Analysis of experiments to determine individual colour preference

Finding an efficient way to understand individual colour preference is important to researchers and designers. This article compares three research strategies to test individual colour preference including two research experimental environments (online and laboratory) and two research methods (multiple choice for N‐alternative‐forced‐choice and multiple choice for rank‐order). Three psychophysical experiments have been carried out. Participants were presented with six colour patches (red, orange, yellow, green, blue, and purple) arranged in a random order on a computer display. In the first two experiments (Online experiment and Laboratory experiment I), participants were asked to indicate which colour square they prefer most; in the third experiment (Laboratory experiment II), participants were asked to rank their colour preferences of the six colour patches. The similarity between the results obtained from two experimental environments provides some validation for the online protocol and suggests that online experiments could be used more often. Pairwise comparisons for individual colour preference between genders and nationalities were carried out, and it was found that male and female responses were significantly different; but there was no statistical significance between Chinese and UK participants. The results from Monte Carlo simulations suggested that the rank‐order method should be preferred for individual colour preference studies involving small numbers of participants (especially less than 15 participants).     

Evacuation experiments in a virtual reality high‐rise building: exit choice and waiting time for evacuation elevators

The egress strategy in high‐rise buildings has traditionally been based on the sole use of stairs for evacuation. However, it is becoming more common to include evacuation elevators in the egress strategy in high‐rise buildings. Traditionally, evacuation elevators have not been allowed as an evacuation route, and people have been instructed to not use elevators in case of fire. This means that people might still not consider evacuation elevators even if they are designed to be safe in case of fire. Even if people choose evacuation elevators, they might not be willing to wait very long for an elevator to arrive. Virtual reality (VR) experiments were conducted to study exit choice and the waiting time for evacuation elevators in high‐rise buildings. The experiment was performed in a VR lab with a VR model of an existing high‐rise building. Results suggest that a simple way‐finding system using green flashing lights can influence people to more likely choose the elevator as their first evacuation choice. The results also show that the general trend is that people wait for either a limited time (<5 min) or a long time (>20 min). Copyright © 2015 John Wiley & Sons, Ltd.     

有机物水溶液粘度的关联和预测

在Eyring的液体粘性流动模型的基础上,根据Sandler的水溶液过量自由焓溶质聚集模型,导出有机物水溶液的粘度模型。利用该模型方程参数与温度的关系,可预测低压下各种温度和不同组成的有机物水溶液的粘度。用该模型计算了7个体系442个不同温度和组成的二元水溶液和3个体系164个不同温度和组成的三元水溶液的粘度,计算值与实验值的总平均相对偏差分别为1.554%和2.588%,计算值与实验数据吻合很好。     

The Role of Intravitreal Corticosteroids in the Treatment of DME: Predictive OCT Biomarkers

This work aims to summarize predictive biomarkers to guide treatment choice in DME. Intravitreal anti-VEGF is considered the gold standard treatment for centers involving DME, while intravitreal steroid treatment has been established as a second-line treatment in DME. However, more than 1/3 of the patients do not adequately respond to anti-VEGF treatment despite up to 4-weekly injections. Not surprisingly, insufficient response to anti-VEGF therapy has been linked to low-normal VEGF levels in the serum and aqueous humor. These patients may well benefit from an early switch to intravitreal steroid treatment. In these patients, morphological biomarkers visible in OCT may predict treatment response and guide treatment decisions. Namely, the presence of a large amount of retinal and choroidal hyperreflective foci, disruption of the outer retinal layers and other signs of chronicity such as intraretinal cysts extending into the outer retina and a lower choroidal vascular index are all signs suggestive of a favorable treatment response of steroids compared to anti-VEGF. This paper summarizes predictive biomarkers in DME in order to assist individual treatment decisions in DME. These markers will help to identify DME patients who may benefit from primary dexamethasone treatment or an early switch.     

A mathematical modeling approach for supply chain management under disruption and operational uncertainty

In this work, we proposed a two-stage stochastic programming model for a four-echelon supply chain problem considering possible disruptions at the nodes (supplier and facilities) as well as the connecting transportation modes and operational uncertainties in form of uncertain demands. The first stage decisions are supplier choice, capacity levels for manufacturing sites and warehouses, inventory levels, transportation modes selection, and shipment decisions for the certain periods, and the second stage anticipates the cost of meeting future demands subject to the first stage decision. Comparing the solution obtained for the two-stage stochastic model with a multi-period deterministic model shows that the stochastic model makes a better first stage decision to hedge against the future demand. This study demonstrates the managerial viability of the proposed model in decision making for supply chain network in which both disruption and operational uncertainties are accounted for.     

MODULAR DESIGN OF HEAT EXCHANGER NETWORKS

In a competitive market the design and operating decisions of the competing firms influence their own and their competitors’ profitability. Game theory suggests ways in which the competitors’ intentions can be allowed for Its use is illustrated with reference to a simple chemical plant example.

In the first part of the paper the decision making problem for competing firms is cast into a Lagrange multiplier formulation for constrained optimization. This gives new insight into the conventional micro-economic formulations, enables more comprehensive results to be obtained for the Russell and Bogaert problem (1980) and resolves some apparent discrepancies. The treatment also illustrates how a two-level decision problem can be solved in a competitive environment where, as is very commonly found, design decisions are irrevocable once the plant has been built but operating conditions can be adjusted to match the current situation.

The second part of the paper treats the case in which the two participating firms agree to co-operate to their mutual benefit. However, the way in which the benefits of this co-operation are divided between the participants is determined by the pressure each can exert on the other by potentially threatening behaviour. Numerical results are presented for the earlier example for various scenarios and compared with the results obtained for purely competitive activity in the first part of the paper     

GAME THEORY APPLIED TO CHEMICAL PLANT INVESTMENT DECISIONS IN A COMPETITIVE MARKET PART I: COMPETITIVE BEHAVIOUR

In a competitive market the design and operating decisions of the competing firms influence their own and their competitors' profitability. Game theory suggests ways in which the competitors' intentions can be allowed for Its use is illustrated with reference to a simple chemical plant example.

In the first part of the paper the decision making problem for competing firms is cast into a Lagrange multiplier formulation for constrained optimization. This gives new insight into the conventional micro-economic formulations, enables more comprehensive results to be obtained for the Russell and Bogaert problem (1980) and resolves some apparent discrepancies. The treatment also illustrates how a two-level decision problem can be solved in a competitive environment where, as is very commonly found, design decisions are irrevocable once the plant has been built but operating conditions can be adjusted to match the current situation.

The second part of the paper treats the case in which the two participating firms agree to co-operate to their mutual benefit. However, the way in which the benefits of this co-operation are divided between the participants is determined by the pressure each can exert on the other by potentially threatening behaviour. Numerical results are presented for the earlier example for various scenarios and compared with the results obtained for purely competitive activity in the first part of the paper     

Ecommerce interface colour and consumer decision making: Two routes of influence

This article reports an empirical study of the effects of interface colour (blue vs. grey) on ecommerce decision making. Participants viewed a set of products and information on the attributes of each and then made a series of purchase decisions that provided the basis for individual rankings of this set. Results support two proposed ‘routes of influence’. In the first, interface colour influences the cognitive capacities and strategies of consumers. This was evident as participants considered more attributes in the grey interface condition. Importantly, this was not mediated by participants' affective state. In the second, interface colour exerts influence via participants' aesthetic judgements. This was evident at a product‐specific level—with colour‐related differences in product selection decisions mediated (for two product alternatives) by participants' assessments of product aesthetics. There was also some support for a product‐generic effect of interface colour—with product aesthetics tending to be more influential in the grey condition. Overall, the results demonstrate the multifacetted nature of the influence of interface colour on consumer decision making in retail environments. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011;     

Handling of fuzzy decisions in the engineering management of large desalination plants

Engineering managers of large desalination projects often face several alternate strategies, the choice among which is rather unclear due to the lack of specific statistics to favor one choice over the others. Usually, the manager eliminates some options in a preliminary screening process, thus ending with a limited but viable alternative, each of which has its own merits. Fuzzy set theory provides a practicable tool in cases of management decisions under uncertainty where the factors affecting the decision are imprecise in nature. Fuzzy decision-making utilizes the set theory to provide ranges representing subjective judgements in absence of precise quantitative measures. The approach has been formalized in an interactive computer code which can be easily used by managers without the need for familiarization with the theoretical foundations of set theory.The fuzzy decision method is applied here to the problem of selecting management personnel for a large desalination plant in Saudi Arabia. Five alternate strategies are considered; namely use of foreign experts only, extensive use of tested software with minimum reliance on indigent personnel, mixture between the use of foreign personnel and computer software, dependence upon indigent personnel with foreign experience, or the employment of foreign expertise that is gradually phased out and replaced by trained locals. The decision would depend upon a set of attributes that describe the factors affecting the choice of the optimal option. Nevertheless, each attribute has a different degree of effectiveness and a distinct judgemental value for each of the five alternatives. A set of fourteen independent attributes is found for the problem under consideration including costs, lead time, continuity, language proficiency, dedication and compatibility with local culture. Each of the attributes has been provided with a verbal weight indicating level of importance. Then the attributes were ranked for each alternate strategy. Such verbal weights and ratings are input to the computer code called MAFDA to provide a combinetorial. The final analysis showed preferability of introduction of software management techniques followed by training of locals.     

A global optimization method for model selection in chemical reactions networks

Model inference is a challenging problem in the analysis of chemical reactions networks. In order to empirically test which, out of a catalogue of proposed kinetic models, is governing a network of chemical reactions, the user can compare the empirical data obtained in one experiment against the theoretical values suggested by the models under consideration. It is thus fundamental to make an adequate choice of the decision variables (e.g. initial concentrations of the different species in the tank) in order to have maximal separation between sets of concentrations provided by the theoretical models, making then easier to identify which of the theoretical models yields data closest to those obtained empirically under identical conditions.In this paper we illustrate how global optimization techniques can be successfully used to address the problem of model separation, as a basis for model selection. Some examples illustrate the usefulness of our approach.     

粗集理论及其在旋转机械故障诊断中的应用(四)决策表属性的约简

在旋转机械典型故障实验的基础上,按照粗糙集理论的要求,对采集的各种信息由数据库向符合粗集理论要求的知识库的转换,建立故障振动特征决策表。在决策功能不变的前提下,利用区分矩阵和区分方程,对决策属性进行简化,并寻找属性集的核和属性集合的选优。通过对4种典型旋转机械故障的频域特性表的约简,将6个条件属性简化为3个条件属性。     

Sequential Classification on Lattices with Experiment-Specific Response Distributions

Abstract

A Bayesian framework for sequential classification on finite lattice models is described in which response distributions are allowed to vary according to experiment. Optimal rates of convergence in classification are established. Intuitive and computationally simple experiment selection rules are proposed, and it is shown that this class of rules attains optimal rates almost surely under general conditions. A simulation study demonstrates that sequential classification can be conducted efficiently on lattices, with potentially great savings in experiment adminstration while maintaining high classification accuracy. This framework can be applied to adaptive testing for cognitive assessment and to other sequential classification problems such as group testing when experimental response distributions depend on pool composition.     

沈北、大庆混合减四线脱蜡油NMP精制及选择性系数求取

以沈北、大庆混合减四线脱蜡油为原料,进行NMP单级抽提试验,借助数学手段得到最优操作条件.NMP精制的最佳操作条件为:剂油比1.38(m/m),抽提温度60.8℃,含水量2.1%.在此操作条件下,精制油的收率为88.74%,60℃折光率为1.4776,黏度指数95.27.采用柱色谱法分析减四线脱蜡油族组成,测出所得四组...     

市场波动情况下氯碱企业的生产决策

介绍了在市场波动的情况下氯碱企业运用现代决策科学安排生产取得最佳效益的方法,对有关决策方法的软件用法进行了说明.     

透明塑料过滤器壳成型工艺分析

结合透明过滤器塑料壳的特点,分析了透明过滤器塑料壳制造的过程与方法,从成型工艺过程及成型工艺条件的选择与控制方面进行了讨论。重点介绍了成型工艺过程和工艺条件的设定,指出了各种透明过滤器壳成型过程中可能出现的缺陷及其解决方法。     

Modellübertragung in der Verfahrenstechnik

Model scale-up in chemical engineering . Similarity theory and the theory of models based thereon are working tools which permit reasonable planning of experiments, their execution with a minimum of effort, and their evaluation in such a way as to provide reliable information about the design and the operating conditions of the technical plant – provided these methods are used in good time and in the proper manner. A brief introduction to the problems involved and to the methodology of similarity theory is provided by the introductory section and the first example. Four more problems and their solutions according to similarity theory serve to answer questions concerning the size of the experimental scale, the choice of material system used in the experiment, and the problem of scale-up under conditions of partial similarity. Two of these examples clearly illustrate that an inadequate knowledge of the material parameters (e. g. for foams and slurries) necessitates model measurements on the technical system with a change of scale.     

Diagnosis using backpropagation neural networks—analysis and criticism

Artificial neural networks based on a feedforward architecture and trained by the backpropagation technique have recently been applied to static fault diagnosis problems. The networks are used to classify measurement vectors into a set of predefined categories that represent the various functional and malfunctional states of the process. While the networks can usually produce decision surfaces that correctly classify the training examples, regions of the input space not occupied by training data are classified arbitrarily. As a result, the networks may not accurately extrapolate from the training data. Although extrapolation is not required under ideal circumstances, in practice the network may be required to extrapolate when undersized training sets are used, when parent distributions of fault classes undergo shifts subsequent to training, and when the input data is corrupted by missing or biased sensors. These situations cause relatively high error rates for the neural classifier. A related probem is that the networks cannot detect when they lack the data for a reliable classification, a serious deficiency in many practical applications. Classifiers based on distance metrics assign regions of the input space according to their proximity to the training data, and thus extrapolation is not arbitrary but based on the most relevant data. Distance-based classifiers perform better under nonideal conditions and are to be preferred to neural network classifiers in diagnostic applications.     

ON-LINE VARIANCE ESTIMATION FOR THE STEADY STATE BAYESIAN FORECASTING MODEL

Abstract. The Bayesian approach to forecasting provides the user with distributional information which plays an important role in decision making. However, in practice, the process variances are unknown and therefore if the model operates with fixed estimates of these variances, the distributional information can be misleading. A method is proposed in this paper which produces on-line maximum likelihood estimates of the variances for the steady state Dynamic Linear model, whose updating employs the Kalman filter. It makes use of a one-dimensional class I multi-process model approach which requires a set of initial values. In the limit the variance estimates are independent of the choice of initial values, but some practical suggestions are made which enable the procedure to converge faster. A numerical illustration and a number of points relevant to the performance of the model when tested under different choices of starting values are also given.     

Selection of desalination technology, a decision analysis approach and a case study

The state-of-the-art desalination technologies are screened from the point of view of meeting the Saudi Arabian requirements including water/power demand, forecast and future expansions. Also, compatibility with the Saudi Arabian technology development, environment and manpower availability is considered.

Considering MSF and ED as alternate technologies, multi-objective decision analysis is used to select the most preferred technology for Saudi Arabia. The methodology is based upon assessment of the attributes that affect the selection. Some of those attributes include: reliability, operability, maintainability, manpower requirements and utilization of national resources. Utility values are then computed to reflect the preference of decision makers and the values are then combined to give the overall utility for each choice.

The selection method is described and the formal numerical analysis are presented. The methodology is applicable for various situations and is flexible enough for introducing other sets of attributes.