MDP Optimal Control under Temporal Logic Constraints

In this paper, we develop a method to automatically generate a control policy for a dynamical system modeled as a Markov Decision Process (MDP). The control specification is given as a Linear Temporal Logic (LTL) formula over a set of propositions defined on the states of the MDP. We synthesize a control policy such that the MDP satisfies the given specification almost surely, if such a policy exists. In addition, we designate an "optimizing proposition" to be repeatedly satisfied, and we formulate a novel optimization criterion in terms of minimizing the expected cost in between satisfactions of this proposition. We propose a sufficient condition for a policy to be optimal, and develop a dynamic programming algorithm that synthesizes a policy that is optimal under some conditions, and sub-optimal otherwise. This problem is motivated by robotic applications requiring persistent tasks, such as environmental monitoring or data gathering, to be performed.Comment: Technical report accompanying the CDC2011 submissio

Social Media – the new challenge for PR measurement and evaluation

In the five years since Paul Noble and I wrote the second edition of our book, Evaluating Public Relations, the biggest change in the field has been the rapid emergence of social media in media relations and organisational communication. Although we devoted a full chapter to the online environment, social media has rushed ahead in terms of its usage for communications and in the demands for measurement of its effectiveness. In this short paper, prepared with help from AMEC, the International Association for the Measurement of Communication, some of the issues that PR practitioners must consider are discussed

Transferring simulation skills from other industries to nuclear

Engineering analysis and simulation has always played a significant role in the nuclear sector and its use continues to increase across all branches of industry. To remain competitive in an increasingly global environment and to ensure the safety and reliability of designs, the nuclear industry must take advantage of the new engineering simulation technologies. Concerns surrounding the inappropriate use of simulation by staff without the appropriate competency persist, as analyses become more advanced, increasingly embracing more complex physical phenomena, often in an effort to model reality more faithfully. Furthermore, the age profile of the skilled staff in the nuclear sector in the UK is such that the skills shortage is likely to increase in future. These trends emphasize the need for life-long learning and continual staff development along with transfer of skills from other industry sectors to the nuclear sector. The nuclear industry has taken some initiatives to address skill shortages through the National Skills Academy for Nuclear and Nuclear Energy Skills Alliance (NESA) but these are mostly focused on manufacturing and R&D skills. The recently completed EU funded EASIT2 project is directly aimed at addressing the engineering analysis and simulation skills. This paper gives a brief overview of the EASIT2 project and its deliverables and points out how it can help the skills issues being faced by the nuclear industry. INTRODUCTIO

Understanding Dialogue and Engagement Through Communication Experts’ Use of Interactive Writing to Build Relationships

Dialogic communication is an important public relations theory, yet scholarship has found few organizations using it to its full potential. Meanwhile, multiple overlapping definitions exist for related terms like engagement, interactivity, and responsiveness, causing potential confusion for researchers and professionals. This research reports the results of in-depth interviews with top digital public relations professionals regarding how they use interactive writing, a form of social media engagement, to build relationships. Through their own unprompted words, the research also describes how professionals use terms such as dialogue, engagement, interactivity, and responsiveness, and corresponding definitions, to refer to their daily work. Our model clarifies relationships between similar concepts and recommends areas of future research to advance theory informed by practic

Control of Probabilistic Systems under Dynamic, Partially Known Environments with Temporal Logic Specifications

We consider the synthesis of control policies for probabilistic systems, modeled by Markov decision processes, operating in partially known environments with temporal logic specifications. The environment is modeled by a set of Markov chains. Each Markov chain describes the behavior of the environment in each mode. The mode of the environment, however, is not known to the system. Two control objectives are considered: maximizing the expected probability and maximizing the worst-case probability that the system satisfies a given specification

U.S. Geological Survey External Quality-Assurance Project Report for the National Atmospheric Deposition Program / National Trends Network and Mercury Deposition Network, 2011-12

The U.S. Geological Survey operated six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program (NADP) / National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2011–2012. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples; a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory and Mercury Analytical Laboratory (HAL). A blind-audit program was implemented for the MDN during 2011 to evaluate analytical bias in HAL total mercury concentration data. The co-located–sampler program was used to identify and quantify potential shifts in NADP data resulting from the replacement of original network instrumentation with new electronic recording rain gages and precipitation collectors that use optical precipitation sensors. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the United States. Co-located rain gage results indicate -3.7 to +6.5 percent bias in NADP precipitation-depth measurements. Co-located collector results suggest that the retrofit of the NADP networks with the new precipitation collectors could cause +10 to +36 percent shifts in NADP annual deposition values for ammonium, nitrate, and sulfate; -7.5 to +41 percent shifts for hydrogen-ion deposition; and larger shifts (-51 to +52 percent) for calcium, magnesium, sodium, potassium, and chloride. The prototype N-CON Systems bucket collector typically catches more precipitation than the NADP-approved Aerochem Metrics Model 301 collector.National Atmospheric Deposition Programpublished or submitted for publicationis peer reviewedOpe