Project Risk Screening Matrix for River Management and Restoration

The ‘project risk screening matrix’ derives from a broader effort to assist US government agency staff in reviewing proposed stream management and restoration projects more efficiently and effectively. The River Restoration Analysis Tool (RiverRAT) developed through this effort provides a thorough, comprehensive and auditable approach to review and evaluate proposed stream actions and projects ( www.restorationreview.com ). The matrix was initially developed as the first step in applying the RiverRAT, its purpose being to assist reviewers in assessing the risk to natural resources associated with a particular proposal and matching the intensity of their review to the severity of that risk. Hence, the primary application of the matrix to date has been to identify and screen out low risk projects that may be dealt with expeditiously, so freeing the time and technical resources needed to allow deep reviews of higher risk projects. A second form of screening emerged from this primary function because the matrix proved adept at identifying the minimum level of site and project characterization required to support initial risk assessment. On this basis, proposals lacking adequate information can also be screened out, being referred back to the proponent with a request for additional information. More recently, new and novel versions of the matrix, featuring modification and refinement of one or both of the original axes, have emerged to widen and refine its application to linear infrastructure (e.g. pipelines, roads, and electrical transmission lines), in‐stream structures (e.g. large wood placement and culvert removal), and pre‐application, regulatory, decision‐support tools. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.     

A step-by-step performance assessment and improvement method for ERP implementation: Action case studies in Chinese companies

The implementation of enterprise resource planning (ERP) is a complex process, and the failure rate remains very high. The literature has reported over 80 critical success factors for ERP implementation, but companies typically do not know to exploit them. In this article, a step-by-step assessment and improvement method for ERP implementation is proposed and applied in three companies. First, a five-stage ERP implementation model is proposed. Second, about 80 critical success factors (CSFs) from the literature are elaborated into key performance indices (KPIs), which are associated with each stage of ERP implementation by ten local ERP experts. Third, the weights of the KPIs are calculated using the Dumpster–Shafer method and the evaluation of ten experts. During the implementation process, performance is measured at each stage and remedial actions are identified if the performance is below expectation. An implementation flowchart is developed based on a five-stage model and the philosophy of continuous improvement. Three action cases in Chinese manufacturing companies are conducted to illustrate the effects of the assessment model, which is also currently being used by a consulting company specialising in ERP implementation. With further evaluation by local experts, the model has the potential to serve as a guideline for ERP implementation in other countries.     

Towards sensible toxicity testing for nanomaterials: proposal for the specification of test design

During the last decade, nanomaterials (NM) were extensively tested for potential harmful effects towards humans and environmental organisms. However, a sound hazard assessment was so far hampered by uncertainties and a low comparability of test results. The reason for the low comparability is a high variation in the (1) type of NM tested with regard to raw material, size and shape and (2) procedures before and during the toxicity testing. This calls for tailored, nanomaterial-specific protocols. Here, a structured approach is proposed, intended to lead to test protocols not only tailored to specific types of nanomaterials, but also to respective test system for toxicity testing. There are existing standards on single procedures involving nanomaterials, however, not all relevant procedures are covered by standards. Hence, our approach offers a detailed way of weighting several plausible alternatives for e.g. sample preparation, in order to decide on the procedure most meaningful for a specific nanomaterial and toxicity test. A framework of several decision trees (DT) and flow charts to support testing of NM is proposed as a basis for further refinement and in-depth elaboration. DT and flow charts were drafted for (1) general procedure—physicochemical characterisation, (2) choice of test media, (3) decision on test scenario and application of NM to liquid media, (4) application of NM to the gas phase, (5) application of NM to soil and sediments, (6) dose metrics, (S1) definition of a nanomaterial, and (S2) dissolution. The applicability of the proposed approach was surveyed by using experimental data retrieved from studies on nanoscale CuO. This survey demonstrated the DT and flow charts to be a convenient tool to systematically decide upon test procedures and processes, and hence pose an important step towards harmonisation of NM testing.     

高校思政课网络评估系统的分析与设计

思政课程作为对大学生思想道德培养最为重要一门课程,在高校教学中有着非常突出的作用。因此,构建一个科学合理的思政课程教学评估系统,对提高当前教师的教学有着重要的帮助。基于此,本文结合自身的工作,提出运用软件工程的设计思路,并以模糊综合评判理论为基础,论述了评估系统的设计思路、功能模块以及数据库的设计。     

A depth perception and visual comfort guided computational model for stereoscopic 3D visual saliency

With the emerging development of three-dimensional (3D) related technologies, 3D visual saliency modeling is becoming particularly important and challenging. This paper presents a new depth perception and visual comfort guided saliency computational model for stereoscopic 3D images. The prominent advantage of the proposed model is that we incorporate the influence of depth perception and visual comfort on 3D visual saliency computation. The proposed saliency model is composed of three components: 2D image saliency, depth saliency and visual comfort based saliency. In the model, color saliency, texture saliency and spatial compactness are computed respectively and fused to derive 2D image saliency. Global disparity contrast is considered to compute depth saliency. Particularly, we train a visual comfort prediction function to distinguish stereoscopic image pair as high comfortable stereo viewing (HCSV) or low comfortable stereo viewing (LCSV), and devise different computational rules to generate a visual comfort based saliency map. The final 3D saliency map is obtained by using a linear combination and enhanced by a “saliency-center bias” model. Experimental results show that the proposed 3D saliency model outperforms the state-of-the-art models on predicting human eye fixations and visual comfort assessment.     

里必井田承压水带压开采评估

煤层底板承压水突出是发生水害事故的原因之一,要减少该类事故的发生,需对底板突水危险性进行准确评价。为保障里必井田承压水带压开采的安全进行,基于煤层底板突水研究理论分析,采用常规突水系数法和等效厚度突水系数法,分别对里必井田内3#煤和15#煤的奥灰水突水危险性进行了研究。研究发现,奥灰水对于3#煤的开采影响不大,但在局部构造及陷落柱发育地段及采区东北部区域仍存在一定的突水可能性;奥灰水对15#煤开采具有较大威胁,大部分区域具有较大突水危险性。等效岩层厚度法计算的突水系数考虑了不同性质岩层的岩石强度和阻水能力,计算更接近生产实际,结果更可靠;且在对突水系数法进一步优化后,其评价的结果可以更精确。     

Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing

Although predictive machine learning for supply chain data analytics has recently been reported as a significant area of investigation due to the rising popularity of the AI paradigm in industry, there is a distinct lack of case studies that showcase its application from a practical point of view. In this paper, we discuss the application of data analytics in predicting first tier supply chain disruptions using historical data available to an Original Equipment Manufacturer (OEM). Our methodology includes three phases: First, an exploratory phase is conducted to select and engineer potential features that can act as useful predictors of disruptions. This is followed by the development of a performance metric in alignment with the specific goals of the case study to rate successful methods. Third, an experimental design is created to systematically analyse the success rate of different algorithms, algorithmic parameters, on the selected feature space. Our results indicate that adding engineered features in the data, namely agility, outperforms other experiments leading to the final algorithm that can predict late orders with 80% accuracy. An additional contribution is the novel application of machine learning in predicting supply disruptions. Through the discussion and the development of the case study we hope to shed light on the development and application of data analytics techniques in the analysis of supply chain data. We conclude by highlighting the importance of domain knowledge for successfully engineering features.     

Life Cycle Assessment of Substitute Natural Gas production from biomass and electrolytic hydrogen

The synthesis of a Substitute Natural Gas (SNG) that is compatible with the gas grid composition requirements by using surplus electricity from renewable energy sources looks a favourable solution to store large quantities of electricity and to decarbonise the gas grid network while maintaining the same infrastructure. The most promising layouts for SNG production and the conditions under which SNG synthesis reduces the environmental impacts if compared to its fossil alternative is still largely untapped. In this work, six different layouts for the production of SNG and electricity from biomass and fluctuating electricity are compared from the environmental point of view by means of Life Cycle Assessment (LCA) methodology. Global Warming Potential (GWP), Cumulative Energy Demand (CED) and Acidification Potential (AP) are selected as impact indicators for this analysis. The influence of key LCA methodological aspects on the conclusions is also explored. In particular, two different functional units are chosen: 1 kg of SNG produced and 1 MJ of output energy (SNG and electricity). Furthermore, different approaches dealing with co-production of electricity are also applied. The results show that the layout based on hydrogasification has the lowest impacts on all the considered cases apart from the GWP and the CED with SNG mass as the functional unit and the avoided burden approach. Finally, the selection of the multifunctionality approach is found to have a significant influence on technology ranking.