Uncertainty Profile Research Articles

Uncertainty profile for NIR analysis of tanshinone I content in tanshinone extract powders

Uncertainty profile for NIR analysis of tanshinone I content in tanshinone extract powders

Application of a New Strategy of Validation Based on “β,γ-Content Tolerance Interval” for Checking the Chiral Chromatography Method for Quantification of the Chiral Impurity of Levofloxacin

A simple and accurate chiral high performance liquid chromatography (HPLC) method was developed for determination of Levofloxacin and its chiral impurity (R)-enantiomer. The chiral impurity Levofloxacin separation method was optimized by Box-Behnken design and validated by an innovative analytical approach recently developed in our laboratory. This last approach as well as uncertainty estimation consists of building a graphical decision-making tool, based on the β,γ-content tolerance interval, called the uncertainty profile. The proposal approach applied to the optimized chiral separation method of Levofloxacin shows its fitness.

Derivation of uncertainty functions from validation studies in biological fluids: Application to the analysis of caffeine and its major metabolites in human plasma samples

Procedures for estimating the measurement uncertainty (MU) of the concentration of a given analyte in a sample are of major concern for analytical chemists. Unfortunately, it is still unclear how and why MU should be assessed. While several possibilities exist, an appropriate approach consists in using method validation data for the evaluation of MU. This was demonstrated by a validation study achieved in the framework of a clinical study related to caffeine in sports medicine, where the results were used for the evaluation of MU. After validation of the method developed using ultra-high pressure liquid chromatography–mass spectrometry for caffeine and its three main metabolites, accuracy profiles were built for each analyte. The first important conclusion is that the developed method was valid for all compounds and met the given specifications for the application (fit for purpose). Relevant estimates of combined standard uncertainty were computed to obtain uncertainty functions, which allow obtaining values of MU as a function of the concentration of the analyte. The great advantage of both uncertainty function and uncertainty profile is the development of a continuous model that enables easy calculation of the standard, expanded and relative expanded uncertainty at any concentration within the validation domain. In fact, the expanded uncertainty interval is assumed to contain 95% of all possible measurements, regardless of the concentration. Finally, the uncertainty function enables the determination of the lowest limit of quantification by selecting adequate acceptance limits, with the limit of quantification being defined as the point where the relative uncertainty equals the acceptance limit threshold. It has to be noted that further discussions remain mandatory to establish which criteria should be applied to define an adequate decision threshold, and the proposal afforded in this work may open new avenues in this direction.

Probabilistically Weighted OWA Aggregation

In decision-making under uncertainty we have a collection of alternatives from which we must choose one. Associated with each alternative is an uncertainty profile consisting of the set of possible outcomes that can occur if we choose this alternative along with some indication of the uncertainty associated with the outcomes. Since it is difficult to compare these uncertainty profiles one commonly used approach is to obtain a representative value, an aggregation of the information in the uncertainty profile, and use these to compare the alternatives. The method that we use to aggregate the information in the uncertainty profile must reflect aspects of the decision attitude of the decision maker. Here we look at the role that the ordered weighted averaging (OWA) can play in the aggregation process used to obtain these representative values. Since an uncertainty profile can involve a discrete set of possible outcomes or an interval of possible outcomes we provide the OWA operator with the capability to perform aggregations in either of these environments. In addition we provide the OWA operator with the ability to perform aggregations in situations where the arguments being aggregated, the potential outcomes, have an associated uncertainty, probability of occurrence. Particularly notable is the extension the OWA operator to perform aggregation with arguments consisting of a continuum of values with an associated probability density function. We also look at the cases where the uncertainty is modeled with a belief structure as well a possibility distribution.

Impact Of Cognitive Profile And Information Uncertainty On Herding Behavior Of Investor

Primary objective of this paper was to investigate the impact of information uncertainty and cognitive profile of investors on herding behavior. We analyzed the behavior of investors influenced by the decision of other investors due to the lack of information and cognitive profile of investors. Well-designed experiments in three sessions are conducted for this study. These experiments were conducted in three stages to check the impact of different levels of information and conditions on the herding behavior. This study reflects that there is a positive relationship between the information uncertainty and the biasness of investor's behavior and occurrence of herding. Studies also reveal that the previously existing financial information and previously shown behavior in the market also encourages the herding phenomenon prevailing in the market. Researches indicate that the change in the Cognitive profile of the investors is more significant due to the increase in the financial information and the historical record of the transaction. There is also a significant change in the biasness of the investor due to the public information.

Developing the Agile IS Development Practices in Large-Scale IT Projects: The Trust-Mediated Organizational Controls and IT Project Team Capabilities Perspectives

This paper is based on multiple case studies on the construction of the Beijing Capital International Airport Terminal 3 in preparation for the 2008 Olympic Games that investigated the processes of instilling agile IS development practices in large-scale IT projects. This study develops useful theoretical constructs that will help researchers and practitioners who wish to learn about agile IS development practices as developed in large-scale IT projects. Adopting a contingent view, we uncover four factors that are critical in this development processes, namely: project uncertainty profile and project completion urgency; IT project team capabilities; organizational control mechanisms; and trust relationships among the IT project team, the vendors, and the users. Depending on the unpredictable nature of the project and the trust level among the IT project team, the vendors, and the users, we have uncovered the IT project team capabilities and the organizational control mechanisms that are needed to assure the success of a large-scale IT project. We posit that the interplay between the IT project team capabilities and the trust-mediated organizational control mechanisms forms the theoretical basis that defines agile IS development practice in large-scale IT projects. We argue that our findings provide insights to practitioners who are attempting to introduce agile IS development practices into any large-scale IT project. From a research perspective, the theory developed in this paper also sheds light on the importance of adopting a contingency view when researching agile IS development practices in a large-scale IT project and the factors to consider. This underpinning theoretical perspective will aid in the design of all future researches.

Analysing Web-Orchestrations Under Stress Using Uncertainty Profiles

An orchestration is a multi-threaded computation which invokes a number of remote services. In practice the responsiveness of a web-service fluctuates with demand; during surges in activity service responsiveness may be degraded, perhaps even to the point of failure. An uncertainty profile formalises a user’s perception of the effects of stress on an orchestration of web-services; it describes a strategic situation, modelled by a zero-sum angel-daemon game. Stressed webservice scenarios are analysed, using game theory, in a realistic way, lying between over-optimism (services are entirely reliable) and over-pessimism (all services are broken). The “resilience” of an uncertainty profile can be assessed using the valuation of its associated zero-sum game. In order to demonstrate the validity of the approach we consider two measures of resilience and a number of different stress models. It is shown how (i) uncertainty profiles can be ordered by risk (as measured by game valuations) and (ii) the structural properties of risk partial orders can be analysed.

Impact of Cognitive Profile and Information Uncertainty on Herding Behavior of Investor

Primary objective of this paper was to investigate the impact of information uncertainty and cognitive profile of investors on herding behavior. We analyzed the behavior of investors influenced by the decision of other investors due to the lack of information and cognitive profile of investors. Well designed experiments in three sessions are conducted for this study. These experiments were conducted in three stages to check the impact of different levels of information and conditions on the herding behavior. This study reflects that there is a positive relationship between the information uncertainty and the biases of investor's behavior and occurrence of herding. Studies also reveal that the previously existing financial information and previously shown behavior in the market also encourages the herding phenomenon prevailing in the market. Researches indicate that the change in the Cognitive profile of the investors is more significant due to the increase in the financial information and the historical record of the transaction. There is also a significant change in the biases of the investor due to the public information.

An overall uncertainty approach for the validation of analytical separation methods

The aim of this paper is to recommend a new strategy for the analytical validation based on the uncertainty profile as a graphical decision-making tool, and to exemplify a novel method to estimate the measurement uncertainty. Indeed, the innovative formula that we offer to assess the uncertainty is based on the calculation of the β-content tolerance interval. Three chemometric methodologies are exposed to build the (β, γ) tolerance interval, namely: the Satterthwaite approximation, the GPQ method (generalized pivotal confidence) and the MLS procedure (modified large simple). Furthermore, we illustrate the applicability and flexibility of the uncertainty profile to assess the fitness of the purpose of chromatographic and electrophoretic analytical methods, which use different instrumental techniques such as liquid chromatography (LC-UV, LC-MS), gas chromatography (GC-FID, GC-MS) and capillary electrophoresis (CE, CE-MS). In addition, we demonstrate here that (β, γ) tolerance intervals will provide perfect estimates of the routine uncertainty. In particular, we show that there is no difference statistically between the uncertainties estimated by our methodology as of the validation stage with those obtained from the routine phase.

In-Flight Dynamical Method to Verify Sample Collection for Small-Body Sample Return Mission

An in-flight dynamical method is introduced for use by sample-collection missions to identify the presence and quantity of collected sample material. The method, denoted as G-Sample, implements a maximum-likelihood estimator to identify the collected samplemass, based on onboard force-sensormeasurements, thruster firings, and a dynamicsmodel of the spacecraft. In terms of hardware, G-Sample requires only a force sensor. Hardware complexities are avoided by treating sample mass determination largely as a computational problem in modern estimation, rather than requiring the need for additional specialized equipment or sophisticated sensing architectures. Simulation examples are provided for a spacecraft configuration with a sample-collection device mounted on the end of an extended boom. In one representative example, a 1000 g sample mass is estimated to within 110 g (95% confidence) under realistic assumptions of thruster profile error, spacecraft parameter uncertainty, and sensor noise. For convenience to future mission design, an overall sample-mass estimation error budget is developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

‘I know the type of people I work well with’: student anxiety in multicultural group projects

Research indicates that the uncertainty created when students are required to work in groups for assessed projects induces anxiety, which can manifest itself both cognitively and affectively. Such anxiety may influence student attitudes towards the selection and formation of the groups. This study explored whether different methods of group formation impact on student anxiety levels and, in addition, whether the home language of the students is associated with the different levels of anxiety. In this study, 165 first-year tertiary students were surveyed before and after completion of assessed group projects. The findings reveal that the uncertainty profile produced different levels of anxiety.

Investigating a training supporting shared decision making (IT'S SDM 2011): study protocol for a randomized controlled trial

BackgroundShared Decision Making (SDM) is regarded as the best practice model for the communicative challenge of decision making about treatment or diagnostic options. However, randomized controlled trials focusing the effectiveness of SDM trainings are rare and existing measures of SDM are increasingly challenged by the latest research findings. This study will 1) evaluate a new physicians' communication training regarding patient involvement in terms of SDM, 2) validate SDMMASS, a new compound measure of SDM, and 3) evaluate the effects of SDM on the perceived quality of the decision process and on the elaboration of the decision.MethodsIn a multi-center randomized controlled trial with a waiting control group, 40 physicians from 7 medical fields are enrolled. Each physician contributes a sequence of four medical consultations including a diagnostic or treatment decision.The intervention consists of two condensed video-based individual coaching sessions (15min.) supported by a manual and a DVD. The interventions alternate with three measurement points plus follow up (6 months).Realized patient involvement is measured using the coefficient SDMMASS drawn from the Multifocal Approach to the Sharing in SDM (MAPPIN'SDM) which includes objective involvement, involvement as perceived by the patient, and the doctor-patient concordance regarding their judges of the involvement. For validation purposes, all three components of SDMMASS are supplemented by similar measures, the OPTION observer scale, the Shared Decision Making Questionnaire (SDM-Q) and the dyadic application of the Decisional Conflict Scale (DCS). Training effects are analyzed using t-tests. Spearman correlation coefficients are used to determine convergent validities, the influence of involvement (SDMMASS) on the perceived decision quality (DCS) and on the elaboration of the decision. The latter is operationalised by the ELAB coefficient from the UP24 (Uncertainty Profile, 24 items version).DiscussionDue to the rigorous blinded randomized controlled design, the current trial promises valid and reliable results. On the one hand, we expect this condensed time-saving training to be adopted in clinical routine more likely than previous trainings. On the other hand, the exhaustivity of the MAPPIN'SDM measurement system qualifies it as a reference measure for simpler instruments and to deepen understanding of decision-making processes.Trial registrationCurrent Controlled Trials ISRCTN78716079

What is the best way to ensure that valid analytical methods are used for food control?

Monitoring and Quality Assurance in the Food Supply Chain is a Network of Excellence funded by the European Union. This Network of Excellence aims to make food safer by harmonizing the quality of methods used for food control. Part of this process involves the development and validation of new methods, including rapid methods and emerging technologies; the production of practical harmonized guidance on method validation and criteria for analytical methods; and the production of reference and testing materials to be used for food control. New technologies and analytical research enable us to measure new and emerging food contaminants and other chemicals that may be a threat to the health of the consumer. Once risk assessment confirms the threat, legislation may be enacted to limit the amount of these chemicals present in food that is sold. In order to enforce this legislation it is necessary to be able to detect the presence of chemical and measure its concentration in food. Hence, the consumer protection provided by enforcement depends on how well the measurement method performs. We need to be confident that measurement methods are performing sufficiently well to protect the consumer, without leading to the rejection of large quantities of food that comply with legislation. A number of approaches that can be used to provide confidence include: the use of standard methods, the use of analytical criteria that describe the performance of a method, and consideration of fitness for purpose based on measurement uncertainty. This paper examines the utility and ease of application of the different approaches. In addition a simple method for assessing fitness for purpose, the uncertainty profile, is discussed. ROSE M, POMS R, MACARTHUR R, PÖPPING B & ULBERTH F (2011). What is the best way to ensure that valid analytical methods are used for food control?. Quality Assurance and Safety of Crops & Foods, 3, 123–134

Uncertainty profiles for the validation of analytical methods

This article aims to expose a new global strategy for the validation of analytical methods and the estimation of measurement uncertainty. Our purpose is to allow to researchers in the field of analytical chemistry get access to a powerful tool for the evaluation of quantitative analytical procedures. Indeed, the proposed strategy facilitates analytical validation by providing a decision tool based on the uncertainty profile and the β-content tolerance interval. Equally important, this approach allows a good estimate of measurement uncertainty by using data validation and without recourse to other additional experiments.In the example below, we confirmed the applicability of this new strategy for the validation of a chromatographic bioanalytical method and the good estimate of the measurement uncertainty without referring to any extra effort and additional experiments. A comparative study with the SFSTP approach [1] showed that both strategies have selected the same calibration functions.The holistic character of the measurement uncertainty compared to the total error was influenced by our choice of profile uncertainty. Nevertheless, we think that the adoption of the uncertainty in the validation stage controls the risk of using the analytical method in routine phase.

Medicine expert system dynamic Bayesian Network and ontology based

The paper proposes an application framework to be used for medicine assisted diagnosis based on ontology and Bayesian Network (DBNO). There are two goals: (1) to separate the domain knowledge from the probabilistic information and (2) to create an intuitive user interface. The framework architecture has three layers: knowledge, uncertainty model and user interface. The contributions of the domain experts are decoupled, the ontology builder will create the domain concepts and relationships focusing on the domain knowledge only. The uncertainty model is Bayesian Network and the probabilities of the variables states are stored in a profile repository. The diagnostician will use the user interface feeded with the domain ontology and one uncertainty profile. The application was tested on a sample medicine model for the diagnose of heart disease.

Herding, information uncertainty and investors' cognitive profile

PurposeThe purpose of this paper is to analyze the interaction between the availability of financial information and individuals' cognitive profiles to explain investors' herding behavior.Design/methodology/approachThe authors designed and conducted an experiment to observe the behavior of subjects in three settings, each with a different level of information.FindingsResults confirm that a dependence relation exists between information, investors' behavioral biases and the herding phenomenon. Moreover, the experiment shows that information concerning the number of previous transactions in the market is particularly relevant to explain herding propensity among investors. The findings indicate that the cognitive profile of investors is more relevant as the availability of information increases and the number of previous transactions in the market is low.Research limitations/implicationsFuture research should examine further the best way to measure the individual's cognitive profile and its interaction with information limitation in financial markets. The presence of high levels of uncertainty favors herding behavior regardless of inter‐individual differences, and only when the availability of information is high and the number of transactions is low does the subjects' cognitive profile explain the investors' herding behavior. Finally, it is observed that not all public information receives the same attention by investors. The attractiveness of public information requires further attention.Social implicationsThe herding phenomenon is difficult to anticipate because there are factors of a very diverse nature that intervene.Originality/valueThe research described in this paper measures investors' cognitive profile to identify the interaction between availability of information, cognitive profile and herding.

A method for addressing research gaps in HTA, developed whilst evaluating robotic-assisted surgery: a proposal

BackgroundWhen evaluating health technologies with insufficient scientific evidence, only innovative potentials can be assessed. A Regional policy initiative linking the governance of health innovations to the development of clinical research has been launched by the Region of Emilia Romagna Healthcare Authority. This program, aimed at enhancing the research capacity of health organizations, encourages the development of adoption plans that combine use in clinical practice along with experimental use producing better knowledge. Following the launch of this program we developed and propose a method that, by evaluating and ranking scientific uncertainty, identifies the moment (during the stages of the technology's development) where it would be sensible to invest in research resources and capacity to further its evaluation. The method was developed and tested during a research project evaluating robotic surgery.MethodsA multidisciplinary panel carried out a 5-step evaluation process: 1) definition of the technology's evidence profile and of all relevant clinical outcomes; 2) systematic review of scientific literature and outline of the uncertainty profile differentiating research results into steady, plausible, uncertain and unknown results; 3) definition of the acceptable level of uncertainty for investing research resources; 4) analysis of local context; 5) identification of clinical indications with promising clinical return.ResultsOutputs for each step of the evaluation process are: 1) evidence profile of the technology and systematic review; 2) uncertainty profile for each clinical indication; 3) exclusion of clinical indications not fulfilling the criteria of maximum acceptable risk; 4) mapping of local context; 5) recommendations for research.Outputs of the evaluation process for robotic surgery are described in the paper.ConclusionsThis method attempts to rank levels of uncertainty in order to distinguish promising from hazardous clinical use and to outline a research course of action. Decision makers wishing to tie coverage policies to the development of scientific evidence could find this method a useful aid to the governance of innovations.

Construction of Measurement Uncertainty Profiles for Quantitative Analysis of Genetically Modified Organisms Based on Interlaboratory Validation Data

A method is presented for estimating the size of uncertainty associated with the measurement of products derived from genetically modified organisms (GMOs). The method is based on the uncertainty profile, which is an extension, for the estimation of uncertainty, of a recent graphical statistical tool called an accuracy profile that was developed for the validation of quantitative analytical methods. The application of uncertainty profiles as an aid to decision making and assessment of fitness for purpose is also presented. Results of the measurement of the quantity of GMOs in flour by PCR-based methods collected through a number of interlaboratory studies followed the log-normal distribution. Uncertainty profiles built using the results generally give an expected range for measurement results of 50-200% of reference concentrations for materials that contain at least 1% GMO. This range is consistent with European Network of GM Laboratories and the European Union (EU) Community Reference Laboratory validation criteria and can be used as a fitness for purpose criterion for measurement methods. The effect on the enforcement of EU labeling regulations is that, in general, an individual analytical result needs to be < 0.45% to demonstrate compliance, and > 1.8% to demonstrate noncompliance with a labeling threshold of 0.9%.

Uncertainty reduction for improved mishap probability prediction: Application to level control of distillation unit

At all levels, the understanding of uncertainty associated with risk of major chemical industrial hazards should be enhanced. In this study, a quantitative risk assessment (QRA) was performed for a knockout drum in the distillation unit of a refinery process and then probabilistic uncertainty analysis was applied for this QRA. A fault tree was developed to analyze the probability distribution of flammable liquid released from the overfilling of a knockout drum. Bayesian theory was used to update failure rates of the equipment so that generic information from databases and plant equipment real life data are combined to gain all available knowledge on component reliability. Using Monte Carlo simulation, the distribution of top event probability was obtained to characterize the uncertainty of the result. It was found that the uncertainty of basic event probabilities has a significant impact on the top event probability distribution. The top event probability prediction uncertainty profile showed that the risk estimation is improved by reducing uncertainty through Bayesian updating on the basic event probability distributions. The whole distribution of top event probability replaces point value in a risk matrix to guide decisions employing all of the available information rather than only point mean values as in the conventional approach. The resulting uncertainty guides where more information or uncertainty reduction is needed to avoid overlap with intolerable risk levels.

Towards a Theory of Organizational Information Services

The use of information technology (IT) in organizations has undergone dramatic changes during the past 30 years. As a result, it has become increasingly common to adopt services rather than traditional systems perspective to more accurately capture contemporary practices. There is, however, a lack of theories that can help us understand, assess, and design information services in organizational contexts. On this backdrop, we combine general notions of information processing options and requirements to outline a contingency theory of organizational use of information services. The theory suggests that information services are configurations of heterogeneous information processing capabilities; these services are evoked by organizational actors to help execute tasks, and evoking different configurations may lead to equally satisfactory outcomes. The theory distinguishes between four types of services computational, adaptive, networking, and collaborative services, and it suggests that organizational actors need portfolios of information services that are suited to the equivocality and uncertainty profile of the information processing they face. The paper defines four types of services and how they relate to information processing requirements; it applies the theory to a study of information services in response to vehicle policing; and it outlines how the theory relates to standardization and unintended consequences of information services. We conclude by discussing the theory and its implications for research and practice.