Journal articles on the topic 'Model credibility assessment'
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Pryor, S. C., and J. T. Schoof. "Differential Credibility Assessment for Statistical Downscaling." Journal of Applied Meteorology and Climatology 59, no. 8 (August 1, 2020): 1333–49. http://dx.doi.org/10.1175/jamc-d-19-0296.1.
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AbstractClimate science is increasingly using (i) ensembles of climate projections from multiple models derived using different assumptions and/or scenarios and (ii) process-oriented diagnostics of model fidelity. Efforts to assign differential credibility to projections and/or models are also rapidly advancing. A framework to quantify and depict the credibility of statistically downscaled model output is presented and demonstrated. The approach employs transfer functions in the form of robust and resilient generalized linear models applied to downscale daily minimum and maximum temperature anomalies at 10 locations using predictors drawn from ERA-Interim reanalysis and two global climate models (GCM; GFDL-ESM2M and MPI-ESM-LR). The downscaled time series are used to derive several impact-relevant Climate Extreme (CLIMDEX) temperature indices that are assigned credibility based on 1) the reproduction of relevant large-scale predictors by the GCMs (i.e., fraction of regression beta weights derived from predictors that are well reproduced) and 2) the degree of variance in the observations reproduced in the downscaled series following application of a new variance inflation technique. Credibility of the downscaled predictands varies across locations and between the two GCM and is generally higher for minimum temperature than for maximum temperature. The differential credibility assessment framework demonstrated here is easy to use and flexible. It can be applied as is to inform decision-makers about projection confidence and/or can be extended to include other components of the transfer functions, and/or used to weight members of a statistically downscaled ensemble.
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Wauchope, R. Don. "Environmental Risk Assessment of Pesticides: Improving Simulation Model Credibility." Weed Technology 6, no. 3 (September 1992): 753–59. http://dx.doi.org/10.1017/s0890037x00036162.
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Registrant use of computer simulation modeling is generally accepted by regulators in lieu of some experimental data for risk assessment, provided worst-case assumptions and extremely conservative criteria for negligible risk are used. These requirements taken together mean that only extreme cases escape the requirement for actual environmental data. This conservatism reflects the uncertainty in both exposure estimates by the models and in the hazard estimates from toxicologists. Until the credibility of estimated environmental concentrations given by models is improved by more experimental data and experience on the part of both registrants and regulators, the models will continue to be considered not-validated by many. There are four current developments that provide a compromise between the two impossible extremes of total model validation and total field measurement: (1) as models develop more process detail the parameters become more fundamental in nature and these are generally more amenable to independent estimation or measurement; (2) the reporting of probabilistic analyses and probable errors of results by modelers will enhance credibility; (3) the development of data sets for specific crop/site/pesticide/weather scenarios will allow users to modify those parts of the input they are concerned with while retaining confidence that parameters with which they are unfamiliar will have reasonable values; and (4) meso-scale and micro-scale physical simulation experiments can fill the gap between laboratory and field results. The most important need for enhancing model credibility is full access by the pesticide science community to all the information available, so that we may increase our understanding. Legal mechanisms should be considered for longer ownership of exclusive marketing rights of active ingredients, in exchange for complete public disclosure of the environmental fate and toxicology data submitted to regulatory agencies.
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Zhu, Mingxun, Xiaohong Chen, Xinxing Luo, and Fujun Liu. "Software credibility assessment model based on back propagation network." International Journal of Computational Systems Engineering 2, no. 2 (2015): 66. http://dx.doi.org/10.1504/ijcsyse.2015.077069.
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Susanti, Dwi, and Sokono Sukono. "Calculating Premium Credibility Using the Buhlmann-Straub Modelwith Nonparametric Assessment." International Journal of Global Operations Research 1, no. 1 (February 4, 2020): 20–32. http://dx.doi.org/10.47194/ijgor.v1i1.15.
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When an insurance company calculates the premium it will divides the policy holders into groups. The division is considered based on risk level in each group. The problem is then to devise a way of combining the experience risk of the group with the experience of the individual risk to calculate the premium, so then Credibility Theory provides a solution to this problem.This script discuss about calculation of credibility premium use Buhlmann-Straub Model with nonparametric estimation to the aggregate claim amount data set within few years observation in some group of policy holders in general insurance. By using credibility theory we can calculate the value of credibility factor and credibility premium or future premium. The value of premium credibility is calculated from only one group of policyholders from the previous year's data. For better value of premium credibility, data with more experience years and the policyholder group better reflect the total loss value during the observation year.The result of this calculation are credibility factor per group, average credibility premium per members in group and credibility premium total for the last year for each group. We can obtain total losses and total premium which surprisingly equal.
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Yao, Jinglong, Ling Xing, and Honghai Wu. "A Microblog Content Credibility Evaluation Model Based on the Influence of Sentiment Polarity." Mobile Information Systems 2022 (May 31, 2022): 1–11. http://dx.doi.org/10.1155/2022/8983534.
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False content in microblogs affects users’ judgment of facts. An evaluation of microblog content credibility can find false information as soon as possible, which ensures that social networks maintain a positive environment. The influence of sentiment polarity can be used to analyze the correlation between sentiment polarity in comments and Weibo content through semantic features and sentiment features in comments, to improve the effect of content credibility assessment. This paper proposes a Weibo content credibility evaluation model, CEISP (Credibility Evaluation based on the Influence of Sentiment Polarity). The semantic features of microblog content are extracted by a bidirectional-local information processing network. Bidirectional long short-term memory (BiLSTM) is used to mine the sentiment features of comments. The attention mechanism is used to capture the impact of different sentiment polarities in comments on microblog content, and the influence of sentiment polarities is obtained for the credibility assessment of microblog content. The experimental results on real datasets show that the evaluation performance of the CEISP model is improved compared with the comparison model. Compared with the existing Att-BiLSTM model, the evaluation accuracy of the CEISP model is improved by 0.0167.
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Shafqat, Wafa, Yung-Cheol Byun, and Namje Park. "Effectiveness of Machine Learning Approaches Towards Credibility Assessment of Crowdfunding Projects for Reliable Recommendations." Applied Sciences 10, no. 24 (December 18, 2020): 9062. http://dx.doi.org/10.3390/app10249062.
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Recommendation systems aim to decipher user interests, preferences, and behavioral patterns automatically. However, it becomes trickier to make the most trustworthy and reliable recommendation to users, especially when their hardest earned money is at risk. The credibility of the recommendation is of magnificent importance in crowdfunding project recommendations. This research work devises a hybrid machine learning-based approach for credible crowdfunding projects’ recommendations by wisely incorporating backers’ sentiments and other influential features. The proposed model has four modules: a feature extraction module, a hybrid LDA-LSTM (latent Dirichlet allocation and long short-term memory) based latent topics evaluation module, credibility formulation, and recommendation module. The credibility analysis proffers a process of correlating project creator’s proficiency, reviewers’ sentiments, and their influence to estimate a project’s authenticity level that makes our model robust to unauthentic and untrustworthy projects and profiles. The recommendation module selects projects based on the user’s interests with the highest credible scores and recommends them. The proposed recommendation method harnesses numeric data and sentiment expressions linked with comments, backers’ preferences, profile data, and the creator’s credibility for quantitative examination of several alternative projects. The proposed model’s evaluation depicts that credibility assessment based on the hybrid machine learning approach contributes efficient results (with 98% accuracy) than existing recommendation models. We have also evaluated our credibility assessment technique on different categories of the projects, i.e., suspended, canceled, delivered, and never delivered projects, and achieved satisfactory outcomes, i.e., 93%, 84%, 58%, and 93%, projects respectively accurately classify into our desired range of credibility.
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Feng, Yanling, Jixiong Hu, Rui Duan, and Zhuming Chen. "Credibility Assessment Method of Sensor Data Based on Multi-Source Heterogeneous Information Fusion." Sensors 21, no. 7 (April 5, 2021): 2542. http://dx.doi.org/10.3390/s21072542.
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The credibility of sensor data is essential for security monitoring. High-credibility data are the precondition for utilizing data and data analysis, but the existing data credibility evaluation methods rarely consider the spatio-temporal relationship between data sources, which usually leads to low accuracy and low flexibility. In order to solve this problem, a new credibility evaluation method is proposed in this article, which includes two factors: the spatio-temporal relationship between data sources and the temporal correlation between time series data. First, the spatio-temporal relationship was used to obtain the credibility of data sources. Then, the combined credibility of data was calculated based on the autoregressive integrated moving average (ARIMA) model and back propagation (BP) neural network. Finally, the comprehensive data reliability for evaluating data quality can be acquired based on the credibility of data sources and combined data credibility. The experimental results show the effectiveness of the proposed method.
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Wang, Bowen, Haitao Xiong, and Chengrui Jiang. "A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/347619.
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As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.
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Zhong, Yin Zhen, Min Xia Liu, and Wei Chun Gao. "An Improved Education Evaluation Model Based on SEEQ." Advanced Materials Research 926-930 (May 2014): 4457–60. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.4457.
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In order to improve the credibility of vocational teaching evaluation, the paper summarizes the traditional SEEQ evaluation model, and analyzes some existing deficiencies. Combined with the demand of current teaching evaluation, a kind of improved teaching evaluation model-VSEEQ is proposed. The model increases two new evaluation dimensions. Through the research sampling, the data is conducted the KMO and Bartlett analysis. The experiment can show that VSEEQ evaluation result can accurately reflect the practical issue existed in the teaching, thus greatly improving the credibility of teaching assessment.
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Tashtoush, Yahya M., Aisha Zaidan, and Izzat M. Alsmadi. "Implications for Website Trust and Credibility Assessment." International Journal of E-Entrepreneurship and Innovation 3, no. 4 (October 2012): 17–33. http://dx.doi.org/10.4018/jeei.2012100102.
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With the expansion of the Internet services provided to users to cover almost all areas that were dominated by traditional face-to-face and location based businesses, one of the major challenges for such expansion is security and its related concerns. Customers or users need to trust the websites they visit in terms of the information or content. This research proposes a new formula for evaluating the credibility (called XD TRank) metric of websites. A case study of 40 selected websites in Jordan is used to assess the proposed credibibility metric. The metrics required to assess Websites and pages credibility are collected and evaluated based on 25 existing metrics and built a model using SPSS by applying stepwise linear regression analysis to predict the XD TRank. Results showed that there is a broad range of metrics that affect the credibility of a website or a webpage and their impact on credibility may vary on their significancy or impact on the trust rank metric. For e-business in particular, trust rank metrics can be used part of quality assurance and auditing processes. Those can be important assets for users to be able to distinguish known, popular and reliable e-commerce websites from spammers or websites which try to trick novice users. Trust rank can be also used like a logo in all Website pages to alert users if they were redirected to phishing pages.
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O'Reilly, Norm, Gashaw Abeza, Andy Fodor, Eric MacIntosh, John Nadeau, Lane MacAdam, Gary Pasqualicchio, Mark Dottori, and Heather Jane Lawrence. "Impact studies in sport: the development of an assessment process model." Sport, Business and Management: An International Journal 10, no. 4 (May 11, 2020): 381–402. http://dx.doi.org/10.1108/sbm-05-2018-0037.
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PurposeThe criticisms put forward against economic impact studies lead to a key question: “Is it possible to measure the impact of sporting properties and events in a holistic, conservative, and reliable way?” This research endeavors to build on the academic literature to add to the scope and rigor of economic impact research by proposing an impact assessment process model for practitioners that facilitates employment of a holistic, conservative and reliable impact study and seeks to address these concerns.Design/methodology/approachUsing seven identified key realities that highlight the challenges facing impact studies, and adopting a collaborative self-ethnographic methodological approach, the work highlights lessons learned from four empirical economic impact studies undertaken by the authors over a five-year period.FindingsThe study provides a broad view of impact studies, which extend beyond financial implications and provides a more inclusive methodology. Particularly, the proposed impact assessment process model seeks to improve the credibility of impact studies by facilitating a holistic approach that incorporates direct, indirect and intangible impacts.Research limitations/implicationsThe proposed model has value to researchers and is designed to improve the overall credibility of economic impact methodology. It also provides a more accurate measure of direct impact while considering intangible and indirect impacts, including social/community impacts.Practical implicationsThe proposed model has value to and practitioners and is designed to improve the overall credibility of economic impact methodology. It also provides a more accurate measure of direct impact while considering intangible and indirect impacts, including social/community impacts.Originality/valueThe proposed process model to measure the impact of a sports event is a needed element in the world of funding, managing and implementing events of all sizes.
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Hänninen, Niko, Aki Pulkkinen, and Tanja Tarvainen. "Image Reconstruction with Reliability Assessment in Quantitative Photoacoustic Tomography." Journal of Imaging 4, no. 12 (December 11, 2018): 148. http://dx.doi.org/10.3390/jimaging4120148.
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Quantitative photoacoustic tomography is a novel imaging method which aims to reconstruct optical parameters of an imaged target based on initial pressure distribution, which can be obtained from ultrasound measurements. In this paper, a method for reconstructing the optical parameters in a Bayesian framework is presented. In addition, evaluating the credibility of the estimates is studied. Furthermore, a Bayesian approximation error method is utilized to compensate the modeling errors caused by coarse discretization of the forward model. The reconstruction method and the reliability of the credibility estimates are investigated with two-dimensional numerical simulations. The results suggest that the Bayesian approach can be used to obtain accurate estimates of the optical parameters and the credibility estimates of these parameters. Furthermore, the Bayesian approximation error method can be used to compensate for the modeling errors caused by a coarse discretization, which can be used to reduce the computational costs of the reconstruction procedure. In addition, taking the modeling errors into account can increase the reliability of the credibility estimates.
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Zhai, Kun, Qiang Ren, Junli Wang, and Chungang Yan. "Byzantine-robust federated learning via credibility assessment on non-IID data." Mathematical Biosciences and Engineering 19, no. 2 (2021): 1659–76. http://dx.doi.org/10.3934/mbe.2022078.
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<abstract> <p>Federated learning is a novel framework that enables resource-constrained edge devices to jointly learn a model, which solves the problem of data protection and data islands. However, standard federated learning is vulnerable to Byzantine attacks, which will cause the global model to be manipulated by the attacker or fail to converge. On non-iid data, the current methods are not effective in defensing against Byzantine attacks. In this paper, we propose a Byzantine-robust framework for federated learning via credibility assessment on non-iid data (BRCA). Credibility assessment is designed to detect Byzantine attacks by combing adaptive anomaly detection model and data verification. Specially, an adaptive mechanism is incorporated into the anomaly detection model for the training and prediction of the model. Simultaneously, a unified update algorithm is given to guarantee that the global model has a consistent direction. On non-iid data, our experiments demonstrate that the BRCA is more robust to Byzantine attacks compared with conventional methods.</p> </abstract>
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Kiili, Carita, Donald J. Leu, Jukka Utriainen, Julie Coiro, Laura Kanniainen, Asko Tolvanen, Kaisa Lohvansuu, and Paavo H. T. Leppänen. "Reading to Learn From Online Information: Modeling the Factor Structure." Journal of Literacy Research 50, no. 3 (July 2, 2018): 304–34. http://dx.doi.org/10.1177/1086296x18784640.
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Identifying the factor structure of online reading to learn is important for the development of theory, assessment, and instruction. Traditional comprehension models have been developed from, and for, offline reading. This study used online reading to determine an optimal factor structure for modeling online research and comprehension among 426 sixth graders (ages 12 and 13). Confirmatory factor analysis was employed to evaluate an assessment of online research and comprehension based on a widely referenced theoretical model. Student performance reflected the theoretical constructs of the model, but several additional constructs appeared, resulting in a six-factor model: (a) locating information with a search engine, (b) questioning credibility of information, (c) confirming credibility of information, (d) identifying main ideas from a single online resource, (e) synthesizing information across multiple online resources, and (f) communicating a justified, source-based position. The findings are discussed in terms of theory, assessment, and instruction.
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Sun, Jiatai, Zengnan Zhao, Minghui Zhang, Ning Wang, and Lihua Wang. "Medical Record Storage Model Based on Credibility Assessment H-Algorand Consensus Mechanism." Journal of Physics: Conference Series 1827, no. 1 (March 1, 2021): 012177. http://dx.doi.org/10.1088/1742-6596/1827/1/012177.
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Li, Yongjie, Hao Tang, Xinju Guo, and Lingyun Li. "Risk Assessment of Microgrid Based on Credibility Entropy Weight Coefficient Evaluation Model." IOP Conference Series: Earth and Environmental Science 300 (August 9, 2019): 042037. http://dx.doi.org/10.1088/1755-1315/300/4/042037.
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Guo, Xingfeng, Yanhui Zhou, Jin Qian, and Yong Deng. "Using Evidence Credibility Decay Model for dependence assessment in human reliability analysis." Annals of Nuclear Energy 100 (February 2017): 107–18. http://dx.doi.org/10.1016/j.anucene.2016.10.007.
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Zhu, Qi. "Node Behavior Trust Evaluation Model Based on Sliding Window." Applied Mechanics and Materials 155-156 (February 2012): 138–42. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.138.
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In order to improve confidence of the node behavior the credibility assessing, this paper presents the nodes behavior of the trust evaluation mechanism based on sliding window, Through the sliding window Assessment strategies to ensure the trust assessment to meet the node behavior assessment principles, Assessment strategies is good combination of confidence assessment method of the subjective and assessment content of the objectivity to ensure contacts number ofa large number of nodes (Nmin) at the same time maintaining good scalability, trust assessment reflects the importance of the recent behavior and the attenuation of long-term behavior, with a "slow rise" and "fast drop" feature, the algorithm with good against fraud and punishment of malicious nodes .
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Idris, N. H., M. J. Jackson, and M. H. I. Ishak. "A conceptual model of the automated credibility assessment of the volunteered geographic information." IOP Conference Series: Earth and Environmental Science 18 (February 25, 2014): 012070. http://dx.doi.org/10.1088/1755-1315/18/1/012070.
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Kleinberg, Bennett, Yaloe van der Toolen, Aldert Vrij, Arnoud Arntz, and Bruno Verschuere. "Automated verbal credibility assessment of intentions: The model statement technique and predictive modeling." Applied Cognitive Psychology 32, no. 3 (April 2, 2018): 354–66. http://dx.doi.org/10.1002/acp.3407.
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Kumar, Prashant, Michael Polonsky, Yogesh K. Dwivedi, and Arpan Kar. "Green information quality and green brand evaluation: the moderating effects of eco-label credibility and consumer knowledge." European Journal of Marketing 55, no. 7 (March 11, 2021): 2037–71. http://dx.doi.org/10.1108/ejm-10-2019-0808.
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Purpose This study aims to examine the effects of three green information quality dimensions – persuasiveness, completeness and credibility – on green brand evaluation and whether this is mediated by green brand credibility. It also examines the moderating effects of eco-label credibility and consumer knowledge on green information quality dimensions and green brand credibility relationships. Design/methodology/approach Using a structured questionnaire on environmentally-friendly electrical goods/electronics, cosmetic and apparel product advertisements, involving an elaboration task, this study collected usable data from 1,282 Indian consumers across 50 cities. It also undertook an assessment for three different product groups using structural equation modelling to examine proposed hypotheses and assessed moderated mediation using the Hays process model. Findings The study indicates that: green brand credibility mediates the effects of green information quality dimensions on green brand evaluation; consumer knowledge moderates the effects of persuasiveness and completeness on green brand credibility and eco-label credibility moderates the effects of persuasiveness and credibility on green brand credibility. Research limitations/implications In green information processing, this study supports the relevance of the elaboration likelihood model and the mediation effect of green brand credibility. It also presents evidence that credible eco-labels enhance green information processing. While the results are broadly consistent across the three product categories, the results may only generalizable to the environmentally-aware urban populations. Practical implications Help brand managers to design advertisements that add brand credibility in environmentally-aware urban markets. Originality/value It helps to define green information quality and the interacting effects of eco-label credibility and consumer knowledge in green information processing.
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Shaklee, Beverly D., and Karen J. Viechnicki. "A Qualitative Approach to Portfolios: The Early Assessment for Exceptional Potential Model." Journal for the Education of the Gifted 18, no. 2 (April 1995): 156–70. http://dx.doi.org/10.1177/016235329501800204.
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The purpose of this article is to examine the creation of a portfolio assessment model based on qualitative research principles. Four assumptions provide the scaffolding for working with portfolios in the classroom: designing authentic learning opportunities; interaction of assessment, curriculum, and instruction; multiple criteria derived from multiple sources; and systematic teacher preparation. In addition, we examine the qualitative research procedures which were embedded in the development of the Early Assessment for Exceptional Potential (EAEP) model and provide support for meeting the standards of credibility, transferability, dependability, and confirmability of the research design (Guba & Lincoln, 1981).
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Calabrese, Edward J. "The Maturing of Hormesis as a Credible Dose-Response Model." Nonlinearity in Biology, Toxicology, Medicine 1, no. 3 (July 1, 2003): 154014203902499. http://dx.doi.org/10.1080/15401420390249907.
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Hormesis is a dose-response phenomenon that has received little recognition, credibility and acceptance as evidenced by its absence from major toxicological/risk assessment texts, governmental regulatory dose-response modeling for risk assessment, and non-visibility in major professional toxicological society national meetings. This paper traces the historical evolution of the hormetic dose-response hypothesis, why this model is not only credible but also more common than the widely accepted threshold model in direct comparative evaluation, and how the toxicological community made a critical error in rejecting hormesis, a rejection sustained over 70 years.
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Wolny-Dominiak, Alicja, and Tomasz Żądło. "The Measures of Accuracy of Claim Frequency Credibility Predictor." Sustainability 13, no. 21 (October 29, 2021): 11959. http://dx.doi.org/10.3390/su132111959.
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Nowadays, the sustainability risks and opportunities start to affect strongly insurance companies in regard to the resulting additional variability of future values of variables taken into account in the decision processes. This is important especially in the era of sustainable non-life insurance promoting, among others, the use of ecological car engines or ecological systems of building heating. The fundamental issue in non-life insurance is to predict future claims (e.g., the aggregate value of claims or the number of claims for a single policy) in a heterogeneous portfolio of policies taking account of claim experience. For this purpose, the so-called credibility theory is used, which was initiated by the fundamental Bühlmann model modified to the Bühlmann–Straub model. Several modifications of the model have been proposed in the literature. One of them is the development of the relationship between the credibility models and statistical mixed models (e.g., linear mixed models) for longitudinal data. The article proposes the use of the parametric bootstrap algorithm to estimate measures of accuracy of the credibility predictor of the number of claims for a single policy taking into account new risk factors resulting from the emergence of green technologies on the considered market. The predictor is obtained for the model which belongs to the class of Generalised Linear Mixed Models (GLMMs) and which is a generalization of the Bülmann–Straub model. Additionally, the possibility of predicting the number of claims and the problem of the assessment of the prediction accuracy are presented based on a policy characterized by new green risk factor (hybrid motorcycle engine) not previously present in the portfolio. The paper presents the proposed methodology in a case study using real insurance data from the Polish market.
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Vander Kolk, Charles J. "Client Self-Report: Assessment of Accuracy." Journal of Applied Rehabilitation Counseling 24, no. 3 (September 1, 1993): 22–25. http://dx.doi.org/10.1891/0047-2220.24.3.22.
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Rehabilitation professionals frequently must evaluate the accuracy and truthfulness of a client's self-report. Inaccurate self-report may cause problems with rehabilitation planning and provision of appropriate services. A conceptual and practical approach to assessment of exaggeration. malingering, and conversion disorder is presented. Included are the stages of evaluation, summary of a model to assess client credibility, and methods for determination of malingering and conversion disorder. Suggestions are offered for counseling the client whose self-report is not accurate.
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Willems, P. "Random number generator or sewer water quality model?" Water Science and Technology 54, no. 6-7 (September 1, 2006): 387–94. http://dx.doi.org/10.2166/wst.2006.581.
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Integrated urban drainage modelling and environmental impact assessment require sewer emission models to be linked with submodels for treatment infrastructure and receiving rivers. The uncertainty in current water quality modelling is, however, huge, and environmental impact assessment looses more and more credibility. Based on an integrated modelling case for a combined sewer – WWTP – river system, it is shown in the paper that the integrated model does not produce more accurate results in comparison with the random simulation of emission concentrations from a frequency distribution. This should, however, not pose a serious problem as in most applications of impact assessment, model results are not needed in real time but in statistical terms. Further investigation makes clear that detail/sophistication in water quality modelling is not so important, but that more focus has to be given to long-term simulations, the use of parsimonious models and model validation based on concentration frequencies.
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Liu, Xu Na, Ying Wang, and Xian Yong Xiao. "Credibility Measure and Assessment Method of Equipment Severity to Voltage Sag." Advanced Materials Research 605-607 (December 2012): 788–92. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.788.
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In order to accurately describe the equipment’ severity caused by voltage sag, the credibility measure which meets the conditions of non-additive is proposed based on their physical properties of responses. This assessment measure can avoid the deficiencies that classical probability measure needs a large number of samples and the non-duality of fuzzy measure. The membership functions of sensitive equipment voltage tolerance capability that corresponding to the characteristic quantities in the status uncertain area was determined by fuzzy statistical method and polynomial fitting method. Then the joint credibility distribution function was deduced based on uncertainty theory. Hence, the assessment model of severity of equipment failure is constructed. Based on practical samples, the PCs were simulated using the proposed method. Comparing the simulation results with methods using classical probability measure and possibility measure prove that the proposed method is proper and credible and can reflect practical condition more objectively.
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Campbell, Malcolm. "An Integrated System for Estimating the Risk Premium of Individual Car Models in Motor Insurance." ASTIN Bulletin 16, no. 2 (November 1986): 165–83. http://dx.doi.org/10.2143/ast.16.2.2015006.
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AbstractThe estimation of risk premium for individual car models is discussed. Cluster analysis is used to identify groups of car models with similar technical attributes. Credibility theory is used to combine estimates of risk premium from individual car model claim statistics, group claim statistics, and a technical assessment carried out by car experts. The procedure is applied to a small set of car models.
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Rotboim, Aviad, Arnon Hershkovitz, and Eddie Laventman. "Positive vs. Negative Framing of Scientific Information on Facebook Using Peripheral Cues: An Eye-Tracking Study of the Credibility Assessment Process." Interdisciplinary Journal of e-Skills and Lifelong Learning 15 (2019): 081–103. http://dx.doi.org/10.28945/4369.
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Aim/Purpose: To examine how positive/negative message framing – based on peripheral cues (regarding popularity, source, visuals, and hyperlink) – affects perceptions of credibility of scientific information posted on social networking sites (in this case, Facebook), while exploring the mechanisms of viewing the different components. Background: Credibility assessment of information is a key skill in today's information society. However, it is a demanding cognitive task, which is impossible to perform for every piece of online information. Additionally, message framing — that is, the context and approach used to construct information— may impact perceptions of credibility. In practice, people rely on various cues and cognitive heuristics to determine whether they think a piece of content is true or not. In social networking sites, content is usually enriched by additional information (e.g., popularity), which may impact the users' perceived credibility of the content. Methodology: A quantitative controlled experiment was designed (N=19 undergraduate students), collecting fine grained data with an eye tracking camera, while analyzing it using transition graphs. Contribution: The findings on the mechanisms of that process, enabled by the use of eye tracking data, point to the different roles of specific peripheral cues, when the message is overall peripherally positive or negative. It also contributes to the theoretical literature on framing effects in science communication, as it highlights the peripheral cues that make a strong frame. Findings: The positively framed status was perceived, as expected from the Elaboration Likelihood Model, more credible than the negatively framed status, demonstrating the effects of the visual framing. Differences in participants' mechanisms of assessing credibility between the two scenarios were evident in the specific ways the participants examined the various status components. Recommendations for Practitioners: As part of digital literacy education, major focus should be given to the role of peripheral cues on credibility assessment in social networking sites. Educators should emphasize the mechanisms by which these cues interact with message framing, so Internet users would be encouraged to reflect upon their own credibility assessment skills, and eventually improve them. Recommendation for Researchers: The use of eye tracking data may help in collecting and analyzing fine grained data on credibility assessment processes, and on Internet behavior at large. The data shown here may shed new light on previously studied phenomena, enabling a more nuanced understanding of them. Impact on Society: In an era when Internet users are flooded with information that can be created by virtually anyone, credibility assessment skills have become ever more important, hence the prominence of this skill. Improving citizens' assessment of information credibility — to which we believe this study contributes — results on a greater impact on society. Future Research: The role of peripheral cues and of message framing should be studied in other contexts (not just scientific news) and in other platforms. Additional peripheral cues not tested here should be also taken into consideration (e.g., connections between the information consumer and the information sharer, or the type of the leading image).
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Zheng, Xianglin, and Yong Deng. "Dependence assessment in human reliability analysis based on evidence credibility decay model and IOWA operator." Annals of Nuclear Energy 112 (February 2018): 673–84. http://dx.doi.org/10.1016/j.anucene.2017.10.045.
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Košková, R., and S. Němečková. "Assessment of evapotranspiration simulations in the Malše basin." Soil and Water Research 4, Special Issue 2 (March 19, 2010): S111—S122. http://dx.doi.org/10.17221/479-swr.
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The application of the distributed hydrological model brings the benefits of assessment of the spatially distributed quantities which are hard to measure in the field over a larger area, e.g. evapotranspiration. The Malše River basin has been chosen for the evaluation of evapotranspiration simulation by the distributed hydrological model, SWIM (Soil and Water Integrated Model). The primary interest in this analysis was to assess the ability of the hydrological model to simulate the actual evapotranspiration on larger scales and to evaluate its dependence on the landscape characteristics such as the vegetation cover, soil type, and average precipitation amount during the simulation. Annual actual evapotranspiration in each hydrotope was evaluated in the simulation period of 1985–1998. Because of the lack of the data observed (evapotranspiration), the model was calibrated on the discharge time series. The credibility was quantified using Nash Sutcliffe efficiency which was more than 0.7. The main trends of the simulated actual evapotranspiration were evaluated and assessed as satisfactory. The differences in the soil types did not seem significant for the evapotranspiration variation, the monthly average values among soil types differing by ± 10% except histosol. On the other hand the differences in the land-use categories strongly influenced the amount of evapotranspiration (–30; +50%). It appears that the model SWIM overestimates the actual evapotranspiration in the spring and, on the other hand, underestimates that in the autumn according to the comparison with the only data available in the entire Climate Atlas of the Czech Republic.
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Gao, Dianzhu, Jun Peng, Jieqi Rong, Yingze Yang, Xiaoyong Zhang, Qin Zhao, Weirong Liu, and Zhiwu Huang. "Health Condition Assessment of Braking System Based on Multi-agent Federated Learning." Journal of Physics: Conference Series 2203, no. 1 (February 1, 2022): 012070. http://dx.doi.org/10.1088/1742-6596/2203/1/012070.
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Abstract The brake system has the characteristics of multi-component, multi working conditions and complex degradation process, which brings great challenges to its health condition assessment. As it is difficult for a single brake agent to make a comprehensive and accurate health condition assessment, a health condition assessment model based on multi-agent federated learning is proposed in this paper. The different agents train their brake health data under different working conditions and states, which ensures the accuracy of health condition assessment and the safety of data of each agent. Aiming at the problem that it is difficult to determine the credibility of agent data in the process of federated learning, a credibility of agent data scheme based on evidence theory is proposed, which not only reduces the cost of calculation and communication, but also further improves the accuracy of health condition assessment. Simulation results show that the scheme not only has higher prediction accuracy, but also can ensure the security of agent data compared with the conventional centralized training scheme.
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Brand, Michael, Davood Babazadeh, Sebastian Lehnhoff, and Dominik Engel. "Trust in control: a trust model for power system network assessment." EPJ Web of Conferences 217 (2019): 01008. http://dx.doi.org/10.1051/epjconf/201921701008.
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The question of whether a process variable transmitted from a device in the field to a power system control center is trustworthy is of high importance nowadays. Traditional bad data detection schemes have their limits in cases of elaborated cyberattacks and cascading failures in a system of systems such as a digitalized power system. This paper proposes a trust model designed for power system network assessment (PSNA). Different to other domains, where trust models already exist (e.g., OC-Trust for organic computing systems), the environment for PSNA is more centralized, and the focus lies on other facets than in organic computing due to the nature of the environment. Therefore, OC-Trust is tailored by categorizing its facets regarding their relevance for PSNA on the one hand. On the other hand, the trust model is extended to realize context-sensitive intersections of trust values. Furthermore, an example of an instantiation of the resulting PSNA-Trust model is given. Two security metrics and one credibility metric based on literature are presented as well as an equation for a context-sensitive intersection.
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Hassan, Shahizan, Norshuhada Shiratuddin, Nor Laily Hashim, and Feng Li. "Evaluating Social Media." International Journal of Interactive Communication Systems and Technologies 4, no. 2 (July 2014): 33–49. http://dx.doi.org/10.4018/ijicst.2014070103.
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Despite the widespread adoption and popularity of social media, research on measuring the quantifiable impact of popular social media platforms remains scarce. To this end, this study attempts to investigate how the influence of social media can be assessed in quantitative terms. The main objective is to develop a new assessment model able to integrate a broad range of criteria such as likes, subscribers, comments, posts, shares, and links. The authors extend previous assessment models focused on individual platforms such as blogs and propose a Social Media Influence Assessment model (SMIA). The process of model development—criteria, dimensions, and formula—and its validation are discussed. The results indicate that social media's influence can be measured in a structured, quantifiable manner by utilising a set of nine criteria grouped into three dimensions: recognition, activity generation, and credibility.
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Wang, Gaocai, and Ning Yu. "Risk Situation Assessment Model Based on Interdomain Interaction in Cloud Computing Environment." Security and Communication Networks 2020 (August 25, 2020): 1–12. http://dx.doi.org/10.1155/2020/7816925.
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With the widespread application of cloud computing sharing technology, the demand for cross-domain interaction is also increasing. However, due to the uncertainty of interaction behaviour and the difference of network service quality, the risk of cross-domain interaction cannot be accurately evaluated. Therefore, this paper proposes a risk situation evaluation model based on interdomain interactions. The model collects interactive credentials such as the frequency, credibility, and time-effectiveness of the user-submitted evaluations. At the same time, it collects the evaluation of quality of service provided by the network security domain. Then, we set up a risk evaluation equation based on the interaction credentials to implement the risk evaluation of cross-domain interaction behaviour. Finally, we apply MATLAB platform to simulate the evolution process of evaluation. The experimental results show that, compared with other models, the evaluation method proposed in this paper improves the accuracy of the evaluation results and meets the security requirements of multidomain interaction.
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Krysanova, Valentina, Jamal Zaherpour, Iulii Didovets, Simon N. Gosling, Dieter Gerten, Naota Hanasaki, Hannes Müller Schmied, et al. "How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change." Climatic Change 163, no. 3 (October 12, 2020): 1353–77. http://dx.doi.org/10.1007/s10584-020-02840-0.
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AbstractImportance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections.
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Brodziak, Jon, and Kevin Piner. "Model averaging and probable status of North Pacific striped marlin, Tetrapturus audax." Canadian Journal of Fisheries and Aquatic Sciences 67, no. 5 (May 2010): 793–805. http://dx.doi.org/10.1139/f10-029.
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We show how model averaging can be applied to estimate the probable status of a fishery resource under assessment scenario uncertainty. This approach is applied to North Pacific striped marlin ( Tetrapturus audax ), an apex predator that may be vulnerable to recruitment overfishing in pelagic longline fisheries targeting tunas. In the current striped marlin assessment, two assessment scenarios were used to account for different hypotheses about the steepness of the stock–recruitment dynamics. Estimates of spawning stock and recruitment from these scenarios are used post hoc to fit age-structured production models that represent alternative hypotheses about the degree of compensation in stock–recruitment dynamics and the degree of serial correlation of environmental forcing. Model-averaged estimates of target spawning biomass to produce maximum sustainable yield (SMSY) and the associated limit fishing mortality (FMSY) characterize relative stock status (S/SMSY and F/FMSY) under each scenario. Scenario-weighted averages of relative status determine probable stock status, with weightings reflecting the credibility of each scenario. Estimates of the variance of probable status account for both model selection and assessment scenario uncertainty in risk analyses. Using model averaging to estimate probable stock status from multiple assessment scenarios is analogous to using ensemble averages from multiple predictive models to make weather forecasts.
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Coburn, Jacob, and S. C. Pryor. "Differential Credibility of Climate Modes in CMIP6." Journal of Climate 34, no. 20 (October 2021): 8145–64. http://dx.doi.org/10.1175/jcli-d-21-0359.1.
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AbstractThis work quantitatively evaluates the fidelity with which the northern annular mode (NAM), southern annular mode (SAM), Pacific–North American pattern (PNA), El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Atlantic multidecadal oscillation (AMO), and the first-order mode interactions are represented in Earth system model (ESM) output from the CMIP6 archive. Several skill metrics are used as part of a differential credibility assessment (DCA) of both spatial and temporal characteristics of the modes across ESMs, ESM families, and specific ESM realizations relative to ERA5. The spatial patterns and probability distributions are generally well represented but skill scores that measure the degree to which the frequencies of maximum variance are captured are consistently lower for most ESMs and climate modes. Substantial variability in skill scores manifests across realizations from individual ESMs for the PNA and oceanic modes. Further, the ESMs consistently overestimate the strength of the NAM–PNA first-order interaction and underestimate the NAM–AMO connection. These results suggest that the choice of ESM and ESM realizations will continue to play a critical role in determining climate projections at the global and regional scale at least in the near term.
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Alzaid, Jawaher Mohammed. "The Effect of Peer Assessment on the Evaluation Process of Students." International Education Studies 10, no. 6 (May 30, 2017): 159. http://dx.doi.org/10.5539/ies.v10n6p159.
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This study aims at finding out the effect of peer assessment on the evaluation process of students. The hypothesis underlying this study is that assessment is an integral part of the learning process, which should play an important role in the educational model. The current study will emphasize the importance of using peer assessment as a tool to engage students in the evaluation process, clarify the role of peer assessment in promoting student learning, diversify the scope of the evaluation through the frameworks of theory and methodology to get to understand the uses and limitations of peer assessment as a tool for assessment, and discuss the goals and benefits that can be achieved by the students from practicing peer assessment in accordance with scientific standards and bases, which emphasize active participation of the students in their learning and responsibility. Additionally, this study will check the credibility of peer assessments as a suitable tool in the assessment process. Findings show that there is a statistically significant relationship between the assessment of peers to each other, as well as between peer assessment and teacher assessment.
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Wei, Dengfeng, and Qing-Ju Jiao. "A Novel Core-Peer Based Trust Model for Peer-to-Peer Networks." Journal of Computational and Theoretical Nanoscience 14, no. 1 (January 1, 2017): 114–18. http://dx.doi.org/10.1166/jctn.2017.6135.
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In this paper, the P2P network node trust relationships and transactions are less likely to feature on the P2P network trust model based on the core nodes. Network nodes in the network model to the public reputation and private credibility clustering rely on node reliability for core nodes and node points to discuss and give relevant solutions. Simulation results show that the trust model not only has a robust anti-malicious node attack has a lower assessment of the amount of computation and communication overhead, network resources search.
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Wang, Longbao, Yingchi Mao, Yangkun Cheng, and Yi Liu. "Deep Learning-Based Diagnosing Structural Behavior in Dam Safety Monitoring System." Sensors 21, no. 4 (February 7, 2021): 1171. http://dx.doi.org/10.3390/s21041171.
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Collecting a myriad of prototype data through various types of monitoring sensors plays a virtual important role in many aspects of dam safety such as real-time grasp of safety state, exposure of hidden dangers, and inspection design and construction. However, the current methods of prediction are weak in the long-term sequence of nodes with missing and abnormal error value. Moreover, the limitation caused by the apparatus, environmental factors, and network transmission can lead to the deviation and inconsistency of diagnosis and evaluation of local region. In this paper, we consider the correlation of data on nodes in the entire monitoring network. To avoid the deviation caused by noise and missing value in the single-node data sequence, we calculate the correlation between the multiple sequences. A single-node assessment model based on multiple relevant sequence (SAM) is proposed to improve the accuracy of single node assessment. Given the different nodes of a local region have varying impacts on the evaluation results, a local region evaluation algorithm based on node credibility (LREA) is presented to model the credibility of nodes in order to alleviate inconsistent evaluation results in the local region of dam. LREA can assess the dam’s operation state by considering the variations in credibility and multiple nodes coordination. The experimental results illustrate the LREA can reveal the trends of the monitoring values change in a timely and accurate way, which can elevate the accuracy of evaluation results of dam safety.
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Jabbari, Aida, Jae-Min So, and Deg-Hyo Bae. "Precipitation Forecast Contribution Assessment in the Coupled Meteo-Hydrological Models." Atmosphere 11, no. 1 (December 27, 2019): 34. http://dx.doi.org/10.3390/atmos11010034.
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A numerical weather prediction and a rainfall-runoff model employed to evaluate precipitation and flood forecast for the Imjin River (South and North Korea). The real-time precipitation at point and catchment scales evaluated to select proper hydrological model to couple with atmospheric model. As a major limitation of previous studies, temporal and spatial resolutions of hydrological model are smaller than those of meteorological model. Here, through high resolution of temporal (10 min) and spatial (1 km × 1 km), the optimal resolution determined. The results showed Weather Research and Forecasting (WRF) model underestimated precipitation in point and catchment assessment and its skill was relatively higher for catchment than point scale, as illustrated by the lower Root Mean Square Error (RMSE) of 59.67, 160.48, 68.49 for the catchment and 84.49, 212.80 and 91.53 for the point scale in the events 2002, 2007 and 2011, respectively. The findings led to choose the semi-distributed hydrological model. The variations in temporal and spatial resolutions illustrated accuracy decrease; additionally, the optimal spatial resolution obtained at 8 km and temporal resolution did not affect the inherent inaccuracy of the results. Lead-time variation demonstrated that lead-time dependency was almost negligible below 36 h. With reference to this study, comparisons of model performance provided quantitative knowledge for understanding credibility and restrictions of meteo-hydrological models.
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Trostianska, Karyna, and Ilona Semencha. "Reputational risk management in conditions of credibility gap in the banking system." Journal of Financial Economic Policy 12, no. 3 (September 12, 2019): 327–43. http://dx.doi.org/10.1108/jfep-03-2019-0063.
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Purpose This paper aims to provide appropriate and effective methods for diagnosing and managing the reputational risk of a bank. Design/methodology/approach Using the data-mining system CONFOR, the authors have defined and arranged in the objective way the factors influencing the reputational risk level of a bank, with specific factor groups assigned. The mathematical tools of the theory of graphs and cognitive mapping are used for building the cognitive map of reputational risk assessment of a bank. To enable choosing which risk management strategies to use, the methods of impulse modeling and scenario analysis are applied for the purpose of prognostication. Findings The authors proposed an integrated approach to the objective determination of the reputational risk level and an easy-to-use choice of risk management scenarios considering all components of management decision making and the main managerial functions. Practical implications The range of tools proposed can be used as a simple measure of the bank's reputational risk level, as a component of risk management model, and as a strategic risk management tool. Implementing this approach at the level of the central bank will facilitate realization of its strategic program for restoring confidence in the banking system as a whole. Originality/value A relatively greater objectivity in the reputational risk assessment of the bank was achieved, with each stage formalized and confirmed by an economic and mathematical basis, risk parameters quantified. The authors have developed a comprehensive approach to the reputational risk level assessment (the integral assessment included) as well as the management algorithm.
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de Lima Silva, Diogo F., Julio Cezar Soares Silva, Lucimário G. O. Silva, Luciano Ferreira, and Adiel T. de Almeida-Filho. "Sovereign Credit Risk Assessment with Multiple Criteria Using an Outranking Method." Mathematical Problems in Engineering 2018 (September 23, 2018): 1–11. http://dx.doi.org/10.1155/2018/8564764.
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In view of the records of failures in rating agencies’ assessments for sorting countries’ quality of credit in degrees of default risk, this paper proposes a multicriteria sorting model using reference alternatives so as to allocate sovereign credit securities into three categories of risk. From a numerical application, what was observed from the results was a strong adherence of the model in relation to those of the agencies: Standard & Poor's and Moody's. Since the procedure used by the agencies is extremely subjective and often questioned, the contribution of this paper is to put forward the use of an objective and transparent methodology to sort these securities. Given the agencies’ conditions for undertaking the assessment, a complete similarity between the results obtained and the assignments of the agencies was not expected. Therefore, this difference arises from subjective factors that the agencies consider but the proposed model does not. Such subjective and questionable aspects have been partly responsible for the credibility of these credit agencies being diminished, especially after the 2007-2008 crisis.
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Garavelli, Chiara, Cristina Curreli, Marco Palanca, Alessandra Aldieri, Luca Cristofolini, and Marco Viceconti. "Experimental validation of a subject-specific finite element model of lumbar spine segment using digital image correlation." PLOS ONE 17, no. 9 (September 9, 2022): e0272529. http://dx.doi.org/10.1371/journal.pone.0272529.
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Pathologies such as cancer metastasis and osteoporosis strongly affect the mechanical properties of the vertebral bone and increase the risk of fragility fractures. The prediction of the fracture risk with a patient-specific model, directly generated from the diagnostic images of the patient, could help the clinician in the choice of the correct therapy to follow. But before such models can be used to support any clinical decision, their credibility must be demonstrated through verification, validation, and uncertainty quantification. In this study we describe a procedure for the generation of such patient-specific finite element models and present a first validation of the kinematics of the spine segment. Quantitative computed tomography images of a cadaveric lumbar spine segment presenting vertebral metastatic lesions were used to generate the model. The applied boundary conditions replicated a specific experimental test where the spine segment was loaded in compression-flexion. Model predictions in terms of vertebral surface displacements were compared against the full-field experimental displacements measured with Digital Image Correlation. A good agreement was obtained from the local comparison between experimental data and simulation results (R2 > 0.9 and RMSE% <8%). In conclusion, this work demonstrates the possibility to apply the developed modelling pipeline to predict the displacement field of human spine segment under physiological loading conditions, which is a first fundamental step in the credibility assessment of these clinical decision-support technology.
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Pitera, Rafał, Justyna Chmiel, and Karolina Kozioł. "Credibility of Discriminatory Models on the Example of Enterprises from the Lubelskie and Podkarpackie Voivodeships." Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia 54, no. 3 (December 1, 2020): 91. http://dx.doi.org/10.17951/h.2020.54.3.91-99.
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<p>Theoretical background: The results of the conducted research allowed the classification of early-warning models according to the accuracy of the forecasts received for the last year of the study.</p><p>Purpose of the article: The aim of the article was verification and prognostic assessment of discriminative models popular among researchers, answer to the question whether the model properly reflects the financial situation of the company.</p><p>Research methods: The basis of all the methods used in this article was the analysis of existing data and methods of discriminant analysis.</p><p>Main findings: The selected models properly reflected the financial situation of the 84 enterprises surveyed.</p>
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Walton, Douglas N. "Ethotic arguments and fallacies: The credibility function in multi-agent dialogue systems." Pragmatics and Cognition 7, no. 1 (1999): 177–203. http://dx.doi.org/10.1075/pc.7.1.08wal.
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In this paper, it is shown how formal dialectic can be extended to model multi-agent argumentation in which each participant is an agent. An agent is viewed as a participant in a dialogue who not only has goals, and the capability for actions, but who also has stable characteristics of types that can be relevant to an assessment of some of her arguments used in that dialogue. When agents engage in argumentation in dialogues, each agent has a credibility function that can be adjusted upwards or downwards by certain types of arguments brought forward by the other agent in the dialogue. One type is the argument against the person or argumentum ad hominem, in which personal attack on one party's character is used to attack his argument. Another is the appeal to expert opinion, traditionally associated with the informal fallacy called the argumentum ad verecundiam. In any particular case, an agent will begin a dialogue with a given degree of credibility, and what is here called the credibility function will affect the plausibility of the arguments put forward by that agent. In this paper, an agent is shown to have specific character traits that are vital to properly judging how this credibility function should affect the plausibility of her arguments, including veracity, prudence, sincerity and openness to opposed arguments. When one of these traits is a relevant basis for an adjustment in a credibility function, there is a shift to a subdialogue in which the argumentation in the case is re-evaluated. In such a case, it is shown how the outcome can legitimately be a reduction in the credibility rating of the arguer who was attacked. Then it is shown how the credibility function should be brought into an argument evaluation in the case, yielding the outcome that the argument is assigned a lower plausibility value.
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Bukovsky, Melissa S., David J. Gochis, and Linda O. Mearns. "Towards Assessing NARCCAP Regional Climate Model Credibility for the North American Monsoon: Current Climate Simulations*." Journal of Climate 26, no. 22 (October 29, 2013): 8802–26. http://dx.doi.org/10.1175/jcli-d-12-00538.1.
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Abstract The authors examine 17 dynamically downscaled simulations produced as part of the North American Regional Climate Change Assessment Program (NARCCAP) for their skill in reproducing the North American monsoon system. The focus is on precipitation and the drivers behind the precipitation biases seen in the simulations of the current climate. Thus, a process-based approach to the question of model fidelity is taken in order to help assess confidence in this suite of simulations. The results show that the regional climate models (RCMs) forced with a reanalysis product and atmosphere-only global climate model (AGCM) time-slice simulations perform reasonably well over the core Mexican and southwest United States regions. Some of the dynamically downscaled simulations do, however, have strong dry biases in Arizona that are related to their inability to develop credible monsoon flow structure over the Gulf of California. When forced with different atmosphere–ocean coupled global climate models (AOGCMs) for the current period, the skill of the RCMs subdivides largely by the skill of the forcing or “parent” AOGCM. How the inherited biases affect the RCM simulations is investigated. While it is clear that the AOGCMs have a large influence on the RCMs, the authors also demonstrate where the regional models add value to the simulations and discuss the differential credibility of the six RCMs (17 total simulations), two AGCM time slices, and four AOGCMs examined herein. It is found that in-depth analysis of parent GCM and RCM scenarios can identify a meaningful subset of models that can produce credible simulations of the North American monsoon precipitation.
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Jaam, Myriam, Zachariah Nazar, Daniel C. Rainkie, Diana Alsayed Hassan, Farhat Naz Hussain, Salah Eldin Kassab, and Abdelali Agouni. "Using Assessment Design Decision Framework in understanding the impact of rapid transition to remote education on student assessment in health-related colleges: A qualitative study." PLOS ONE 16, no. 7 (July 9, 2021): e0254444. http://dx.doi.org/10.1371/journal.pone.0254444.
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Maintaining integrity and validity with online assessment is a significant issue that is well documented. Overt policies encouraging educators to adopt e-Learning and implement digital services coupled with the dramatic change in the education system in response to the challenges posed by COVID-19, has furthered the demand for evidence-based approaches for the planning and delivery of assessments. This study employed the Assessment Design Decision Framework (ADDF), a theoretical model that considers key aspects of assessment design, to retrospectively investigate from a multi-stakeholder perspective the assessments implemented following the rapid transition to remote learning during the COVID-19 pandemic. One-to-one semi-structured interviews were conducted with faculty and students from the Colleges of Pharmacy, Medicine and Health Sciences. After inductive and deductive thematic analysis three major themes were identified. These reflected on the impact of sudden transition on assessment design and assessment plan; changing assessment environment; and faculty-student assessment related interactions which included feedback. The use of a comprehensive validated framework such as ADDF, to plan assessments can improve validity and credibility of assessments. The strengths of this study lie in the innovative adoption of the ADDF to evaluate assessment design decisions from both an educator and student perspective. Further, the data yielded from this study offers novel validation of the use of ADDF in circumstances necessitating rapid transition, and additionally identifies a need for greater emphasis to be attributed to the significance of timeliness of the various activities that are advocated within the framework.
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Krysanova, Valentina, Fred F. Hattermann, and Zbigniew W. Kundzewicz. "How evaluation of hydrological models influences results of climate impact assessment—an editorial." Climatic Change 163, no. 3 (December 2020): 1121–41. http://dx.doi.org/10.1007/s10584-020-02927-8.
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AbstractThis paper introduces the Special Issue (SI) “How evaluation of hydrological models influences results of climate impact assessment.” The main objectives were as follows: (a) to test a comprehensive model calibration/validation procedure, consisting of five steps, for regional-scale hydrological models; (b) to evaluate performance of global-scale hydrological models; and (c) to reveal whether the calibration/validation methods and the model evaluation results influence climate impacts in terms of the magnitude of the change signal and the uncertainty range. Here, we shortly describe the river basins and large regions used as case studies; the hydrological models, data, and climate scenarios used in the studies; and the applied approaches for model evaluation and for analysis of projections for the future. After that, we summarize the main findings. The following general conclusions could be drawn. After successful comprehensive calibration and validation, the regional-scale models are more robust and their projections for the future differ from those of the model versions after the conventional calibration and validation. Therefore, climate impacts based on the former models are more trustworthy than those simulated by the latter models. Regarding the global-scale models, using only models with satisfactory or good performance on historical data and weighting them based on model evaluation results is a more reliable approach for impact assessment compared to the ensemble mean approach that is commonly used. The former method provides impact results with higher credibility and reduced spreads in comparison to the latter approach. The studies for this SI were performed in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).