Relevant bibliographies by topics / Confusion Assessment Method

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Confusion Assessment Method'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Confusion Assessment Method"

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Inouye, Sharon K. "Clarifying Confusion: The Confusion Assessment Method." Annals of Internal Medicine 113, no. 12 (December 15, 1990): 941. http://dx.doi.org/10.7326/0003-4819-113-12-941.

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Waszynski, Christine M. "Confusion Assessment Method (CAM)." Journal of Gerontological Nursing 27, no. 4 (April 1, 2002): 4–5. http://dx.doi.org/10.3928/0098-9134-20020401-04.

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Jackson, James C., and E. Wesley Ely. "The Confusion Assessment Method (CAM)." International Journal of Geriatric Psychiatry 18, no. 6 (2003): 557–58. http://dx.doi.org/10.1002/gps.872.

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Inouye, S. K. "Correction: Table on the Confusion Assessment Method." Annals of Internal Medicine 114, no. 5 (March 1, 1991): 433. http://dx.doi.org/10.7326/0003-4819-114-5-433_2.

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Tsuruta, Ryosuke. "The confusion assessment method for the ICU." Journal of the Japanese Society of Intensive Care Medicine 14, no. 2 (2007): 229–30. http://dx.doi.org/10.3918/jsicm.14.229.

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Schümmelfeder, Frank. "Confusion Assessment Method (CAM) – an instrument for the diagnosis of acute Confusion." Connect: The World of Critical Care Nursing 3, no. 3 (September 2004): 74–76. http://dx.doi.org/10.1891/1748-6254.3.3.74.

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Antoine, V., J. Belmin, H. Blain, S. Bonin-Guillaume, L. Goldsmith, O. Guerin, M. J. Kergoat, et al. "Adaptation transculturelle francophone de la Confusion Assessment Method." Revue d'Épidémiologie et de Santé Publique 66, no. 3 (May 2018): 187–94. http://dx.doi.org/10.1016/j.respe.2018.01.133.

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Caino de Oliveira, Felipe Rezende, Orlei Ribeiro de Araujo, and Werther Brunow de Carvalho. "Is Delirium Pediatric Confusion Assessment Method Tools Confiable?" Pediatric Critical Care Medicine 21, no. 4 (April 2020): 406. http://dx.doi.org/10.1097/pcc.0000000000002284.

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Smith, Heidi A. B., Maalobeeka Gangopadhyay, Christina M. Goben, Natalie L. Jacobowski, Mary Hamilton Chestnut, Shane Savage, Michael T. Rutherford, et al. "The Preschool Confusion Assessment Method for the ICU." Critical Care Medicine 44, no. 3 (March 2016): 592–600. http://dx.doi.org/10.1097/ccm.0000000000001428.

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Laplante, Johanne, and Martin G. Cole. "DETECTION OF DELIRIUM USING THE CONFUSION ASSESSMENT METHOD." Journal of Gerontological Nursing 27, no. 9 (September 1, 2001): 16–23. http://dx.doi.org/10.3928/0098-9134-20010901-05.

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Dissertations / Theses on the topic "Confusion Assessment Method"

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Paul, Michaelynn R. "Medical Floor Confusion Assessment Method: Implementation and Assessment of Risk Factors." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/4243.

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An estimated 50% of older hospitalized patients experience delirium. This has created significant complications costing an estimated $164 billion or more per year worldwide. The ability to identify patients developing delirium would allow the implementation of specific interventions to decrease or eliminate the adverse effects of delirium. The purpose of this quality improvement project was to provide high quality delirium education to determine if medical unit nursing staff could successful implement the Confusion Assessment Method (CAM) screening tool to identify patients experiencing delirium as the first phase of an overall plan. Implementation of the project followed Roger's diffusion of innovations theory. Patients were additionally screened for 5 potential risk factors of delirium from the multifactorial model of delirium to determine if delirium could be identified in the local population admitted to a single hospital. With a high quality education intervention, the staff nurses on the medical unit successfully implemented the CAM into their nursing practice and accurately identified delirium. Nurses identified delirium and subsyndromal delirium in 25% of the 208 patients in the study population. Consistent with the literature, patients who had a urinary catheter and experienced an iatrogenic event were predictors of delirium. An additional predictor of delirium, not included in the multifactorial model of delirium, included patients receiving benzodiazepines. This quality improvement project suggests that quality delirium education combined with the use of an accurate delirium detection tool could predict delirium accurately in the medical floor population. This has the potential to reduce the impact of delirium on patients, hospital staff, and reduce hospital expenditures.
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Townsend, Nichole L. "Validation of the Confusion Assessment Method in the Intensive Care Unit in the Post-Anesthesia Care Unit." Thesis, The University of Arizona, 2012. http://hdl.handle.net/10150/221596.

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A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.
Introduction: Patients who develop delirium while hospitalized are increasingly recognized as at risk for the development of long term cognitive impairment. We became interested in the contribution of delirium to the development of post-operative cognitive dysfunction (POCD) when we found that patients at Mayo Clinic in Arizona, compared to patients at the Mayo facilities in Rochester, MN, were 17 times more likely to receive the drug physostigmine (Antilirium®) for the treatment of delirium in the Post Anesthesia Care Unit (PACU). However, before we could examine the relationship between delirium and POCD we needed to validate a tool we could use to quickly assess the presence of delirium in patients emerging from anesthesia in the PACU. Hypothesis: The Confusion Assessment Method in the Intensive Care Unit (CAM-ICU) can be used in the PACU to identify patients with delirium. Methods: Patients 65 years of age or greater who were going to have a standardized general anesthetic for a surgical procedure were identified on the day of surgery and consent to participate in the study was obtained. The CAM-ICU was used preoperatively to determine study eligibility (patients who scored less than 7 [scale of 1-10], indicating delirium, on the test were not followed further) and postoperatively, one hour after the patient was admitted to the PACU, to assess for delirium. The CAM-ICU was administered after we asked the patient’s nurse whether or not he or she had determined that the patient was delirious. Results: 168 patients, mean age 75 ± 7 (SD) with the majority of participants having urologic or orthopedic procedures were assessed pre- and post-operatively with the CAM-ICU, and post-operatively by a nursing assessment for delirium. The CAM-ICU took little time to administer and was easy for patients to understand and use. The nurse at the bedside identified 5 of 168 patients as delirious (prevalence of 2.98%). The CAM-ICU was positive for delirium in 11 of 168 (6.55%). The CAM-ICU had a sensitivity of 60% (3/5) and a specificity of 95% (155/163). Conclusion: In this investigation, the CAM-ICU was easy to use and had a high specificity for identifying post-operative delirium.
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Schneider, Moritz [Verfasser]. "Das frühe postoperative Delirium : Vergleich des Nursing Delirium Screening Scale und der Confusion Assessment Method / Moritz Schneider." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2009. http://d-nb.info/1027813674/34.

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Ullrich, Dennis [Verfasser]. "Validierung der Schweregradskala für die Confusion Assessment Method für Intensivstationen bei neurologischen und neurochirurgischen Intensivpatienten / Dennis Ullrich." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2021. http://d-nb.info/1241539766/34.

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Klugkist, Meint Henrik. "Diagnostik des postoperativen Delirs bei kardiochirurgischen Patienten mit der Confusion Assessment Method for the Intensive Care Unit (CAM-ICU)." Lübeck Zentrale Hochschulbibliothek Lübeck, 2009. http://d-nb.info/1000926648/34.

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Klugkist, Meint Henrik [Verfasser]. "Diagnostik des postoperativen Delirs bei kardiochirurgischen Patienten mit der Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) / Meint Henrik Klugkist." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2009. http://d-nb.info/1000926648/34.

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Köcher, Lena [Verfasser]. "Validität und Reliabilität der deutschen Übersetzung der Confusion Assessment Method for Intensive Care Units (CAM-ICU) zur Erkennung eines Delirs auf Intensivstationen / Lena Köcher." Bonn : Universitäts- und Landesbibliothek Bonn, 2012. http://d-nb.info/1043699082/34.

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Olofsson, Susanne. "Att beskriva och jämföra en expertgrupp och intensivvårdssjuksköterskors överensstämmelse i att detektera delirium hos intuberade, respiratorbehandlade patienter med sedering/analgesi, före och efter en utbildningsintervention : En kvasiexperimentell studie." Thesis, Högskolan i Gävle, Avdelningen för hälso- och vårdvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-18598.

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The aim: was to describe and compare a group of experts and critical care nurses' agreement in detecting delirium in intubated, ventilator treated patients with sedation / analgesia, before and after an in house training intervention with the instrument Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Method: A quasi-experimental study, one group pretest - posttest design. A convenience sample of 17 critical care nurses in a general intensive care unit included. To detect delirium the instrument CAM-ICU was used, 21 paired tests before and 22 after an educational intervention. Main Results: The results showed that after an in house training intervention sensitivity and kappa coefficient improved of the characteristic 1 "acute onset and fluctuating course," an improvement that was significant. In other features, and overall values were signs of numerical improvement and deterioration in sensitivity, specificity and kappa coefficient but no significant change. Conclusion: Implementing a new instrument for detecting delirium in clinical practice requires education and follow-up. A small sample of critical care nurses with varying ability to use the new instrument and the fact that patients' status may change rapidly making it difficult to draw any conclusions from this study. It is clear, however, that education and follow-up is needed when new care routines are introduced, and that further studies are needed to clarify whether the CAM-ICU is a valit and reliable instrument to use in clinical practice.
Syftet var att beskriva och jämföra en expertgrupp och intensivvårdssjuksköterskors överensstämmelse i att detektera delirium hos intuberade, respiratorbehandlade patienter med sedering/analgesi, före och efter en utbildningsintervention med instrumentet Confusion assessment method for the intensive care unit (CAM-ICU). Metod: En kvasiexperimentell studie, en grupps pretest – posttest design. Ett bekvämlighetsurval på en allmän intensivvårdsavdelning där inkluderades 17 intensivvårdssjuksköterskor. För att detektera delirium användes instrumentet CAM-ICU, 21 parmätningarna före och 22 efter en utbildningsintervention. Huvudresultat: Resultatet visade att efter utbildningsinterventionen förbättrades sensitiviteten och kappa koefficienten i kännetecken 1 ”akut insättande eller fluktuerande förlopp”, en förbättring som var signifikant. I övriga kännetecken och totalvärden fanns tecken på numerär förbättring och försämring i sensitivitet, specificitet och kappakoefficient men ingen signifikant förändring. Slutsats: Att implementera ett nytt instrument för att detektera delirium i klinisk verksamhet kräver utbildning och uppföljning. Ett litet sample av intensivvårdssjuksköterskor med varierad förmåga att använda det nya instrumentet samt det faktum att patienters status hastigt kan förändras gör det svårt att dra några slutsatser av denna studie. Klart är dock att utbildning och uppföljning behövs när nya vårdrutiner införs, och att ytterligare studier behövs för att klargöra om CAM-ICU är ett valit och reliabelt instrument att använda i klinisk verksamhet.
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Martins, Sónia Patrícia Vilar. "Confusion Assessment Method (CAM); Adaptação e Validação Portuguesa." Tese, 2014. https://repositorio-aberto.up.pt/handle/10216/106209.

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Martins, Sónia Patrícia Vilar. "Confusion Assessment Method (CAM); Adaptação e Validação Portuguesa." Doctoral thesis, 2014. https://repositorio-aberto.up.pt/handle/10216/106209.

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Books on the topic "Confusion Assessment Method"

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Alvis, Bret D., and Christopher G. Hughes. Delirium. Edited by Matthew D. McEvoy and Cory M. Furse. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190226459.003.0061.

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Delirium in the postoperative period, characterized by inattention, disorganized thinking, disorientation, and/or altered levels of consciousness within the first few days after surgery, has been associated with significant increases in hospital stay, functional decline, prolonged cognitive dysfunction, and mortality. It is underdiagnosed without routine assessments with validated tools such as the Confusion Assessment Method (CAM), the 4AT, the Confusion Assessment Method for Intensive Care Unit (CAM-ICU), or the Intensive Care Delirium Screening Checklist (ICDSC). Prevention strategies for postoperative delirium include multimodal pain control, judicious use of medications that affect the sensorium, including benzodiazepines and anticholinergics, maintenance of appropriate volume status, and optimization of the patient’s environment. In patients who develop delirium with severe agitation, antipsychotic and alpha-2 agonist medications may be useful. Because postoperative delirium occurs commonly and is associated with worse outcomes, an understanding of its disease process, risk factors, and management is essential for an anesthesiologist.
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Hogg, Jenny. Delirium. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199644957.003.0040.

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Delirium (acute confusional state) is a common condition affecting between ten and thirty percent of a general hospital inpatient population. The diagnosis is suspected when there is an acute onset of confusion in the presence of a physical precipitant. Pre-existing dementia, advancing age, previous delirium and increasing illness severity favour the development of delirium. The diagnosis of delirium is solely clinical and can be quickly arrived at using assessment tools such as the cognitive Assessment Method (CAM). Historical perspectives, diagnosis, the use of assessment tools, differential diagnosis, communication with patients and relatives, prevention, prognosis, and treatment are discussed in this chapter, along with the pathophysiology of this common condition
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van den Boogaard, Mark, and Paul Rood. Delirium in Critically Ill Patients. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199398690.003.0002.

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This chapter addresses delirium in critically ill patients in the intensive care unit (ICU), especially the mixed subtype (alternating hyperactivity and hypoactivity). The Confusion Assessment Method for the ICU and the Intensive Care Delirium Screening Checklist are discussed as useful delirium assessment tools in this setting. Several neurotransmitter pathways have been implicated in delirium, including cholinergic, GABAergic, and serotonergic pathways; cytokines and glucocorticoids also appear relevant. Risk factors for delirium in the ICU include older age, prior cognitive impairment, worse illness severity, recent delirium or coma, mechanical ventilation, admission category (especially trauma or neurological/neurosurgical admission), infection, metabolic acidosis, morphine and sedative administration, urea concentration, respiratory failure, and admission urgency. Prevention and treatment of delirium are discussed, including nonpharmacological interventions (frequent reorientation, providing eyeglasses and hearing aids if needed, promoting nighttime sleep, and early mobilization) and judicious use of opiate, sedative, and antipsychotic medications.
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Book chapters on the topic "Confusion Assessment Method"

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Hoyer, Daniel, Eric P. Zorrilla, Pietro Cottone, Sarah Parylak, Micaela Morelli, Nicola Simola, Nicola Simola, et al. "Confusion Assessment Method." In Encyclopedia of Psychopharmacology, 345–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_1161.

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Ghani, Nur Laila Ab, Siti Zaleha Zainal Abidin, and Noor Elaiza Abd Khalid. "Accuracy Assessment of Urban Growth Pattern Classification Methods Using Confusion Matrix and ROC Analysis." In Communications in Computer and Information Science, 255–64. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-936-3_24.

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Lemke, Claudia. "Methodology." In Sustainable Management, Wertschöpfung und Effizienz, 63–111. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-33246-4_4.

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AbstractBecause sustainable development only becomes defined when measured (see Chapter 3; e.g. Bell & Morse, 2008), sustainable development index construction is an unsupervised modelling task without a supervising output variable (G. James, Witten, Hastie & Tibshirani, 2013). Consequently, sustainable development measurement is diverse in methods and methodologies (see Section 3.2, Section 3.3, and Section 4.2) and hallmarked by subjectivity and arbitrariness (e.g. Böhringer & Jochem, 2007), such that sustainable development indicators are rather confusing and non-consensual (Pope et al., 2017; Ramos & Moreno Pires, 2013). To counteract this finding and to achieve objectivity in assessment (see Table 10.1007/978-3-658-33246-4_3; Sala et al., 2015), the previous theoretical research is coupled with a profound methodological research.
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"Confusion Assessment Method." In Encyclopedia of Psychopharmacology, 436. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-36172-2_200168.

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Inouye, Dyck, Alessi, Balkin, Siegal, and Horwitz. "Confusion Assessment Method (CAM)." In A Compendium of Tests, Scales and Questionnaires, 54–57. Psychology Press, 2020. http://dx.doi.org/10.4324/9781003076391-15.

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Farne, Hugo, Edward Norris-Cervetto, and James Warbrick-Smith. "Confusion." In Oxford Cases in Medicine and Surgery. Oxford University Press, 2015. http://dx.doi.org/10.1093/oso/9780198716228.003.0008.

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• Delirium: an acute impairment in cognitive ability together with impaired consciousness. • Dementia: a chronic, progressive impairment in cognitive ability but with intact consciousness. Note that this is different from delirium and that you cannot diagnose dementia from a single mental status assessment. • Mental impairment: a permanent impairment in cognitive ability. • Psychosis: the patient may not be confused, but have a disorder of thought content/perception (e.g. delusions and/or hallucinations). • Receptive dysphasia: the patient may have difficulties comprehending your questions (e.g. due to damage to Wernicke’s area of the brain). • Expressive dysphasia: the patient may be cognitively intact but have difficulties verbalizing an answer to your questions (e.g. due to damage to Broca’s area of the brain). Note that these syndromes may coexist in patients, particularly delirium and dementia which are both very common. Remember to start by checking the patient’s airway, breathing, and circulation (ABC) and whether they are in any pain that requires analgesia. To work out what type of confusion this is, you should start by conducting a quick screen of confusion because if the patient does poorly in your screen, taking a conventional history may prove unhelpful. For example, you may ask: • Are they oriented to time, place, and person? Can they tell you why they are here? The Abbreviated Mental Test Score (AMTS; see Box 2.1) is a simple 10-question screening tool for assessing confusion where a score of less than 6/10 indicates cognitive impairment. An alternative is the 30-question Mini Mental State Exam (MMSE), where a score of less than 26/30 indicates cognitive impairment. Be aware that there are many other scoring systems in routine use, such as the Confusion Assessment Method (CAM), Montreal Cognitive Assessment (MoCA), etc. • If their ability to converse is impaired, can they follow a three-step command? Can they name three common objects? These questions test for receptive and expressive dysphasia respectively. It will be fairly obvious early in your interaction with the patient whether either of these questions is relevant (they do not need to be asked routinely). • Other symptoms? Are they in pain? (even the most confused patient will complain of pain). You should also ask about breathlessness, cough, and urinary symptoms as a chest or urinary tract infection (UTI) is often the cause of confusion.
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Rashid, Megan. "Agitation." In Acute Care Casebook, edited by Julie Mayglothling Winkle, 180–83. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190865412.003.0036.

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The case illustrates a classic example of intensive care unit (ICU) delirium, which often goes unrecognized but can adversely affect both morbidity and mortality. The Confusion Assessment Method for the ICU (CAM-ICU) is a validated tool for diagnosing delirium, but it remains a diagnosis of exclusion, and it is important to rule out potentially life-threatening medical causes of altered mental status. Treatment is difficult even with the correct diagnosis, and prevention is key. The ABCDEF bundle (assessing and managing pain, both SAT and SBT, choice of analgesia/sedation, delirium, early mobility, and family engagement) is a tool that identifies high-risk populations, and can help mitigate the prevalence of ICU delirium.
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Cohen, DDS, MS, PhD, Nicolas. "Periodontal Treatment and Computerized Occlusal Analysis." In Oral Healthcare and Technologies, 75–111. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1903-4.ch002.

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This chapter addresses the ongoing controversy regarding occlusion's role in the progression of periodontal disease. Occlusal force has been considered a non-factor in the initiation of periodontal attachment loss. However, the absence of a validated measuring device or quantifying method for analyzing the occlusion has contributed to the confusion that still exists in the scientific community today about the relationship between periodontal disease and occlusion. The development of the T-Scan occlusal measurement technology, which is independent of a clinician's occlusal contact force level subjective assessment, may change the scientific opinion about occlusion's role in periodontal disease. This chapter illustrates how the T-Scan 8 system aids in treating patients who have tissue loss and occlusal issues. Notably, after the major etiologic risk factors of periodontal disease have been controlled, adjusting the occlusion with the T-Scan improves healing outcomes resulting in less inflammation, decreased probing depths, and bone level stability.
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Cohen, DDS, MS, PhD, Nicolas. "Periodontal Treatment and Computerized Occlusal Analysis." In Handbook of Research on Computerized Occlusal Analysis Technology Applications in Dental Medicine, 791–828. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-6587-3.ch018.

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This chapter addresses the ongoing controversy regarding occlusion's role in the progression of periodontal disease. Occlusal force has been considered a non-factor in the initiation of periodontal attachment loss. However, the absence of a validated measuring device or quantifying method for analyzing the occlusion has contributed to the confusion that still exists in the scientific community today about the relationship between periodontal disease and occlusion. The development of the T-Scan occlusal measurement technology, which is independent of a clinician's occlusal contact force level subjective assessment, may change the scientific opinion about occlusion's role in periodontal disease. This chapter illustrates how the T-Scan 8 system aids in treating patients who have tissue loss and occlusal issues. Notably, after the major etiologic risk factors of periodontal disease have been controlled, adjusting the occlusion with the T-Scan improves healing outcomes resulting in less inflammation, decreased probing depths, and bone level stability.
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Conference papers on the topic "Confusion Assessment Method"

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Linstrum, K., E. Nuzzo, B. Curtis, S. Rapport, B. J. McVerry, and T. D. Girard. "Comparison of the Confusion Assessment Method for the ICU (CAM-ICU) and the Intensive Care Delirium Screening Checklist (ICDSC) for Delirium Detection in Mechanically Ventilated ICU Patients." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a4120.

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Huang, Xiaoping, Xiaoshun Yan, Muk Chen Ong, and Yingcai Huang. "The Effect of Fatigue Loading Spectrum on Crack Propagation in a Ship Detail." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77152.

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The assessment of the loading sequence on fatigue crack growth of cracked details is essential when the ship hull is subjected to random wave-induced loading during the service time. In this paper, the effect of loading sequence on the crack growth life is investigated in order to find a physical engineering method to generate fatigue loading spectrum for ship fatigue assessment. The long term distribution of fatigue loading and the unique crack growth rate curve model have been employed in the analysis. The results show that the shape parameter affects the fatigue life significantly if the long-term distribution of wave-induced stress range is modeled by two-parameter Weibull distribution. Moreover, the spectral-based method provides a reasonable fatigue loading spectrum and avoid the confusion in determining the shape parameter for different empirical formulas, which are recommended by several main ship classification societies. An example of fatigue assessment for a cracked detail in a container ship is demonstrated as a reference for fatigue assessment of a ship hull based on crack growth.
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Awan, O., R. G. Buhr, and B. B. Kamdar. "Delirium... "Unable-to-Assess"? An Electronic Health Record-Based Evaluation of Inappropriate "Unable-to-Assess" Confusion Assessment Method for the Intensive Care Unit (ICU) Documentation in a Medical ICU." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a4099.

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Davison, Craig R., and Jeff W. Bird. "Review of Metrics and Assignment of Confidence Intervals for Health Management of Gas Turbine Engines." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50849.

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The development and evaluation of new diagnostic systems requires statistically-based methods to measure performance. Various metrics are in use by developers and users of diagnostic systems. Current metrics practices are reviewed, including receiver operating characteristics, confusion matrices, Kappa coefficients and various entropy techniques. A set of metrics is then proposed for assessment of diverse gas path diagnostic systems. The use of bootstrap statistics to compare metric results is developed, and demonstrated for a set of hypothetical data sets with a range of relevant characteristics. The bootstrap technique allows the expected range of the metric to be assessed without assuming a probability distribution. A method is proposed to develop confidence intervals for the calculated metrics. The application of a confidence interval could prevent a good diagnostic technique being discarded because of a lower value metric in one test instance. The strengths and weaknesses of the various metrics with derived confidence intervals are discussed. Recommendations are made for further work.
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Chandiramani, Dipak K., Suresh K. Nawandar, and Shyam Gopalakrishnan. "Stresses in Nozzle Shell Junctions due to External Loads: A Comparative Study." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97532.

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Various methods have been in use for the determination of stresses at the nozzle-shell junction due to external loads and moments. Some methods evaluate stress in the cylindrical or spherical shell (e.g. WRC 107 now WRC 537) while others evaluate stresses in cylindrical shells and nozzles (e.g. WRC 297). ASME Section VIII Division. 2 specifies use of WRC 107/WRC 297 or Finite Element Analysis (FEA) for determination of stresses at shell-nozzle junctions with external loads and moments on the nozzle. Each method could yield a different result for the same loading condition and geometry and this has been recognized in comparisons made in WRC 297 with WRC 107 and FEA. Further, customized FEA software are also available for this analysis. There still seems to be some confusion in users of these methods regarding selection of method for optimization of design. Users not familiar with Finite Element Method prefer to use calculations based on WRC 107/297. Hang-Sung Lee, et.al. have recently (PVP 2011 – 57407) analyzed nozzle shell junctions using the Finite Element Method, compared their results with calculations to WRC 297 and made recommendations. The work presented in this paper is not an attempt to compare individual stresses obtained by classical versus analytical methods. Instead, an attempt has been made to consolidate the results obtained by the various methods into charts to enable a user to make a preliminary assessment to ascertain under what geometrical conditions the calculations made by each of the above methods would result in overall Code acceptable stresses without the results being either overly conservative or un-conservative. This is particularly relevant to the geometries which use the graphs and charts which have been extrapolated without rigorous theoretical background in the WRC Bulletin 537. The Finite Element Method has been used as the referee method.
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Mateos-Ronco, Alicia, Juan Carlos Cortés López, Cristina Santamaría Navarro, and Rafael Villanueva Micó. "Evaluación de la competencia transversal “Análisis y resolución de problemas” (CT3) en la titulación de GADE de la Facultad de ADE de la Universitat Politècnica de Valéncia." In JIDDO 2019: “Formación en competencias transversales”. València: Editorial Universitat Politècnica de València, 2019. http://dx.doi.org/10.4995/jiddo2019.2019.10184.

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This paper describes the development and the conclusion of the meeting the professors of the Faculty of Business Administration in charge of the “point of control” subjects of the soft skill “Problem Analysis and Solving” (CT3) in the first and second level, held May 6th, 2019. The professors share their experience in implementing assessment methods in every subject following the guidelines of the general project of the UPV. The main conclusion is that the professor feels alone and has to find imaginative methods to assess the soft skill in a reliable way. Also, extant multiplicity of assessments of the skill contribute to certain confusion in the final consequence of the assessment in each subject, and hence a simplification is proposed.
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Pakalapati, Suryanarayana R., Hayri Sezer, and Ismail B. Celik. "Implications of Using Dual Number Derivatives With a Numerical Solution." In ASME 2013 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/fedsm2013-16378.

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Dual number arithmetic is a well-known strategy for automatic differentiation of computer codes which gives exact derivatives, to the machine accuracy, of the computed quantities with respect to any of the involved variables. A common application of this concept in Computational Fluid Dynamics, or numerical modeling in general, is to assess the sensitivity of mathematical models to the model parameters. However, dual number arithmetic, in theory, finds the derivatives of the actual mathematical expressions evaluated by the computer code. Thus the sensitivity to a model parameter found by dual number automatic differentiation is essentially that of the combination of the actual mathematical equations, the numerical scheme and the grid used to solve the equations not just that of the model equations alone as implied by some studies. This aspect of the sensitivity analysis of numerical simulations using dual number auto derivation is explored in the current study. A simple one-dimensional advection diffusion equation is discretized using different schemes of finite volume method and the resulting systems of equations are solved numerically. Derivatives of the numerical solutions with respect to parameters are evaluated automatically using dual number automatic differentiation. In addition the derivatives are also estimated using finite differencing for comparison. The analytical solution was also found for the original PDE and derivatives of this solution are also computed analytically. It is shown that a mathematical model could potentially show different sensitivity to a model parameter depending on the numerical method employed to solve the equations and the grid resolution used. This distinction is important since such inter-dependence needs to be carefully addressed to avoid confusion when reporting the sensitivity of predictions to a model parameter using a computer code. A systematic assessment of numerical uncertainty in the sensitivities computed using automatic differentiation is presented.
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Benammar, Sarra, Fatima Mraiche, Jensa Mariam Joseph, and Katerina Gorachinova. "Glucose and Transferrin Liganded PLGA Nanoparticles Internalization in Non-Small Lung Cancer Cells." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0227.

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Introduction: Recently, after a decade of confusing results, several studies pointed out that overexpression of GLUT1 (glucose transporter 1) is a biomarker of worse prognosis in NSCLC. Nonetheless, the presence of transferrin (Tf receptor), which is overexpressed in most cancer tissues and most lung cancers as well, in NSCLC is also an indicator of very poor prognosis. Therefore, these ligands can be used for active targeting of lung cancer cells and improved efficacy of internalization of cancer therapy using nanomedicines. Objectives: Having the background, the main goal of the project was the assessment of the influence of the glucose and transferrin ligands on the efficacy of internalization of the designed (i) glucose decorated PLGA (poly lactic-coglycolic acid) nanoparticles (Glu-PLGA NPs) and (ii) transferrin decorated PLGA nanoparticles (Tf-PLGA NPs) in comparison to (iii) non-liganded PLGA NPs using a A549 lung cancer cells. Methods: Glu-PLGA NPs, Tf-PLGA NPs and PLGA NP - fluorescently labelled), were designed using a sonication assisted nanoprecipitation method. Further, physicochemical properties characterization (particle size analysis, zeta potential, FTIR analysis, DSC analysis), cytotoxicity evaluation using MTT test, and cell internalization studies of DTAF labelled NPs using fluorimetry in A549 NSCLC cell line were performed. Results: The results pointed to a significantly improved internalization rate of the liganded compared to PLGA NPs. Glu-PLGA NPs showed higher internalization rate compared to Tf-PLGA and PLGA NPs, in the serum-supplemented and serumfree medium even at normal levels of glucose in the cell growth medium. Conclusion: The developed nanocarriers offer unique advantages of enhanced targetability, improved cell internalization and decreased toxicity, which makes them promising solution for current therapeutic limitations.
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Weiss, Brian A., and Jared Kaplan. "Verification of a Novel Position Verification Sensor to Identify and Isolate Robot Workcell Health Degradation." In ASME 2020 15th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/msec2020-8484.

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Abstract Manufacturing processes have become increasingly sophisticated leading to greater usage of robotics. Sustaining successful manufacturing robotic operations requires a strategic maintenance program. Maintenance can be very costly, especially when some manufacturers unnecessarily spend resources (i.e., time, money) to maintain their equipment. To reduce maintenance costs, manufacturers are exploring how they can assess the health of their robot workcell operations to enhance their maintenance strategies. Effective health assessment relies upon capturing appropriate data and generating intelligence from the workcell. Multiple data streams relevant to a robot workcell may be available including robot controller data, a supervisory programmable logic controller data, maintenance logs, process/part quality data, and equipment/process fault and/or failure data. This data can be extremely informative, yet the extreme volume and complexity of this data can be both overwhelming, confusing, and paralyzing. Researchers at the National Institute of Standards and Technology have developed a test method and companion sensor to assess the health of robot workcells, which will yield an additional and unique data stream. The intent is that this data stream can either serve as a surrogate for larger data volumes to reduce the data collection and analysis burden on the manufacturer or add more intelligence to assessing robot workcell health. This article will present the immediate effort focused on verifying the companion sensor. Results of the verification test process are discussed along with preliminary results of the sensor’s performance during verification testing.
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