public for scrutiny and analysis, resulting in lower levels of corruption. Though data quality has been largely studied and many advancements have been made, it has not been extensively applied to open data, with some aspects of data quality receiving more attention than others. One key aspect however—accuracy—seems to have been overlooked. This gap resulted in our inquiry: how is accurate open data produced and how might breakdowns in this process introduce opportunities for corruption? We study a government agency situated within the Brazilian Federal Government in order to understand in what ways is accuracy compromised. Adopting a distributed cognition (DCog) theoretical framework, we found that the production of open data is not a neutral activity, instead it is a distributed process performed by individuals and artifacts. This distributed cognitive process creates opportunities for data to be concealed and misrepresented. Two models mapping data production were generated, the combination of which provided an insight into how cognitive processes are distributed, how data flow, are transformed, stored, and processed, and what instances provide opportunities for data inaccuracies and misrepresentations to occur. The results obtained have the potential to aid policymakers in improving data accuracy

Loneliness, social relations and health and wellbeing in deprived communities

There is growing policy concern about the extent of loneliness in advanced societies, and its prevalence among various social groups. This study looks at loneliness among people living in deprived communities, where there may be additional barriers to social engagement including low incomes, fear of crime, poor services and transient populations. The aim was to examine the prevalence of loneliness, and also its associations with different types of social contacts and forms of social support, and its links to self-reported health and wellbeing in the population group. The method involved a cross-sectional survey of 4,302 adults across 15 communities, with the data analysed using multinomial logistic regression controlling for sociodemographics, then for all other predictors within each domain of interest. Frequent feelings of loneliness were more common among those who: had contact with family monthly or less; had contact with neighbours weekly or less; rarely talked to people in the neighbourhood; and who had no available sources of practical or emotional support. Feelings of loneliness were most strongly associated with poor mental health, but were also associated with long-term problems of stress, anxiety and depression, and with low mental wellbeing, though to a lesser degree. The findings are consistent with a view that situational loneliness may be the product of residential structures and resources in deprived areas. The findings also show that neighbourly behaviours of different kinds are important for protecting against loneliness in deprived communities. Familiarity within the neighbourhood, as active acquaintance rather than merely recognition, is also important. The findings are indicative of several mechanisms that may link loneliness to health and wellbeing in our study group: loneliness itself as a stressor; lonely people not responding well to the many other stressors in deprived areas; and loneliness as the product of weak social buffering to protect against stressors

Fitness function distributions over generalized search neighborhoods in the q-ary hypercube

Evolutionary Computation, 21(4): 561-590, 2013The frequency distribution of a fitness function over regions of its domain is an important quantity for understanding the behavior of algorithms that employ randomized sampling to search the function. In general, exactly characterizing this distribution is at least as hard as the search problem, since the solutions typically live in the tails of the distribution. However, in some cases it is possible to efficiently retrieve a collection of quantities (called moments) that describe the distribution. In this paper, we consider functions of bounded epistasis that are defined over length-n strings from a finite alphabet of cardinality q. Many problems in combinatorial optimization can be specified as search problems over functions of this type. Employing Fourier analysis of functions over finite groups, we derive an efficient method for computing the exact moments of the frequency distribution of fitness functions over Hamming regions of the q-ary hypercube. We then use this approach to derive equations that describe the expected fitness of the offspring of any point undergoing uniform mutation. The results we present provide insight into the statistical structure of the fitness function for a number of combinatorial problems. For the graph coloring problem, we apply our results to efficiently compute the average number of constraint violations that lie within a certain number of steps of any coloring. We derive an expression for the mutation rate that maximizes the expected fitness of an offspring at each fitness level. We also apply the results to the slightly more complex frequency assignment problem, a relevant application in the domain of the telecommunications industry. As with the graph coloring problem, we provide formulas for the average value of the fitness function in Hamming regions around a solution and the expectation-optimal mutation rate.Spanish Ministry of Science and Innovation and FEDER under contract TIN2008-06491-C04-01 (the M∗ project). Andalusian Government under contract P07-TIC-03044 (DIRICOM project). Air Force Office of Scientific Re- search, Air Force Materiel Command, USAF, under grant number FA9550-08-1-0422