一种改进的多学习教与学优化算法

针对传统教与学算法在解决复杂多峰函数优化问题时,具有局部最优且搜索开发能力较差的缺点,提出了一种改进的多学习教与学优化算法,新算法为学员的每一维加入不同的教学因子,设计了基于学员均值比较的教师选择策略和向教师及学员学习的多学习策略。基于多个单峰和多峰函数的仿真结果表明,新算法跟传统的、改进的教与学算法相比,在稳定性、寻优精度和收敛速度方面更具优势。     

Framework for participative reflection on the accomplishment of transdisciplinary research programs

In response to the increasingly complex social–ecological issues facing society, there is a growing trend to conduct environmental research in large collaborative programs. This approach is described as transdisciplinary research as it transcends formal disciplinary boundaries, explicitly acknowledges that many different perspectives are relevant to the resolution of complex problems, and actively involves the users of research. This poses challenges for the evaluation of “impact” as any evaluation process must take into consideration the different expectations, values, culture, language and reward structures of the main participating groups, the funders, researchers and end users. How can these participating groups learn about the progress of a transdisciplinary research program in a way that is purposeful and structured, continues through the life of the program, and includes explicit feedback mechanisms that facilitate adaptation during the course of the program? This paper presents a framework for co-reflecting on the accomplishment of transdisciplinary research programs. The framework incorporates the perspectives of funders, researchers and users, and recognizes that while they place different emphasis on measures of achievement such as efficiency, rigor and relevance, ultimate accomplishment in terms of translating knowledge into practice requires that the needs and expectations of all three groups are adequately addressed. What emerges from the framework is the importance of early investment in processes, behaviors and relationships that foster social learning and the co-production of the knowledge and understanding that are required to ensure relevance; while maintaining emphasis in the traditional areas of formally testing evidence and mentoring young researchers to ensure rigor and build confidence and capacity in transdisciplinary approaches.     

The Contribution of Pre-impact Posture on Restrained Occupant Finite Element Model Response in Frontal Impact

Objective: The objective of this study was to discuss the influence of the pre-impact posture to the response of a finite element human body model (HBM) in frontal impacts.

Methods: This study uses previously published cadaveric tests (PMHS), which measured six realistic pre-impact postures. Seven postured models were created from the THUMS occupant model (v4.0): one matching the standard UMTRI driving posture as it was the target posture in the experiments, and six matching the measured pre-impact postures. The same measurements as those obtained during the cadaveric tests were calculated from the simulations, and biofidelity metrics based on signals correlation (CORA) were established to compare the response of the seven models to the experiments.

Results: The HBM responses showed good agreement with the PMHS responses for the reaction forces (CORA = 0.80 ± 0.05) and the kinematics of the lower part of the torso but only fair correlation was found with the head, the upper spine, rib strains (CORA= 0.50 ± 0.05) and chest deflections (CORA = 0.67 ± 0.08). All models sustained rib fractures, sternal fracture and clavicle fracture. The average number of rib fractures for all the models was 5.3 ± 1.0, lower than in the experiments (10.8 ± 9.0).

Variation in pre-impact posture greatly altered the time histories of the reaction forces, deflections and the rib strains, mainly in terms of time delay, but no definite improvement in HBM response or injury prediction was observed. By modifying only the posture of the HBM, the variability in the impact response was found to be equivalent to that observed in the experiments. The postured HBM sustained from 4 to 8 rib fractures, confirming that the pre-impact posture influenced the injury outcome predicted by the simulation.

Conclusions: This study tries to answer an important question: what is the effect of occupant posture on kinematics and kinetics. Significant differences in kinematics observed between HBM and PMHS suggesting more coupling between the pelvis and the spine for the models which makes the model response very sensitive to any variation in the spine posture. Consequently, the findings observed for the HBM cannot be extended to PMHS. Besides, pre-impact posture should be carefully quantified during experiments and the evaluation of HBM should take into account the variation in the predicted impact response due to the variation in the model posture.     

Adaptive co-management and network learning in the Room for the River programme

Adaptive co-management and learning are paramount for integrated flood risk management. Relevant literature focuses on adaptation at the level of physical and societal systems. The level of projects and programmes is largely overlooked, but they comprise interventions that adapt our physical systems and they provide opportunities for learning to contribute to transitions of societal systems. This paper aims to increase understanding on how learning takes place and can be stimulated within a programme. The mixed-method case study of Room for the River, a €2.3 billion programme for flood risk management, shows that a programme can be organised using various governance arrangements to stimulate learning and be a means for adaptive co-management to deliver upon environmental objectives.     

Using GIS to Delineate Headwater Stream Origins in the Appalachian Coalfields of Kentucky

Headwater streams have a significant nexus or physical, chemical, and/or biological connection to downstream reaches. Generally, defined as 1st‐3rd order with ephemeral, intermittent, or perennial flow regimes, these streams account for a substantial portion of the total stream network particularly in mountainous terrain. Due to their often remote locations, small size, and large numbers, conducting field inventories of headwater streams is challenging. A means of estimating headwater stream location and extent according to flow regime type using publicly available spatial data is needed to simplify this complex process. Using field‐collected headwater point of origin data from three control watersheds, streams were characterized according to a set of spatial parameters related to topography, geology, and soils. These parameters were (1) compared to field‐collected point of origin data listed in three nearby Jurisdictional Determinations, (2) used to develop a geographic information system (GIS)‐based stream network for identifying ephemeral, intermittent, and perennial streams, and (3) applied to a larger watershed and compared to values obtained using the high‐resolution National Hydrography Dataset (NHD). The parameters drainage area and local valley slope were the most reliable predictors of flow regime type. Results showed the high‐resolution NHD identified no ephemeral streams and 9 and 65% fewer intermittent and perennial streams, respectively, than the GIS model.