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Letteratura scientifica selezionata sul tema "Inaccurate"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 3 febbraio 2022

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Articoli di riviste sul tema "Inaccurate"

Matter, E. Ann, Sarah Jane Boss e Ruth Harris. "Inaccurate Deception?" Women's Review of Books 18, n. 1 (ottobre 2000): 17. http://dx.doi.org/10.2307/4023518.

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Bunyan, R. "Factually inaccurate". British Dental Journal 208, n. 8 (aprile 2010): 329–30. http://dx.doi.org/10.1038/sj.bdj.2010.353.

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Welch, Richard. "Inaccurate advertising". Journal of Wound, Ostomy and Continence Nursing 19, n. 2 (marzo 1992): 55A. http://dx.doi.org/10.1097/00152192-199203000-00035.

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Carrubba, Catherine. "Inaccurate conclusion?" Air Medical Journal 13, n. 2 (febbraio 1994): 58–70. http://dx.doi.org/10.1016/s1067-991x(05)80277-9.

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Skynner, A. C. Robin. "Inaccurate quotation". Bulletin of the Royal College of Psychiatrists 10, n. 12 (dicembre 1986): 362. http://dx.doi.org/10.1192/pb.10.12.362.

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Schiebinger, Londa, e Marie-Helene Huet. "Inaccurate Conceptions". Women's Review of Books 10, n. 9 (giugno 1993): 17. http://dx.doi.org/10.2307/4021578.

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Stein, Leonard I. "Inaccurate Comparison". Psychiatric Services 48, n. 4 (aprile 1997): 544. http://dx.doi.org/10.1176/ps.48.4.544.

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Firmstone, V. R. "Inaccurate reporting". British Dental Journal 205, n. 5 (settembre 2008): 223–24. http://dx.doi.org/10.1038/sj.bdj.2008.746.

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Kubáček, Lubomír. "Linear model with inaccurate variance components". Applications of Mathematics 41, n. 6 (1996): 433–45. http://dx.doi.org/10.21136/am.1996.134336.

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Dunning, Marshall B. "Inaccurate Spirometry Results?" Chest 127, n. 1 (gennaio 2005): 409–10. http://dx.doi.org/10.1378/chest.127.1.409.

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Tesi sul tema "Inaccurate"

McQuerry, Kristen J. "Statistical Methods for Handling Intentional Inaccurate Responders". UKnowledge, 2016. http://uknowledge.uky.edu/statistics_etds/17.

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In self-report data, participants who provide incorrect responses are known as intentional inaccurate responders. This dissertation provides statistical analyses for address intentional inaccurate responses in the data. Previous work with adolescent self-report, labeled survey participants who intentionally provide inaccurate answers as mischievous responders. This phenomenon also occurs in clinical research. For example, pregnant women who smoke may report that they are nonsmokers. Our advantage is that we do not solely have self-report answers and can verify responses with lab values. Currently, there is no clear method for handling these intentional inaccurate respondents when it comes to making statistical inferences. We propose a using an EM algorithm to account for the intentional behavior while maintaining all responses in the data. The performance of this model is evaluated using simulated data and real data. The strengths and weaknesses of the EM algorithm approach will be demonstrated.

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Basinger, Karen Lynn. "Impact of inaccurate data on supply chain inventory performance". Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1164727086.

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Sorhagen, Nicole. "Teacher and Mother Inaccurate Beliefs: Exploring Differential Effects on Child Achievement". Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/286138.

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Psychology
Ph.D.
Conceptual development and achievement are embedded in social relationships. Research on self-fulfilling prophecies in the classroom has shown teachers' inaccurate perceptions about a child's ability shape schoolchildren's intellectual development in the direction of the misperception (Jussim & Harber, 2005; Rosenthal & Jacobson, 1968; Sorhagen, 2013). This contrasts with prior research on the influences of parents' misperceptions, which has shown that parents with accurate perceptions of their child's abilities, compared to those with misperceptions, have children with advanced conceptual development and higher achievement (Hunt & Paraskevopoulos, 1980; S. A. Miller, Manhal, & Mee, 1991; Sorhagen, 2014a, 2014b). Taken together, the literature on adult misperceptions of child abilities paints discrepant pictures of how adults' inaccurate beliefs may influence children's achievement trajectories. There is evidence for conditional direct and indirect effects of misperceptions within both literatures. Perhaps if moderating conditions were the same at school and at home, the effects of teacher and parent misperceptions would be the same. The present dissertation used prospective data to address the conflicting evidence on the effects of teachers' and mothers' misperceptions of abilities, focusing on differences in the magnitude and direction of adult misperceptions by the levels of environmental control (i.e. rigidly structured and intrusive versus autonomy-supporting). The results confirmed and extended the prior literature by showing that children's reading and math achievement in high school were differentially affected by the accuracy of adults' perceptions of the children's abilities depending on whether the adult is a teacher or mother. Children's high school performance benefited most when their teachers overestimated their abilities and when their mothers' accurately estimated their abilities in in third-grade. Furthermore, there was evidence for mediation through adults' differential treatment in the reading models. Evidence for moderation was also seen in the reading models, but only for the influence of teachers' misperceptions on teacher attention, which indirectly led to differences in child achievement (i.e. conditional indirect effects). The effects of teachers' misperceptions were more profound at low levels of environmental control compared to highly controlled classrooms. Thus environmental control did not lead to similar influences of teacher and mother misperceptions. This supports the notion that there are different consequences of teacher and mother misperceptions on child achievement. The results of additional analyses found child characteristics (i.e. child birth order, gender, ethnicity, family SES, child social competencies, and prior abilities), as well as teacher's self-efficacy predicted the degree of accuracy of the adults' perceptions of children's reading and math abilities. Furthermore, the results showed that teachers' and mothers' perceptions were often accurate, but when one adult was inaccurate, it was likely that the other adult's perception was similar. As we become increasingly aware of the importance of social influences on cognition, the results of the present dissertation suggest that it is important to consider differences between socializing agents.
Temple University--Theses

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Burch, Gerald F. "The cost of maintaining a Naval inventory system with inaccurate records". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Mar%5FBurch.pdf.

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Thesis (M.S. in Operations Research)--Naval Postgraduate School, March 2003.
Thesis advisor(s): Robert A. Koyak, Samuel L. Buttrey. Includes bibliographical references (p. 67-68). Also available online.

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Mendoza, Juan Pablo. "Regions of Inaccurate Modeling for Robot Anomaly Detection and Model Correction". Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1059.

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To make intelligent decisions, robots often use models of the stochastic effects of their actions on the world. Unfortunately, in complex environments, it is often infeasible to create models that are accurate in every plausible situation, which can lead to suboptimal performance. This thesis enables robots to reason about model inaccuracies to improve their performance. The thesis focuses on model inaccuracies that are subtle –i.e., they cannot be detected from a single observation– and context-dependent –i.e., they affect particular regions of the robot’s state-action space. Furthermore, this work enables robots to react to model inaccuracies from sparse execution data. Our approach consists of enabling robots to explicitly reason about parametric Regions of Inaccurate Modeling (RIMs) in their state-action space. We enable robots to detect these RIMs from sparse execution data, to correct their models given these detections, and to plan accounting for uncertainty with respect to these RIMs. To detect and correct RIMs, we first develop algorithms that work effectively online in low-dimensional domains. An execution monitor compares outcome predictions made by a stochastic nominal model, to outcome observations gathered during execution. The results of these comparisons are then used to detect RIMs of stateaction space in which outcome observations deviate statistically-significantly from the nominal model. Our detection algorithm is based on an explicit search for the parametric region of state-action space that maximizes an anomaly measure; once the maximum anomaly region is found, a statistical test determines whether the outcomes deviate significantly from the model. To correct detected RIMs, our algorithms apply corrections on top of the nominal model, only in the detected RIMs, treating them as newly-discovered behavioral modes of the domain. To extend this approach to high-dimensional domains, we develop a search-based Feature Selection algorithm. Based on the assumption that RIMs are intrinsically low-dimensional, but embedded in a high-dimensional space, this best-first search starts from the zero-dimensional projection of all the execution data, and searches by adding the single most promising feature to the boundary of the search tree. Our lowdimensional algorithms can then be applied to the resulting low-dimensional space to find RIMs in the robot’s planning model. We also enable robots to make plans that account for their uncertainty about the accuracy of their models. To do this, we first enable robots to represent distributions over possible RIMs in their planning models. With this representation, robots can plan accounting for the probability that their models are inaccurate in particular points in state-action state. Using this approach, we enable robots to effectively trade off actions that are known to produce reward with those that refine their models, potentially leading to higher future reward. We evaluate our approach on various complex robot domains. Our approach enables the CoBot mobile service robots to autonomously detect inaccuracies in their motion models, despite their high-dimensional state-action space: the CoBots detect that they are not moving correctly in particular areas of the building, and that their wheels are starting to fail when making turns. Our approach enables the CMDragons soccer robots to improve their passing and shooting models online in the presence of opponents with unknown weaknesses and strengths. Finally, our approach enables a NASA spacecraft landing simulator to detect subtle anomalies, unknown to us beforehand, in their streams of high-dimensional sensor-output and actuator-input data.

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An, Jing. "A fuzzy non-dominance approach for network routing with inaccurate information". Thesis, King's College London (University of London), 2015. http://kclpure.kcl.ac.uk/portal/en/theses/a-fuzzy-nondominance-approach-for-network-routing-with-inaccurate-information(7ad68012-c3d5-4d43-b9ae-e3c879476108).html.

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Routing is one of the most essential functions in computer and telecommunications networks. As the network grows in size, complexity and mobility, it becomes more dicult to precisely determine the routing metrics due to networks' dynamic nature. As a result the information available for decision making of Quality of Service (QoS) routing is always inaccurate. This thesis considers that network routing metrics are naturally uncertain due to the inaccurate information. A novel concept, fuzzy non-dominance multipath routing is developed for the network routing discovery and routing optimisation. The fuzzy non-dominance multipath routing de nes network routing problem in a fuzzy weight graph. The term fuzzy non-dominance routing used in this thesis is distinct from the conventional sense of fuzzy routing. Fuzzy non-dominance routing leads to the fuzzy Pareto-optimal multipath. A labelling setting algorithm is developed to nd out the limited as well as full non-dominated set of routes for network packets forwarding. This approach provides an alternative way to deal with the network routing and multipath routing optimisation problem with less computational and management costs. This thesis proposed a framework for adopting fuzzy non-dominance routing into conventional structure networks. The simulation results covered fuzzy nondominance routing discovery by considering di erent network topologies, scales, fuzzy number designs and the grade of fuzziness. The thesis also addressed fuzzy non-dominance routing for general trac-engineering. Compare to conventional Open Shortest Part First routing, fuzzy non-dominance routing allows the network to cope with at most 60 % more demand. In addition, the thesis also studied the fuzzy non-dominance routing for optimising network routing convergence, quality of service routing and its applications in Mobile ad-hoc networks.

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Wang, Qi. "Performance improvement of quality of service routing under inaccurate link-state information". Thesis, Southampton Solent University, 2004. http://ssudl.solent.ac.uk/602/.

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It has been observed that the current best-effort IP packet delivery service in the global Internet is sometimes not good enough for emerging real-time multimedia applications. These resource intensive applications normally have more stringent requirements on bandwidth, delay, delay jitter etc. The quality of service (QoS) requirements of these applications raise new challenges for the development of new routing mechanisms. QoS routing can provide increased network utilisation compared to best-effort routing by efficiently regulating and managing resource sharing across a network. However, the benefit of QoS routing comes with complex routing computation costs and increased routing protocol overhead. It is impractical to collect detailed global state information and keep it up-to-date in large-scale dynamic networks, such as the Internet. As a result, inaccurate link-state information increases the flow blocking probability and makes source nodes select non-optimal paths. To maximise the link utilisation and meet application QoS requirements, routing algorithms need accurate link-state information to make routing decisions. This thesis investigates the statistical properties of time series of link utilisation. In particular, the evaluation focuses on the presence of autocorrelation in the time series. Further study under various link-state update policies, network and traffic configurations identifies the factors that may affect the statistical properties of the time series. Based on this analysis, a prediction-based link-state update policy is proposed to reduce the effect of inaccurate link-state information. The approach predicts the link-state utilisation trend based on past values. By advertising trend rather than instantaneous link utilisation, the routing algorithms may have more valuable information to make routing decisions instead of being affected by short lived sudden changes. An appropriate model that can satisfactorily fit the actual model is identified, estimated and validated. Finally, the performance of the proposed prediction-based link-state update policy is validated by simulation and compared with conventional update policies under a variety of network configurations. the results show that this approach is effective in improving routing performance.

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Kinsella, Frederick C. "Is stereotyping of patients by registered nurses associated with inaccurate clinical judgments? /". Staten Island, N.Y. : [s.n.], 1987. http://library.wagner.edu/theses/nursing/1987/thesis_nur_1987_kinse_stere.pdf.

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Teacy, W. T. Luke. "Agent-based trust and reputation in the context of inaccurate information sources". Thesis, University of Southampton, 2006. https://eprints.soton.ac.uk/263190/.

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Trust is a prevalent concept in human society that, in essence, concerns our reliance on the actions of other entities within our environment. For example, we may rely on our car starting to get to work on time, and on our fellow drivers, so that we may get there safely. For similar reasons, trust is becoming increasingly important in computing, as systems, such as the Grid, require integration of computing resources, across organisational boundaries. In this context, the reliability of resources in one organisation cannot be assumed from the point of view of another, as certain resources may fail more often than others. For this reason, we argue that software systems must be able to assess the reliability of different resources, so that they may choose which of them to rely on. With this in mind, our goal is to develop mechanisms, or models, to aid decision making by an autonomous agent (the truster), when the consequences of its decisions depend on the actions of other agents (the trustees). To achieve this, we have developed a probabilistic framework for assessing trust based on a trustee's past behaviour, which we have instantiated through the creation of two novel trust models (TRAVOS and TRAVOS-C). These facilitate decision making in two different contexts with regard to trustee behaviour. First, using TRAVOS, a truster can make decisions in contexts where a trustee can only act in one of two ways: either it can cooperate, acting to the truster's advantage; or it can defect, thereby acting against the truster's interests. Second, using TRAVOS-C, a truster can make decisions about trustees that can act in a continuous range of ways, for example, taking into account the delivery time of a service. These models share an ability to account for observations of a trustee's behaviour, made either directly by the truster, or by a third party (reputation source). In the latter case, both models can cope with third party information that is unreliable, either because the sender is lying, or because it has a different world view. In addition, TRAVOS-C can assess a trustee for which there is little or no direct or reported experience, using information about other agents that share characteristics with the trustee. This is achieved using a probabilistic mechanism, which automatically accounts for the amount of correlation observed between agents' behaviour, in a truster's environment.

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Patterson, Robert W. "The effects of inaccurate speech information on performance in a visual search and identification task". Thesis, Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/30481.

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Libri sul tema "Inaccurate"

Mayne, Kenny. An Incomplete & Inaccurate History of Sport. New York: Crown Publishing Group, 2008.

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Attfield, C. L. F. Rationally inaccurate expectations and stabilisation policy. Bristol: University of Bristol, Department of Economics, 1995.

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Schulman, Sarah. Carson McCullers: (historically inaccurate) : a drama. New York (325 W 38th St., Suite 305 New York 10018): Playscripts, 2006.

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Mayne, Kenny. An incomplete and inaccurate history of sport. New York: Crown, 2008.

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Mayne, Kenny. An incomplete and inaccurate history of sport. New York: Crown, 2008.

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Manufacturing numbers: How inaccurate statistics conceal U.S. industrial decline. Washington, DC: Economic Policy Institute, 1988.

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Murray, Stephen. The universe and other stuff: A brief and inaccurate history of everything. Venice, FL: Eldridge Pub. Co., 1997.

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Alexander, J. Trent. Inaccurate age and sex data in the census pums files: Evidence and implications. Cambridge, MA: National Bureau of Economic Research, 2010.

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Office, General Accounting. The Army's safety level requirements for secondary items may be inaccurate and excessive (GAO/NSIAD-85-160). Washington, D.C: U.S. GAO, 1985.

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Audits, California Bureau of State. California's education institutions: A lack of guidance results in their inaccurate or inconsistent reporting of campus crime statistics. Sacramento: California State Auditor, Bureau of State Audits, 2003.

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Capitoli di libri sul tema "Inaccurate"

de Boer, Hester, Anneke C. Timmermans e Margaretha P. C. van der Werf. "Inaccurate Teacher Expectations". In Interpersonal and Intrapersonal Expectancies, 157–61. Abingdon, Oxon; New York, NY: Routledge, 2016.: Routledge, 2016. http://dx.doi.org/10.4324/9781315652535-21.

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Zhou, Zhi-Hua, Yang Yu e Chao Qian. "Inaccurate Fitness Evaluation". In Evolutionary Learning: Advances in Theories and Algorithms, 129–53. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-5956-9_10.

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Næss, Petter. "Inaccurate and biased". In Crisis System, 48–68. New York : Routledge, 2016. | Series: Ontological explorations: Routledge, 2016. http://dx.doi.org/10.4324/9781315563138-4.

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Tsafrir, Dan. "Using Inaccurate Estimates Accurately". In Job Scheduling Strategies for Parallel Processing, 208–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16505-4_12.

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Bailey Lee, Cynthia, Yael Schwartzman, Jennifer Hardy e Allan Snavely. "Are User Runtime Estimates Inherently Inaccurate?" In Job Scheduling Strategies for Parallel Processing, 253–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11407522_14.

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Jamil, Hasan M., e Fereidoon Sadri. "Recognizing credible experts in inaccurate databases". In Lecture Notes in Computer Science, 46–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58495-1_5.

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Forman, George. "Counting Positives Accurately Despite Inaccurate Classification". In Machine Learning: ECML 2005, 564–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11564096_55.

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Baliga, Ganesh, Sanjay Jain e Arun Sharma. "Learning from multiple sources of inaccurate data". In Analogical and Inductive Inference, 108–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-56004-1_8.

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Souissi, Samia, Xavier Défago e Masafumi Yamashita. "Gathering Asynchronous Mobile Robots with Inaccurate Compasses". In Lecture Notes in Computer Science, 333–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11945529_24.

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Shary, Sergey P. "Interval Regularization for Inaccurate Linear Algebraic Equations". In Studies in Computational Intelligence, 375–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-31041-7_21.

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Atti di convegni sul tema "Inaccurate"

Zhang, Tan, e Suman Banerjee. "Inaccurate spectrum databases?" In HotNets-XII: Twelfth ACM Workshop on Hot Topics in Networks. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2535771.2535793.

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Guillame-Bert, M., e J. L. Crowley. "Planning with Inaccurate Temporal Rules". In 2012 IEEE 24th International Conference on Tools with Artificial Intelligence (ICTAI 2012). IEEE, 2012. http://dx.doi.org/10.1109/ictai.2012.73.

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Fang, J., D. Duncan e A. S. Morse. "Sequential localization with inaccurate measurements". In 2009 American Control Conference. IEEE, 2009. http://dx.doi.org/10.1109/acc.2009.5160383.

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Teacy, W. T. Luke, Jigar Patel, Nicholas R. Jennings e Michael Luck. "Coping with inaccurate reputation sources". In the fourth international joint conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1082473.1082624.

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Doshi, Rajkumar S., James E. White, Raymond Lam e David J. Atkinson. "Reasoning With Inaccurate Spatial Knowledge". In Robotics and IECON '87 Conferences, a cura di David P. Casasent e Ernest L. Hall. SPIE, 1988. http://dx.doi.org/10.1117/12.942800.

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Kacewicz, Boleslaw Z., e Marek A. Kowalski. "Recovering signals from inaccurate data". In Robotics - DL tentative, a cura di Martine J. Silbermann e Hemant D. Tagare. SPIE, 1992. http://dx.doi.org/10.1117/12.135135.

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Shafranova, E. E. "Inaccurate indicators as an investment risk". In ТЕНДЕНЦИИ РАЗВИТИЯ НАУКИ И ОБРАЗОВАНИЯ. НИЦ «Л-Журнал», 2018. http://dx.doi.org/10.18411/lj-04-2018-45.

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Albarelli, Andrea, Emanuele Rodolà e Andrea Torsello. "Robust Camera Calibration using Inaccurate Targets". In British Machine Vision Conference 2010. British Machine Vision Association, 2010. http://dx.doi.org/10.5244/c.24.16.

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Kessler Faulkner, Taylor A., Elaine Schaertl Short e Andrea L. Thomaz. "Interactive Reinforcement Learning with Inaccurate Feedback". In 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2020. http://dx.doi.org/10.1109/icra40945.2020.9197219.

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Bilinski, Mark, e Ryan Gabrys. "Set reconciliation with an inaccurate oracle". In 2017 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2017. http://dx.doi.org/10.1109/iccnc.2017.7876279.

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Rapporti di organizzazioni sul tema "Inaccurate"

Bohren, J. Aislinn, Kareem Haggag, Alex Imas e Devin Pope. Inaccurate Statistical Discrimination: An Identification Problem. Cambridge, MA: National Bureau of Economic Research, giugno 2019. http://dx.doi.org/10.3386/w25935.

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Halloran, Alex, Colton Huntsman, Chad Demers e Michael Courtney. More Inaccurate Specifications of Ballistic Coefficients. Fort Belvoir, VA: Defense Technical Information Center, gennaio 2012. http://dx.doi.org/10.21236/ada555975.

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Pinar, Ali. Accurate Characterization of Real Networks from Inaccurate Measurements. Office of Scientific and Technical Information (OSTI), gennaio 2018. http://dx.doi.org/10.2172/1814082.

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Young, Shelton R., James B. Helfrich, Joel K. Chaney, Curt W. Malthouse e Ted R. Paulson. Quick-Reaction Report on Inaccurate Determination of Initial Spares Support List Requirements. Fort Belvoir, VA: Defense Technical Information Center, ottobre 1991. http://dx.doi.org/10.21236/ada378638.

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Alexander, J. Trent, Michael Davern e Betsey Stevenson. Inaccurate age and sex data in the Census PUMS files: Evidence and Implications. Cambridge, MA: National Bureau of Economic Research, gennaio 2010. http://dx.doi.org/10.3386/w15703.

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Bao, Jieyi, Xiaoqiang Hu, Cheng Peng, Yi Jiang, Shuo Li e Tommy Nantung. Truck Traffic and Load Spectra of Indiana Roadways for the Mechanistic-Empirical Pavement Design Guide. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317227.

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The Mechanistic-Empirical Pavement Design Guide (MEPDG) has been employed for pavement design by the Indiana Department of Transportation (INDOT) since 2009 and has generated efficient pavement designs with a lower cost. It has been demonstrated that the success of MEPDG implementation depends largely on a high level of accuracy associated with the information supplied as design inputs. Vehicular traffic loading is one of the key factors that may cause not only pavement structural failures, such as fatigue cracking and rutting, but also functional surface distresses, including friction and smoothness. In particular, truck load spectra play a critical role in all aspects of the pavement structure design. Inaccurate traffic information will yield an incorrect estimate of pavement thickness, which can either make the pavement fail prematurely in the case of under-designed thickness or increase construction cost in the case of over-designed thickness. The primary objective of this study was to update the traffic design input module, and thus to improve the current INDOT pavement design procedures. Efforts were made to reclassify truck traffic categories to accurately account for the specific axle load spectra on two-lane roads with low truck traffic and interstate routes with very high truck traffic. The traffic input module was updated with the most recent data to better reflect the axle load spectra for pavement design. Vehicle platoons were analyzed to better understand the truck traffic characteristics. The unclassified vehicles by traffic recording devices were examined and analyzed to identify possible causes of the inaccurate data collection. Bus traffic in the Indiana urban areas was investigated to provide additional information for highway engineers with respect to city streets as well as highway sections passing through urban areas. New equivalent single axle load (ESAL) values were determined based on the updated traffic data. In addition, a truck traffic data repository and visualization model and a TABLEAU interactive visualization dashboard model were developed for easy access, view, storage, and analysis of MEPDG related traffic data.

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Crouch, Rebecca, Jared Smith, Bobbi Stromer, Christian Hubley, Samuel Beal, Guilherme Lotufo, Afrachanna Butler et al. Methods for simultaneous determination of legacy and insensitive munition (IM) constituents in aqueous, soil/sediment, and tissue matrices. Engineer Research and Development Center (U.S.), agosto 2021. http://dx.doi.org/10.21079/11681/41720.

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Currently, no standard method exists for analyzing insensitive munition (IM) compounds in environmental matrices, with or without concurrent legacy munition compounds, resulting in potentially inaccurate determinations. The primary objective of this work was to develop new methods of extraction, pre-concentration, and analytical separation/quantitation of 17 legacy munition compounds along with several additional IM compounds, IM breakdown products, and other munition compounds that are not currently included in U.S. Environmental Protection Agency (EPA) Method 8330B. Analytical methods were developed to enable sensitive, simultaneous detection and quantitation of the 24 IM and legacy compounds, including two orthogonal high-performance liquid chromatography (HPLC) column separations with either ultraviolet (UV) or mass spectrometric (MS) detection. Procedures were developed for simultaneous extraction of all 24 analytes and two surrogates (1,2-dinitrobenzene, 1,2-DNB; o-NBA) from high- and low-level aqueous matrices and solid matrices, using acidification, solid phase extraction (SPE), or solvent extraction (SE), respectively. The majority of compounds were recovered from four tissue types within current limits for solids, with generally low recovery only for Tetryl (from 4 to 62%). A preparatory chromatographic interference removal procedure was adapted for tissue extracts, as various analytical interferences were observed for all studied tissue types.

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Stromer, Bobbi, Rebecca Crouch, Katrinka Wayne, Ashley Kimble, Jared Smith e Anthony Bednar. Methods for simultaneous determination of 29 legacy and insensitive munition (IM) constituents in aqueous, soil-sediment, and tissue matrices by high-performance liquid chromatography (HPLC). Engineer Research and Development Center (U.S.), settembre 2021. http://dx.doi.org/10.21079/1168142105.

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Standard methods are in place for analysis of 17 legacy munitions compounds and one surrogate in water and soil matrices; however, several insensitive munition (IM) and degradation products are not part of these analytical procedures. This lack could lead to inaccurate determinations of munitions in environmental samples by either not measuring for IM compounds or using methods not designed for IM and other legacy compounds. This work seeks to continue expanding the list of target analytes currently included in the US Environmental Protection Agency (EPA) Method 8330B. This technical report presents three methods capable of detecting 29 legacy, IM, and degradation products in a single High Performance Liquid Chromatography (HPLC) method with either ultraviolet (UV)-visible absorbance detection or mass spectrometric detection. Procedures were developed from previously published works and include the addition of hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine (MNX); hexahydro-1,3-dinitroso-5-nitro-1,3,5-triazine (DNX); hexahydro-1,3,5-trinitroso-1,3,5-triazine (TNX); 2,4-diamino-6-nitrotoluene (2,4-DANT); and 2,6-diamino-4-nitrotoluene (2,6-DANT). One primary analytical method and two secondary (confirmation) methods were developed capable of detecting 29 analytes and two surrogates. Methods for high water concentrations (direct injection), low-level water concentrations (solid phase extraction), soil (solvent extraction), and tissue (solvent extraction) were tested for analyte recovery of the new compounds.

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Ghislandi, Simone, Raya Muttarak, Markus Sauerberg e Benedetta Scotti. Human costs of the first wave of the COVID-19 pandemic in the major epicentres in Italy. Verlag der Österreichischen Akademie der Wissenschaften, luglio 2021. http://dx.doi.org/10.1553/populationyearbook2022.res2.1.

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Deaths from COVID-19 can be miscounted due to under-reporting and inaccurate death registration. Mortality is often reported at the national level, which can result in the underestimation of the true scale of the impact of the pandemic since outbreaks tend to be localised. This study exploits all-cause daily death registration data provided by the Italian Statistical Office (ISTAT) from 1 January to 31 October to estimate the excess mortality and the corresponding changes in life expectancy during the first wave of the COVID-19 pandemic. Focusing on the five most severely hit provinces in Italy (Bergamo, Brescia, Cremona, Lodi and Piacenza), we calculate the excess mortality in 2020 compared to the average mortality of the years 2015 to 2019. Moreover, we estimate the excess mortality in the first quadrimester of 2020, and the annual life expectancy at birth. The estimated excess deaths show that during this period, mortality was significantly higher than the official mortality statistics for COVID-19. According to our estimates for the first quadrimester, life expectancy in the five provinces declined by 5.4 to 8.1 for men and by 4.1 to 5.8 years for women. In addition, we find that annual life expectancy decreased by 2.4 to 4.1 years for men and by 1.9 to 2.8 years for women compared to the 2015–2019 average. Thus, we conclude that the first wave of the COVID-19 pandemic had a substantial impact on population health in the hardest hit areas in Italy.

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Southwell, Brian, e Vanessa Boudewyns, a cura di. Curbing the Spread of Misinformation: Insights, Innovations, and Interpretations from the Misinformation Solutions Forum. RTI Press, dicembre 2018. http://dx.doi.org/10.3768/rtipress.2018.cp.0008.1812.

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Although many people now have access to more accumulated information than has ever been the case in human existence, we also now face a moment when the proliferation of misinformation, or false or inaccurate information, poses major challenges. In response to these challenges and to build collaboration across disciplines and expertise and a more effective community of learning and practice, the Rita Allen Foundation partnered with RTI International and the Aspen Institute along with Craig Newmark Philanthropies, Democracy Fund, and Burroughs Wellcome Fund to hold the Misinformation Solutions Forum in October 2018 at the Aspen Institute in Washington, DC. This forum brought together academic researchers, technology professionals, data scientists, journalists, educators, community leaders, funders and a set of graduate student fellows to explore promising ideas for curbing the spread of misinformation. We issued an open call for ideas to be featured in the forum that sought interventions focused on reducing behaviors that lead to the spread of misinformation or encouraging behaviors that can lead to the minimization of its influence. Interventions with technological, educational, and/or community-based components were encouraged, as were projects involving science communication, public health and diverse populations. A panel of expert judges assessed submissions through a blind review process; judges included representatives from the Rita Allen Foundation, as well as external institutions such as the Democracy Fund, the National Institutes of Health, the Poynter Institute, First Draft, and academic institutions. Authors developed the essays presented here based on both original submissions and the iterative collaboration process that ensued.

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