The Geographic Distribution of Bowhead Whales, Balaena mysticetus, in the Bering, Chukchi, and Beaufort Seas: Evidence from Whaleship Records, 1849–1914

We have extracted, digitized, and analyzed information about bowhead whales, Balaena mysticetus, contained in records of whaling cruises that were undertaken in the Bering, Chukchi, and Beaufort Seas from 1849 to 1914. Our database consists of 65,000 days of observations which provide insights into whether this bowhead stock may comprise more than one population

Feedback through student essay competitions: what makes a good engineering lecturer?

The Engineering Subject Centre of the HE Academy has run student essay competitions for some years. In 2008 the title was ‘What makes a good engineering lecturer?’. This paper presents an analysis of the 43 submissions, carried out to identify the most commonly cited attributes and to present quotes that convey the spirit of the essays. The same title had been used for the first competition in 2004, and the outcomes of the 2008 competition are compared with those previously published for the 2004 award. The attributes most commonly identified across both sets of essays are use of real-world examples, approachability, enthusiasm, diversity of media, and good communication

Analyzing and improving the energy balancing market in the power trading agent competition

Widespread adoption of sustainable energy sources is driving electricity grid operators to supplement hierarchical control regimes with market-based control that better motivates stakeholder involvement. However, to prevent market failures, such controls require testing before real-world implementation. The Power Trading Agent Competition is a competitive simulation of distribution grids that mirrors real-world scenarios and tests alternative policy and business scenarios. In Power TAC, broker agents acquire energy through bidding in a forward wholesale market to satisfy their customers overall demand on an hourly basis. In addition, a balancing market is intended to resolve real-time energy imbalances caused by broker prediction errors using demand response resources. As part of the annual alignment process, we discovered that brokers in the 2015 competition were persistently buying insufficient energy on the wholesale market to satisfy their customer demand. Instead, the balancing market made up the deficit, charging brokers a premium over the wholesale price. Also, demand response resources were heavily underused. We studied the economic impact of this systematic imbalance on brokers and discovered that they were behaving rationally, given the prices they faced in the two markets. We present the process and results of this analysis, and show how the balancing markets pricing mechanism can be adjusted for the 2016 competition to make it rational for brokers to achieve an overall neutral imbalance

Flexible Decision Support in Dynamic Interorganizational Networks

An effective Decision Support System (DSS) should help its users improve decision-making in complex, information-rich, environments. We present a feature gap analysis that shows that current decision support technologies lack important qualities for a new generation of agile business models that require easy, temporary integration across organisational boundaries. We enumerate these qualities as DSS Desiderata, properties that can contribute both effectiveness and flexibility to users in such environments. To address this gap, we describe a new design approach that enables users to compose decision behaviours from separate, configurable components, and allows dynamic construction of analysis and modelling tools from small, single-purpose evaluator services. The result is what we call an “evaluator service network” that can easily be configured to test hypotheses and analyse the impact of various choices for elements of decision processes. We have implemented and tested this design in an interactive version of the MinneTAC trading agent, an agent designed for the Trading Agent Competition for Supply Chain Management

Assessing Risk and Driving Risk Mitigation for First-of-a-Kind Advanced Reactors

Planning and decision making amidst programmatic and technological risks represent significant challenges for projects. This presentation addresses the four step risk-assessment process needed to determine clear path forward to mature needed technology and design, license, and construct advanced nuclear power plants, which have never been built before, including Small Modular Reactors. This four step process has been carefully applied to the Next Generation Nuclear Plant. STEP 1 - Risk Identification Risks are identified, collected, and categorized as technical risks, programmatic risks, and project risks, each of which result in cost and schedule impacts if realized. These include risks arising from the use of technologies not previously demonstrated in a relevant application. These risks include normal and accident scenarios which the SMR could experience including events that cause the disablement of engineered safety features (typically documented in Phenomena Identification Ranking Tables (PIRT) as produced with the Nuclear Regulatory Commission) and design needs which must be addressed to further detail the design. Product - Project Risk Register contained in a database with sorting, presentation, rollup, risk work off functionality similar to the NGNP Risk Management System . STEP 2 - Risk Quantification The risks contained in the risk register are then scored for probability of occurrence and severity of consequence, if realized. Here the scoring methodology is established and the basis for the scoring is well documented. Product - Quantified project risk register with documented basis for scoring. STEP 3 - Risk Handling Strategy Risks are mitigated by applying a systematic approach to maturing the technology through Research and Development, modeling, test, and design. A Technology Readiness Assessment is performed to determine baseline Technology Readiness Levels (TRL). Tasks needed to mature the technology are developed and documented in a roadmap. Product - Risk Handling Strategy. STEP 4 - Residual Risk Work off The risk handling strategy is entered into the Project Risk Allocation Tool (PRAT) to analyze each task for its ability to reduce risk. The result is risk-informed task prioritization. The risk handling strategy is captured in the Risk Management System, a relational database that provides conventional database utility, including data maintenance, archiving, configuration control, and query ability. The tool's Hierarchy Tree allows visualization and analyses of complex relationships between risks, risk mitigation tasks, design needs, and PIRTs. Product - Project Risk Allocation Tool and Risk Management System which depict project plan to reduce risk and current progress in doing so