Degradation of phenol and TCE using suspended and chitosan-bead immobilized Pseudomonas putida

The degradability of phenol and trichloroethene (TCE) by Pseudomonas putida BCRC 14349 in both suspended culture and immobilized culture systems are investigated. Chitosan beads at a size of about 1-2mm were employed to encapsulate the P. putida cells, becoming an immobilized culture system. The phenol concentration was controlled at 100 mg/L, and that of TCE was studied from 0.2 to 20 mg/L. The pH, between 6.7 and 10, did not affect the degradation of either phenol or TCE in the suspended culture system. However, it was found to be an important factor in the immobilized culture system in which the only significant degradation was observed at pH >8. This may be linked to the surface properties of the chitosan beads and its influence on the activity of the bacteria. The transfer yield of TCE on a phenol basis was almost the same for the suspended and immobilized cultures (0.032 mg TCE/mg phenol), except that these yields occurred at different TCE concentrations. The transfer yield at a higher TCE concentration for the immobilized system suggested that the cells immobilized in carriers can be protected from harsh environmental conditions. For kinetic rate interpretation, the Monod equation was employed to describe the degradation rates of phenol, while the Haldane's equation was used for TCE degradation. Based on the kinetic parameters obtained from the two equations, the rate for the immobilized culture systems was only about 1/6 to that of the suspended culture system for phenol degradation, and was about 1/2 for TCE degradation. The slower kinetics observed for the immobilized culture systems was probably due to the slow diffusion of substrate molecules into the beads. However, compared with the suspended cultures, the immobilized cultures may tolerate a higher TCE concentration as much less inhibition was observed and the transfer yield occurred at a higher TCE concentration.     

On the performance of social network and likelihood-based expert weighting schemes

Using expert judgment data from the TU Delft's expert judgment database, we compare the performance of different weighting schemes, namely equal weighting, performance-based weighting from the classical model [Cooke RM. Experts in uncertainty. Oxford: Oxford University Press; 1991.], social network (SN) weighting and likelihood weighting. The picture that emerges with regard to SN weights is rather mixed. SN theory does not provide an alternative to performance-based combination of expert judgments, since the statistical accuracy of the SN decision maker is sometimes unacceptably low. On the other hand, it does outperform equal weighting in the majority of cases. The results here, though not overwhelmingly positive, do nonetheless motivate further research into social interaction methods for nominating and weighting experts. Indeed, a full expert judgment study with performance measurement requires an investment in time and effort, with a view to securing external validation. If high confidence in a comparable level of validation can be obtained by less intensive methods, this would be very welcome, and would facilitate the application of structured expert judgment in situations where the resources for a full study are not available. Likelihood weights are just as resource intensive as performance-based weights, and the evidence presented here suggests that they are inferior to performance-based weights with regard to those scoring variables which are optimized in performance weights (calibration and information). Perhaps surprisingly, they are also inferior with regard to likelihood. Their use is further discouraged by the fact that they constitute a strongly improper scoring rule.     

Prospect Theory Based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation

The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia. For the sustainable development of maritime transport, International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020. With the approaching of the stipulated implementation date, shipowners need to adopt scientific methods to make decision on low sulfur fuel. In this study, we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel. For this purpose, the hesitant fuzzy decision matrix is established to collect expert opinions, the maximizing deviation method is adopted to determine criteria weights. According to calculate the Euclidean distance from the reference points, we obtain the comprehensive prospect values of alternatives. Lastly, a case study is carried out to illustrate the significance and effectiveness of the proposed methodology. The innovation of this study is that it is the first-time adopting prospect theory and hesitate fuzzy sets to multi-criteria decision making for low Sulphur marine fuel, which provides an effective decision model for shipping companies under Low Sulphur regulations, and can also be extended to other industries.     

Dechlorinating ability of TCE-fed microcosms with different electron donors

The main objective of the work presented herein is to assess the effect of different electron donors (butyric acid and methanol) on the dechlorinating activity of two microbial cultures where active methanogenic populations are present, in an effort to evaluate the importance of the electron donor selection process. The ability of each anaerobic culture to dechlorinate TCE, when enriched with either butyric acid or methanol, was verified based on the results of gas chromatography. In addition, the fluorescent in situ hybridization (FISH) and the polymerase chain reaction (PCR) methods gave positive results for the presence of Dehalococcoides spp. According to results of the batch tests conducted in this study, it appears that the selection of the electron donor for stimulating TCE dechlorination depends on microbial culture composition; therefore, the decision on the appropriate electron donor should be based on site-specific microcosm studies.     

汽车碰撞安全风险决策中基于复合聚类的群决策专家权重确定方法

针对风险评估中群决策数据的处理可靠性问题,提出专家权重对于数据处理的重要性。从汽车碰撞安全研究的行业特色出发,依据专家社会因素指标,运用系统聚类和K-均值聚类分析方法,对专家进行专家权威权重聚类;依据专家提供意见的数据一致性和个体与群体一致性程度,运用基于信息熵的方法对专家进行专家意见权重聚类;将两种聚类结果进行复合聚类,得到各位专家的最终权重。结果表明,在综合专家权威权重和专家意见权重的基础上,经复合聚类得到的专家权重具有较好的均衡性和可靠性,为系统项目的研究奠定基础。     

Force analysis and visualization of NAPL removal during surfactant-related floods in a porous medium

Governing mechanisms of dense non-aqueous phase liquid (DNAPL) removal during surfactant and surfactant-foam (SF) flooding were studied by porous-patterned glass model experiments. Physical forces, viscous forces and capillary forces, acting on trichloroethylene (TCE) blobs were quantified to understand DNAPL removal mechanisms during the floods, simultaneously visualizing the removal mechanisms. The viscous force of the remedial fluid was intimately related to TCE removal from the porous medium. The remedial fluid with a high viscous force displaced more TCE blobs. Displacement of residual TCE by the remedial fluid began as viscous pressure of flooding was closed to the capillary pressure of the porous medium. In the region of viscous pressure less than the capillary pressure, residual TCE was either retained or solubilized, not displaced, implying that TCE solubilization was the dominant TCE removal process. Glass porous model visualization validated a dominance of the capillary forces during a surfactant flush and a dominance of the viscous forces of the displacing fluid during a SF flood.     

声呐渗流测量数据降噪的分类模型研究

渗漏造成的一系列安全隐患己严重威胁到地下隐蔽工程的建设与正常运行.为了研发新的渗流测量手段与技术方法,减少控制渗漏事故的发生,提出了一种基于梯度提升树的声呐渗流检测结果分类模型.模型利用ReliefF算法选取贡献权重大的特征作为训练数据集,利用属性标注的数据集训练出区分水库渗流、井孔渗流与噪声的梯度提升树模型.实验结果...     

Justification for the selection of manufacturing technologies: a fuzzy-decision-tree-based approach

In this paper, a developed model for the justification of alternative manufacturing technologies is presented. The approach, based on fuzzy decision trees, provides a methodology capable of identifying patterns within a technology case repository to support the evaluation of manufacturing systems. Experts are highly influential individuals in the decision process; they provide support and guidance when selecting investments. The experience-oriented task is founded on previous cases or an experts’ experience, and therefore difficult to express in a rational form. The concept is based on a number of characteristics of the case-based reasoning, rule induction and expert system theory. Structured around the fuzzy-decision-tree data-mining technique, the framework provides the ability of using regulated case information to act as structured experience for assisting in the decision process. Fuzzy induction extracts formal rules from a set of experience data, and the expert system philosophy computes the experience base of human expertise for problem-solving. A test case indicates the stability of the classification algorithm and verifies the applicability within the domain.     

Persulfate regeneration of trichloroethylene spent activated carbon

The objective of this study was to demonstrate the regeneration of trichloroethylene (TCE) spent activated carbon using persulfate oxidation and iron activated persulfate (IAP) oxidation. Both processes resulted in decreases in the adsorbability of regenerated activated carbons. IAP was shown to rapidly degrade the aqueous TCE and causes a significant mineralization of the TCE. The release of chloride ions provided evidence of this. Persulfate oxidation mainly resulted in desorption of TCE from the activated carbon and only partial mineralization of the TCE through a carbon activated persulfate reaction mechanism. Concerning destruction of the TCE, in the regeneration test using persulfate, 30% of the original TCE was present in the solution and 9% remained on the activated carbon after the first regeneration cycle. In contrast, in the test that used IAP, it was observed that no TCE was present in the solution and only approximately 5% of the original TCE remained on the activated carbon after the first regeneration. Following the regeneration cycles, elemental analysis was carried out on the samples. BET surface area and EDS analysis showed some effects on the physico-chemical properties of the activated carbon such as a slight decrease in the surface area and the presence of iron precipitates on the carbon.     

Fuzzy hybrid decision model for supplier evaluation and selection

This paper proposes a structured, integrated decision model for evaluating suppliers by combining the fuzzy analytical hierarchy process (FAHP) and grey relational analysis (GRA). The qualitative and partially-known information is incorporated in this decision model using the fuzzy set theory. In this proposed methodology, the weights of the evaluation criteria are calculated by using FAHP, then the ranking of the suppliers is determined by using GRA. Finally to show the robustness of the model, a sensitivity analysis is also performed. In this study, the supplier selection problem of an electroplating industry in the southern part of India was investigated, demonstrating the effectiveness of this developed integrated model. This model can help in solving the complex decision in supplier selection practice. The results generated from the model are properly validated and finally a systematic solution with decision support is provided for decision makers. This model can be integrated with other decision support systems of similar kinds of industries.     

A Dynamic Risk Assessment Methodology for Maintenance Decision Support

The failure mode and effect analysis (FMEA) is a widely applied technique for prioritizing equipment failures in the maintenance decision‐making domain. Recent improvements on the FMEA have largely focussed on addressing the shortcomings of the conventional FMEA of which the risk priority number is incorporated as a measure for prioritizing failure modes. In this regard, considerable research effort has been directed towards addressing uncertainties associated with the risk priority number metrics, that is occurrence, severity and detection. Despite these improvements, assigning these metrics remains largely subjective and mostly relies on expert elicitations, more so in instances where empirical data are sparse. Moreover, the FMEA results remain static and are seldom updated with the availability of new failure information. In this paper, a dynamic risk assessment methodology is proposed and based on the hierarchical Bayes theory. In the methodology, posterior distribution functions are derived for risk metrics associated with equipment failure of which the posterior function combines both prior functions elicited from experts and observed evidences based on empirical data. Thereafter, the posterior functions are incorporated as input to a Monte Carlo simulation model from which the expected cost of failure is generated and failure modes prioritized on this basis. A decision scheme for selecting appropriate maintenance strategy is proposed, and its applicability is demonstrated in the case study of thermal power plant equipment failures. Copyright © 2016 John Wiley & Sons, Ltd.     

基于案例推理的企业项目管理决策支持系统的研究

基于案例推理方法的基本原理,将案例推理方法应用于项目管理辅助决策支持分析,论述了基于案例推理的项目管理决策支持系统中的一些关键步骤,研究了项目管理中项目任务问题案例的知识案例表达、属性权重分析和近邻方法相结合的检索模型,实现了案例检索和匹配,提出了辅助项目任务问题案例辅助决策支持系统的结构,开发了原型系统,并给出应用实例．     

群决策环境下危险品运输风险评价方法

〖HT5”H〗摘要： 〖HTSS〗为了合理地确定不同运输方案的风险等级,为危险品生产企业提供运输决策支持,构建了危险品运输风险评价指标体系,提出了群决策环境下危险品运输风险评价方法。该方法应用模糊语言术语来表达评价值,基于专家评价值的一致度来修正专家初始权重,利用综合赋权法确定评价指标的权重,引入格贴近度确定不同运输方案的风险等级。该方法有效地降低了风险评价工作的复杂性。最后以某危险品运输为例,验证了该方法的可行性和实用性。     

Evaluating flexible manufacturing systems using a combined multiple attribute decision making method

This paper presents a logical procedure to evaluate alternative flexible manufacturing systems for a given industrial application. The procedure is based on a combined multiple attribute decision making method using TOPSIS and AHP methods together. A ‘flexible manufacturing system suitability index’ is proposed that evaluates and ranks flexible manufacturing systems for the given industrial application. The methodology is illustrated by means of an example.     

Calibration of Expert Judgments Applied to Uncertainty Assessment

Abstract:

This article contributes a methodology for eliciting expert judgment in support of decision analysis associated with the conceptual design of advanced engineering systems. To provide a basis for decision making in the presence of model and input parameter uncertainties, experts in several disciplines can be utilized to provide model parameter estimates to facilitate analyses. The judgment elicitation methodology was developed to cover a multitude of system disciplines using multiple experts. To address consistency in expert assessments, the methodology includes expert assessment calibration means. A sample application of the resultant expert judgment methodology is discussed. An engineering manager can use the methodology described in this article to assess viability of potential courses of action in high-risk or advanced state-of-the-art technology systems development ventures.     

An integrated quality function deployment and capital budgeting methodology for occupational safety and health as a systems thinking approach: The case of the construction industry

In this paper, an integrated methodology for Quality Function Deployment (QFD) and a 0–1 knapsack model is proposed for occupational safety and health as a systems thinking approach. The House of Quality (HoQ) in QFD methodology is a systematic tool to consider the inter-relationships between two factors. In this paper, three HoQs are used to consider the interrelationships between tasks and hazards, hazards and events, and events and preventive/protective measures. The final priority weights of events are defined by considering their project-specific preliminary weights, probability of occurrence, and effects on the victim and the company. The priority weights of the preventive/protective measures obtained in the last HoQ are fed into a 0–1 knapsack model for the investment decision. Then, the selected preventive/protective measures can be adapted to the task design. The proposed step-by-step methodology can be applied to any stage of a project to design the workplace for occupational safety and health, and continuous improvement for safety is endorsed by the closed loop characteristic of the integrated methodology.     

基于多维质量屋的企业合作决策方法

为解决企业合作战略实施过程中的大量分布式群决策问题,在分析企业合作动因基础上,提出一种集成多决策代理的质量屋求解、加权集成群决策结果的多维质量屋决策模型.该模型通过扩展传统质量功能配置(QFD),依据专业领域划分相对独立的决策代理,面向各代理构建出一系列平面质量屋;通过代理置信度加权方法集成多质量屋的求解结果,获得群决策综合结果.最后给出了该决策方法的应用案例.     

基于粗集方法的智能专家系统

文章主要介绍基于粗集方法的智能专家系统的基本构成、知识表达方式及学习推理方法。提出了利用不可分辨性或根据算法相容性进行知识简化,导出决策规则的方法,通过研究导师的知识与学习者的知识之间的依赖程度,找出每一概念的有用特征,进行知识简化和系统简化,导出决策规则的学习推理方法。     

Incentive contrats and strictly proper scoring rules

When a decision maker (DM) contracts with an expert to provide information, the nature of the contract can, create incentives for the expert, and it is up to the DM to ensure that the contract provides incentives that align the expert’s and DM’s interests. In this paper, scoring rules (and related functions) are viewed as such contracts and are reinterpreted in terms of agency theory and the theory of revelation games from economics. Although scoring rules have typically been discussed in the literature as devices for eliciting and evaluating subjective probabilities, this study relies on the fact that strictly proper scoring rules reward greater expertise as well as honest revelation. We describe conditions under which a DM can use a strictly proper scoring rule as a contract to give an expert an incentive to gather an amount of information that is optimal from the DM’s perspective. The conditions we consider focus on the expert’s cost structure, and we find that the DM must have substantial knowledge of that cost structure in order to design a specific contract that provides the correct incentives. The model and analysis suggest arguments for hiring and maintaining experts in-house rather than using outside consultants.     

Fuzzy TOPSIS approach for failure mode,effects and criticality analysis

In this paper, an alternative multi‐attribute decision‐making approach for prioritizing failures in failure mode, effects and criticality analysis (FMECA) is presented. The technique is specifically intended to overcome some of the limitations concerning the use of the conventional US MIL‐STD‐1629A method. The approach is based on a fuzzy version of the ‘technique for order preference by similarity to ideal solution’ (TOPSIS).The use of fuzzy logic theory allows one to avoid the intrinsic difficulty encountered in assessing ‘crisp’ values in terms of the three FMECA parameters, namely chance of failure, chance of non‐detection, and severity. With the proposed approach, the definition of a knowledge base supported by several qualitative rule bases is no longer required. To solve the fundamental question of ranking the final fuzzy criticality value, a particular method of classification is adopted, allowing a fast and efficient sorting of the final outcome. An application to an important Italian domestic appliance manufacturer and a comparison with conventional FMECA are reported to demonstrate the characteristics of the proposed method. Finally, a sensitivity analysis of the fuzzy judgement weights has confirmed that the proposed approach gives a reasonable and robust final priority ranking of the different causes of failure. Copyright © 2003 John Wiley & Sons, Ltd.