Know when to fold ‘em: An empirical description of risk management in public research funding
بدانید چه موقع برابر شوید: شرح تجربی مدیریت ریسک در بودجه تحقیق عمومی-2020
Public research funding programs typically make grants with minimal intervention by program staff, rather than using a hands-on approach to project management, which is more common in the private sector. In contrast, program staff at the US Department of Energys Advanced Research Projects Agency – Energy (ARPA-E) are given a set of real options with which to manage funded projects: abandon, contract or expand project budgets or timelines. Using internal data from ARPA-E, we show that active project management enables risk mitigation across a portfolio of research projects. We find that program staff modify projects frequently, especially project timelines, and these changes are more sensitive to poor performance than to strong performance. We also find that projects with a shortened timeline or reduced budget are less likely to generate short-term research outputs, compared to those of ultimately similar size. This evidence suggests that the practice of active project management, when combined with high upfront risk tolerance, can be used to enhance the productivity of missionoriented public research funding.
Keywords: R&D funding | Project management | Real options | Managerial flexibility
Optimal carbon storage reservoir management through deep reinforcement learning
مدیریت بهینه ذخیره مخزن کربن از طریق یادگیری تقویتی عمیق-2020
Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decisionmaking problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.
Keywords: Reinforcement learning | Multistage decision-making | Deep autoregressive model | Deep Q network | Surrogate modeling | Markov decision process | Geological carbon sequestration
The development of complex and controversial innovations. Genetically modified mosquitoes for malaria eradication
توسعه نوآوری های پیچیده و بحث برانگیز. پشه های اصلاح شده ژنتیکی برای ریشه کن کردن مالاریا-2020
When there is significant uncertainty in an innovation project, research literature suggests that strictly sequencing actions and stages may not be an appropriate mode of project management. We use a longitudinal process approach and qualitative system dynamics modelling to study the development of genetically modified (GM) mosquitoes for malaria eradication in an African country. Our data were collected in real time, from early scientific research to deployment of the first prototype mosquitoes in the field. The gene drive technology for modifying the mosquitoes is highly complex and controversial due to risks associated with its characteristics as a living, self-replicating technology. We show that in this case the innovation journey is linear and highly structured, but also embedded within a wider system of adoption that displays emergent behaviour. Although the need to control risks associated with the technology imposes a linearity to the NPD process, there are possibilities for deviation from a more structured sequence of stages. This arises from the effects of feedback loops in the wider system of evidence creation and learning at the population and governance levels, which cumulatively impact on acceptance of the innovation. The NPD and adoption processes are therefore closely intertwined, meaning that the endpoint for R&D and beginning of mainstream adoption and diffusion are unclear. A key challenge for those responsible for NPD and its regulation is to plan for the adoption of the technology while simultaneously conducting its scientific and technical development.
Keywords: New product development | Adoption | Genetically modified mosquitoes | Living technology | Gene drive | Malaria
Implementation of a standardized voiding management protocol to reduce unnecessary re-catheterization - A quality improvement project
اجرای یک پروتکل استاندارد مدیریت تخلیه برای کاهش دوباره کاتتریزاسیون غیر ضروری - یک پروژه بهبود کیفیت-2020
Objective. To design and implement a standardized postoperative voiding management protocol that accurately identifies patients with urinary retention and reduces unnecessary re-catheterization. Methods. A postoperative voiding management protocol was designed and implemented in patients undergoing major, inpatient, non-radical abdominal surgery with a gynecologic oncologist. No patients had epidural catheters. The implemented quality improvement (QI) protocol included: 1) Foley removal at six hours postoperatively; 2) universal bladder scan after the first void; and 3) limiting re-catheterization to patientswith bladder scan volumes N150 ml. A total of 96 patients post-protocol implementation were compared to 52 patients preprotocol. Along with baseline demographic data and timing of catheter removal,we recorded the presence or absence of urinary retention and/or unnecessary re-catheterization and postoperative urinary tract infection rates. Fishers exact test and students t-tests were performed for comparisons. Results. The overall rate of postoperative urinary retention was 21.6% (32/148). The new voiding management protocol reduced the rate of unnecessary re-catheterization by 90% (13.5% vs 2.1%, p = 0.01), without overlooking true urinary retention (23.1% vs 20.8%, p = 0.83). Additionally, there was a significant increase in hospital-defined early discharge prior to 11:00 AM (4.0% vs 22.0%, p = 0.022). There was no difference in the postoperative urinary tract infection rate between the groups (p=1.00). Risk factors associatedwith urinary retention included older age (p b 0.01), use of medications with anticholinergic properties (p b 0.01), and preexisting urinary dysfunction (p b 0.01). Conclusions. Implementation of this new voiding management protocol reduced unnecessary recatheterization, captured and treated true urinary retention, and facilitated early hospital discharge
Keywords: Quality improvement | Bladder voiding | Urinary retention | Postoperative management | Gynecologic Oncology surgery | Urinary tract infection
Research on the policy route of China’s distributed photovoltaic power generation
تحقیق در مورد مسیر سیاست تولید انرژی فتوولتائیک و توزیع شده در چین-2020
The distributed photovoltaic power generation is an important way to make use of solar energy in cities. China issues a series of policies to support the development of distributed photovoltaics in law, electricity price, grid connection standard, project management, financial support and so on. However, there are still some defects in policies and market mechanism. China creates a competitive market with a significant number of projects of distributed photovoltaic power through the reform of the electricity market, yet substantial drawbacks of the corresponding investment subsidies prevent distributed photovoltaic power from rapidly developing. This paper summarizes the status quo of China’s distributed photovoltaic power development, given its long-term plan, presents excellences and shortcomings of the existing policy system, and looks into the supporting policies and implementation paths for China’s distributed photovoltaic power in different stages. Innovative business models and financial support models are conducive to the development of distributed photovoltaic power. Financial innovation methods such as crowd funding and asset securitization should be encouraged to develop a sound risk assessment mechanism for projects, involve insurance institutions, and establish a risk sharing mechanism. In the context of a series of supporting policies, the distributed photovoltaic power in China will move towards market-oriented standardization for a healthier and more stable development.
Keywords: Distributed photovoltaic power | Electricity price | Policy route | Development strategy
AIS-Based Vessel Trajectory Reconstruction with U-Net Convolutional Networks
بازسازی مسیر کشتی مبتنی بر AIS با شبکه های کانولوشن U-Net-2020
The vessel trajectory data indicated by the Automatic Identification System (AIS) is important and useful in maritime data analysis, navigational safety and maritime risk assessment. However, the raw trajectory data contains noise, missing data and other errors which can lead to a wrong conclusion. Therefore, it is essential to develop a vessel trajectory reconstruction method, which is meaningful for enhancing the applicability of vessel trajectory and improving the navigation safety. In recent years, there have been many studies about vessel trajectory reconstruction, but the performance of these methods will degrade when they are faced with curved trajectories with high loss rate. In this paper, we propose a novel trajectory reconstruction method via U-net. Benefiting from the architecture of U-net, this method makes great use of historical trajectories and takes advantage of the rich skip connections in this network which help copy low-level features to corresponding high-level features. Consequently, this method is robust to the trajectories with different sampling rates, missing points, and noisy data. In addition, the proposed method is tested and compared with cubic spline interpolation. The results show that our method is capable of higher accuracy than the cubic spline interpolation especially when the trajectories are curved and have a high loss rate.
Keywords: Trajectory reconstruction | U-net | Machine learning | AIS data | Traffic safety
Qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions
ارزیابی ریسک کمی و کیفی پروژه با استفاده از یک مدل توسعه یافته PMBOK تحت شرایط غیر قطعی-2020
This study presented a qualitative and quantitative project risk assessment using a hybrid PMBOK model developed under uncertainty conditions. Accordingly, an exploratory and applied research design was employed in this study. The research sample included 15 experienced staff working in main and related positions in Neyr Perse Company. After reviewing the literature and the Project Management Body of Knowledge (PMBOK), 32 risk factors were identified and their number reduced to 17 risks using the expert opinions via the fuzzy Delphi technique run through three stages. The results of the confirmatory factor analysis showed that all risks were confirmed by the members of the research sample. Then the identified risks were structured and ranked using fuzzy DEMATEL and fuzzy ANP techniques. The final results of the study showed that the political and economic sanctions had the highest weight followed by foreign investors’ attraction and the lack of regional infrastructure.
Keywords: Project risks | Project management body of knowledge (PMBOK) | Uncertainty | Mixed qualitative and quantitative risk assessment approach | Mathematics | Probability theory | Engineering | Industrial engineering | Business
Uncertainty in information system development: Causes, effects, and coping mechanisms
عدم اطمینان در توسعه سیستم اطلاعات: علل ، اثرات و مکانیسم های مقابله-2020
Information system development (ISD) projects are an ever-growing field of project management (PM) with their unique features, and project failures in ISD are relatively common. In the broader context of PM, uncertainty is a studied, yet mercurial phenomenon. By contrast, uncertainty in ISD projects has received relatively little attention from scholars, and PM literature has not systematically focused on uncertainty in ISD from a viewpoint other than that of project managers. In order to understand uncertainties in ISD projects, we need to first understand the causes behind them, their effects on everyday ISD work, and share coping mechanisms utilized among industry professionals. In the context of ISD projects, we set out to explore what causes uncertainty, what are the effects of uncertainty, and how software industry professionals cope with uncertainty. We conducted eleven semi-structured interviews with a diverse range of ISD professionals, and analyzed the interviews using conventional content analysis. Our results extend and complement current knowledge on the causes, effects, and coping mechanisms of uncertainty, especially in the context of ISD. Additionally, we present practical considerations on how to implement our findings into ISD industry and education.
Keywords: Uncertainty | Risk | Information system development | Cause | Effect | Coping mechanism
Method for tracking and communicating aggregate risk through the use of model-based systems engineering (MBSE) tools
روش ردیابی و برقراری ارتباط ریسک با استفاده از ابزارهای مهندسی سیستم مبتنی بر مدل (MBSE)-2020
Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating ag- gregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5 ×5 risk matrix. Like earlier efforts, each box in the 5 ×5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with “Risk to ”relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system’s true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.
Harnessing AI to Transform Agriculture and Inform Agricultural Research
استفاده از هوش مصنوعی برای تبدیل کشاورزی و اطلاع از تحقیقات کشاورزی-2020
We provide an overview of the Special Issue on current advances, challenges, and opportunities for AI technologies in agriculture. We illustrate the potential of AI using four major components of the food system: production, distribution, consumption, and uncertainty. We recognize that the transformation of agriculture will require new tools to more precisely manage fields to increase production while minimizing the environmental risk to water and air quality. Combining AI with other technologies will be needed to provide effective production management strategies for a given combination of soil, climate, pest complexes, and vegetation. New methods will be needed to determine production limitations, and effective management options. The agricultural enterprise is prime for the use of AI and other technologies if they can be adapted for the unique characteristics of agroecosystems, including variability and directional changes in climate and other global change drivers as well as novel management and policy decisions, and economic market volatility.