Literatura académica sobre el tema "Rupture detection"
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Artículos de revistas sobre el tema "Rupture detection"
Charnock, Mark. "Ultrasound Assessment of an Isolated Rupture of the Medial Bundle of a Bifid Distal Biceps Tendon". Journal of Medical Ultrasound 31, n.º 4 (7 de octubre de 2022): 323–26. http://dx.doi.org/10.4103/jmu.jmu_45_22.
Texto completoXing, Liang, Haibo Long, Rui Bo, Xue Gou, Yan He y Xing Peng. "A Computational Model of Blood D-Dimer, Cystatin C, and CRP Levels Predicts the Risk of Intracranial Aneurysms and their Rupture". Computational Intelligence and Neuroscience 2022 (18 de noviembre de 2022): 1–10. http://dx.doi.org/10.1155/2022/2216509.
Texto completoKünsch, Christophe, Lukas Fürer, Martin Steppan, Nathalie Schenk, Kathrin Blum, Michael Kaess, Julian Koenig, Klaus Schmeck y Ronan Zimmermann. "Withdrawal ruptures in adolescents with borderline personality disorder psychotherapy are marked by increased speech pauses–can minimal responses be automatically detected?" PLOS ONE 18, n.º 1 (17 de enero de 2023): e0280329. http://dx.doi.org/10.1371/journal.pone.0280329.
Texto completoDupont, Stefan A., Giuseppe Lanzino, Eelco F. M. Wijdicks y Alejandro A. Rabinstein. "The use of clinical and routine imaging data to differentiate between aneurysmal and nonaneurysmal subarachnoid hemorrhage prior to angiography". Journal of Neurosurgery 113, n.º 4 (octubre de 2010): 790–94. http://dx.doi.org/10.3171/2010.4.jns091932.
Texto completoWada, Kojiro, Hirohiko Arimoto, Hidenori Ohkawa, Toshiki Shirotani, Yohsitaro Matsushita y Takashi Takahara. "Usefulness of Preoperative Three-Dimensional Computed Tomographic Angiography With Two-Dimensional Computed Tomographic Imaging for Rupture Point Detection of Middle Cerebral Artery Aneurysms". Operative Neurosurgery 62, suppl_1 (1 de marzo de 2008): ONS126—ONS133. http://dx.doi.org/10.1227/01.neu.0000317382.45691.1a.
Texto completoNenezić, Dragoslav y Igor Kocijancic. "The value of the sagittal-oblique MRI technique for injuries of the anterior cruciate ligament in the knee". Radiology and Oncology 47, n.º 1 (1 de enero de 2013): 19–25. http://dx.doi.org/10.2478/raon-2013-0006.
Texto completoDowden, Richard V. "Detection of Gel Implant Rupture". Plastic and Reconstructive Surgery 91, n.º 3 (marzo de 1993): 548–50. http://dx.doi.org/10.1097/00006534-199303000-00025.
Texto completoNg, Beng Kwang, Pei Shan Lim, Mohamad Nasir Shafiee, Nur Azurah Abdul Ghani, Nor Azlin Mohamed Ismail, Mohd Hashim Omar y Muhammad Abdul Jamil Muhammad Yassin. "Comparison between Amnisure Placental Alpha Microglobulin-1 Rapid Immunoassay and Standard Diagnostic Methods for Detection of Rupture of Membranes". BioMed Research International 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/587438.
Texto completoJukovic, Mirela, Tijana Kokovic, Dragan Nikolic, Dalibor Ilic y Viktor Till. "Lower back pain - silent symptom of chronic infrarenal abdominal aneurysm rupture". Medical review 69, n.º 3-4 (2016): 115–17. http://dx.doi.org/10.2298/mpns1604115j.
Texto completoHarris, K. M., M. A. Ganott, K. C. Shestak, H. W. Losken y H. Tobon. "Silicone implant rupture: detection with US." Radiology 187, n.º 3 (junio de 1993): 761–68. http://dx.doi.org/10.1148/radiology.187.3.8497626.
Texto completoTesis sobre el tema "Rupture detection"
Fu, Jiyuan. "Using Thermographic Image Analysis in Detection of Canine Anterior Cruciate Ligament Rupture Disease". Thesis, Southern Illinois University at Edwardsville, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1582920.
Texto completoAnterior cruciate ligament (ACL) rupture is a common trauma which frequently happens in overweight dogs. Veterinarians use MRI (Magnetic resonance imaging) as the standard method to diagnose this disease. However MRI is expensive and time-consuming. Therefore, it is necessary to find an alternative diagnostic method. In this research, thermographic images are utilized as a prescreening tools for the detection of ACL rupture disease. Meanwhile, a quantitative comparison is made of new feature vectors based on Gabor filters with different frequencies and orientations.
Sim, Alisia Mara. "Detection of calcification in atherosclerotic plaques using optical imaging". Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33151.
Texto completoTaillade, Thibault. "A new strategy for change detection in SAR time-series : application to target detection". Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPAST050.
Texto completoThe detection of targets such as ships or vehicles in SAR (Synthetic Aperture Radar) images is an essential challenge for surveillance and security purpose. In some environments such as urban areas, harbor areas or forest observed at low radar frequencies, detecting these objects becomes difficult due to the high backscattering properties of the surrounding background. To overcome this issue, change detection (CD) between SAR images enables to cancel the background and highlight successfully targets present within the scene. However, in several environments, a temporal overlapping of targets may occur and generates possible misinterpretation because the outcome relies on the relative change between objects of different sizes or properties. This is a critical issue when the purpose is to visualize and obtain the number of targets at a specific day in high attendance areas such as harbors or urban environments. Ideally, this change detection should occur between a target-free image and onewith possible objects of interest. With the current accessibility to SAR time-series, we propose to compute a frozen background reference (FBR) image that will consists only in the temporally static background. Performing change detection from this FBR image and any SAR image aim to highlight the presence of ephemeral targets. This strategy has been implemented for ship detection in harbor environment and in the context of vehicles hidden under foliage
LAGRANGE, DOMINIQUE. "Estimation de la date et de l'amplitude d'une rupture conditionnellement a sa detection par une carte cusum". Paris, Institut national d'agronomie de Paris Grignon, 1997. http://www.theses.fr/1997INAP0045.
Texto completoDahal, Rohini. "Bilateral Thermographic Image Comparison Software Tool for Pathology Detection in Canines with Application to Anterior Cruciate Ligament (ACL) Rupture". Thesis, Southern Illinois University at Edwardsville, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10276314.
Texto completoIntroduction: The bilaterally symmetry property in animals can be used to detect pathologies where body parts on both sides can be compared. For any pathological disorder, thermal patterns differ compared to the normal body parts. A software application for veterinary clinics is under development to input two thermograms of body parts on both sides, one normal and the other unknown, and the application compares them on the basis of extracted features and appropriate similarity and difference measures and outputs the likelihood of pathology. Previous research has been used to determine the appropriate image processing, feature extraction and comparison metrics to be used. The comparison metrics used are the vector inner product, Tanimoto, Euclidean, city block, Minkowski and maximum value metric. Also, results from experiments with comparison tests are used to derive a potential threshold values which will separate normal from abnormal images for a specific pathology.
Objectives: The main objective of this research is to build a comparison software tool application by combining the concepts of bilateral symmetrical property in animals and IR thermography that can be for prescreening in veterinary clinics.
Comparison Software Tool Development: The comparison software tool was developed for veterinary clinics as a prescreening tool for pathology detection using the concepts of thermography and bilateral symmetry property in animals. The software tool has a graphical user interface (GUI) that allows ease of use for the clinical technician. The technician inputs images or raw temperature data csv files and compares thermographic images of bilateral body parts. The software extracts features from the images and calculates the difference between the feature vectors with distance and/or similarity metrics. Based upon these metrics, the percentage deviation is calculated which provides the deviation of the unknown (test) image from the known image. The percentage deviation between the thermograms of the same body parts on either side provides an indication regarding the extent and impact of the disease [Poudel; 2015]. The previous research in veterinary thermography [Liu; 2012; Subedi; 2014, Fu; 2014, Poudel; 2015] has been combined with the real world veterinary clinical scenario to develop a software tool that can be helpful for researchers as well as for the clinical technicians in prescreening of pathologies.
Experimental Results and Discussion: Experiments were performed on ACL thermograms to determine a threshold that can separate normal and abnormal ACL images. 18-colored Meditherm images had poor results and could not suggest any threshold value. But results were positive for temperature remapped 256 gray level Meditherm images which suggested the 40% of percentage deviation could produce a separation. The total number of Normal - Normal pairs were greater than total number of Normal – Abnormal pairs below 40% deviation. Similarly, total number of Normal –Abnormal pairs of images were greater than total number of Normal – Normal pairs above 40%. This trend was consistent for Euclidean distance, maximum value distance and Minkowski distance for both texture distances of 6 and 10. The performance in terms of sensitivity and specificity was poor. The best sensitivity of 55% and best specificity of 67% was achieved. This indicates better results for predicting the absence of ACL rupture then actually finding the disease. In this case the software could be used by the clinician in conjunction with other diagnostic methods.
Conclusion: The Experiments, results and analysis show that the comparison software tool can be used in veterinary clinics for the pre-screening of diseases in canines and felines to estimate the extent and impact of the disease based upon the percentage deviation. However, more research is necessary to examine its efficacy for specific pathologies. Note that the software can be used by researchers to compare any two images of any formats. For ACL experimentation, there are indication that a threshold value is possible to separate normal from abnormal and the spectral, texture and spectral features suggested by researches [Subedi; 2014, Liu; 2012, Fu; 2014, Poudel; 2015] are not sufficient to determine that threshold with the given image database.
Le, bars Batiste. "Event detection and structure inference for graph vectors". Thesis, université Paris-Saclay, 2021. http://www.theses.fr/2021UPASM003.
Texto completoThis thesis addresses different problems around the analysis and the modeling of graph signals i.e. vector data that are observed over graphs. In particular, we are interested in two tasks. The rst one is the problem of event detection, i.e. anomaly or changepoint detection, in a set of graph vectors. The second task concerns the inference of the graph structure underlying the observed graph vectors contained in a data set. At first, our work takes an application oriented aspect in which we propose a method for detecting antenna failures or breakdowns in a telecommunication network. The proposed approach is designed to be eective for communication networks in a broad sense and it implicitly takes into account the underlying graph structure of the data. In a second time, a new method for graph structure inference within the framework of Graph Signal Processing is investigated. In this problem, notions of both local and globalsmoothness, with respect to the underlying graph, are imposed to the vectors.Finally, we propose to combine the graph learning task with the change-point detection problem. This time, a probabilistic framework is considered to model the vectors, assumed to be distributed from a specifc Markov Random Field. In the considered modeling, the graph underlying the data is allowed to evolve in time and a change-point is actually detected whenever this graph changes significantly
Do, Van Long. "Sequential detection and isolation of cyber-physical attacks on SCADA systems". Thesis, Troyes, 2015. http://www.theses.fr/2015TROY0032/document.
Texto completoThis PhD thesis is registered in the framework of the project “SCALA” which received financial support through the program ANR-11-SECU-0005. Its ultimate objective involves the on-line monitoring of Supervisory Control And Data Acquisition (SCADA) systems against cyber-physical attacks. The problem is formulated as the sequential detection and isolation of transient signals in stochastic-dynamical systems in the presence of unknown system states and random noises. It is solved by using the analytical redundancy approach consisting of two steps: residual generation and residual evaluation. The residuals are firstly generated by both Kalman filter and parity space approaches. They are then evaluated by using sequential analysis techniques taking into account certain criteria of optimality. However, these classical criteria are not adequate for the surveillance of safety-critical infrastructures. For such applications, it is suggested to minimize the worst-case probability of missed detection subject to acceptable levels on the worst-case probability of false alarm and false isolation. For the detection task, the optimization problem is formulated and solved in both scenarios: exactly and partially known parameters. The sub-optimal tests are obtained and their statistical properties are investigated. Preliminary results for the isolation task are also obtained. The proposed algorithms are applied to the detection and isolation of malicious attacks on a simple SCADA water network
Davis, Elizabeth H. "Detection of rupture-repair sequences in patterns of alliance development the effects of client vs. therapist raters and therapist training status /". Ohio : Ohio University, 2005. http://www.ohiolink.edu/etd/view.cgi?ohiou1133405084.
Texto completoDavis, Elizabeth Helen. "Detection of Rupture-Repair Sequences in Patterns of Alliance Development: The Effects of Client vs. Therapist Raters and Therapist Training Status". Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1133405084.
Texto completoAllab, Nedjmeddine. "Détection d'anomalies et de ruptures dans les séries temporelles. Applications à la gestion de production de l'électricité". Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066658.
Texto completoContinental is the main tool that edf uses for the long-term management of electricity. It elaborates the strategy exploitation of the electrical parc made up by power plants distributed all over europe. the tool simulates for each zone and each scenario several variables, such as the electricity demand, the generated quantity as well as the related costs. our works aim to provide methods to analyse the data of electricity production in order to ease their discovery and synthesis. we get a set of problmatics from the users of continental that we tent to solve through techniques of outliers and changepoints detection in time series
Libros sobre el tema "Rupture detection"
Lelic, Simon. Rupture. Oxford: ISIS Large Print, 2011.
Buscar texto completoCoben, Harlan. Rupture de contrat. Paris: Le Grand livre du mois, 2003.
Buscar texto completoCarpenter, Philip, Morgan Henrie y R. Edward Nicholas. Pipeline Leak Detection Handbook. Elsevier Science & Technology Books, 2016.
Buscar texto completoPipeline Leak Detection Handbook. Elsevier Science & Technology Books, 2016.
Buscar texto completoDeBruhl, Nanette D. y Nazanin Yaghmai. Breast Implants. Editado por Christoph I. Lee, Constance D. Lehman y Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0060.
Texto completoDetecting Chinese Modernities: Rupture and Continuity in Modern Chinese Detective Fiction. BRILL, 2020.
Buscar texto completoRupture. Gallimard Education, 2012.
Buscar texto completoLelic, Simon. Rupture. Picador, 2010.
Buscar texto completoRupture. Picador, 2016.
Buscar texto completoLelic, Simon. Rupture. Picador, 2010.
Buscar texto completoCapítulos de libros sobre el tema "Rupture detection"
Jain, Kartik. "CADA Challenge: Rupture Risk Assessment Using Computational Fluid Dynamics". En Cerebral Aneurysm Detection, 75–86. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_8.
Texto completoIvantsits, Matthias, Leonid Goubergrits, Jan Brüning, Andreas Spuler y Anja Hennemuth. "Intracranial Aneurysm Rupture Prediction with Computational Fluid Dynamics Point Clouds". En Cerebral Aneurysm Detection, 104–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_11.
Texto completoIvantsits, Matthias, Markus Huellebrand, Sebastian Kelle, Titus Kuehne y Anja Hennemuth. "Intracranial Aneurysm Rupture Risk Estimation Utilizing Vessel-Graphs and Machine Learning". En Cerebral Aneurysm Detection, 93–103. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_10.
Texto completoAzaïs, Romain, Anne Gégout-Petit y Florine Greciet. "Rupture Detection in Fatigue Crack Propagation". En Statistical Inference for Piecewise-deterministic Markov Processes, 173–207. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119507338.ch6.
Texto completoLiu, Yanfei, Yunqiao Yang, Yi Lin, Yuexiang Li, Dong Wei, Kai Ma y Yefeng Zheng. "Cerebral Aneurysm Rupture Risk Estimation Using XGBoost and Fully Connected Neural Network". En Cerebral Aneurysm Detection, 87–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_9.
Texto completoDoyle, Barry J., Timothy M. McGloughlin, Eamon G. Kavanagh y Peter R. Hoskins. "From Detection to Rupture: A Serial Computational Fluid Dynamics Case Study of a Rapidly Expanding, Patient-Specific, Ruptured Abdominal Aortic Aneurysm". En Computational Biomechanics for Medicine, 53–68. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0745-8_5.
Texto completoYang, S. W., A. Widodo, W. Caesarendra, J. S. Oh, M. C. Shim, S. J. Kim, B. S. Yang y W. H. Lee. "Support vector machine and discrete wavelet transform method for strip rupture detection based on transient current signal". En Engineering Asset Lifecycle Management, 671–78. London: Springer London, 2010. http://dx.doi.org/10.1007/978-0-85729-320-6_78.
Texto completoSchaefer, Pamela W. y Myriam Edjlali. "Nontraumatic Intracranial Hemorrhage". En IDKD Springer Series, 49–68. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-50675-8_5.
Texto completoAndrianov, Ivan K., M. Kara Balli, Miron S. Grinkrug y Nikita A. Novgorodov. "Finite Element Calculation of the Limiting Pressure for Rupture of Capsules with an Active Substance in the Crack Detection System of Gas Turbine Blades". En Software Engineering Research in System Science, 757–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35311-6_72.
Texto completoHughes, J. R. y S. F. Byrne. "Detection of posterior ruptures in opaque media". En Documenta Ophthalmologica Proceedings Series, 333–42. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3315-6_54.
Texto completoActas de conferencias sobre el tema "Rupture detection"
Bowles, Edgar B., Thomas B. Morrow, Cecil R. Sparks y John G. Gregor. "Gas Pipeline Rupture Detection and Control". En 1996 1st International Pipeline Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/ipc1996-1924.
Texto completoDi Blasi, Martin y Zhan Li. "Pipeline Rupture Detection Based on Machine Learning and Pattern Recognition". En 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64471.
Texto completoSmith, Joel, Jaehee Chae, Shawn Learn, Ron Hugo y Simon Park. "Pipeline Rupture Detection Using Real-Time Transient Modelling and Convolutional Neural Networks". En 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78426.
Texto completoKang, Ju Seok, Nahian Rahman, Sung Min Yoon, Gm Gang Cha y Min Cheol Lee. "Organ rupture detection algorithm of surgical robot". En 2014 14th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2014. http://dx.doi.org/10.1109/iccas.2014.6987884.
Texto completoNanditha, Hg, Sanjana Sampige, S. N. Shreya, Samyutha Bhaskar y G. N. Anusha. "Glove Rupture Detection System using skin impedance." En 2023 International Conference on the Confluence of Advancements in Robotics, Vision and Interdisciplinary Technology Management (IC-RVITM). IEEE, 2023. http://dx.doi.org/10.1109/ic-rvitm60032.2023.10434990.
Texto completoMu, Xiuping. "A New Approach to Monitoring Rupture Disc Operation". En ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-86369.
Texto completoCLAUSS, FELIX, MARK ALEXANDER AHRENS y PETER MARK. "DAMAGE WITHOUT INDICATION—DETECTION OF TENDON RUPTURE USING CODA WAVE INTERFEROMETRY". En Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36263.
Texto completoMacDonald, Christopher, Michael Yang, Shawn Learn, Ron Hugo y Simon Park. "Liquid Pipeline Rupture Detection Using Multiple Artificial Intelligence Classifiers During Steady-State and Transient Operations". En 2020 13th International Pipeline Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/ipc2020-9237.
Texto completoMamou, J., A. Y. Ammi, L. Bridal, G. I. Wang y W. D. O�Brien Jr. "2D-2 Automatic Detection of Ultrasound Contrast Microbubble Shell Rupture". En 2006 IEEE Ultrasonics Symposium. IEEE, 2006. http://dx.doi.org/10.1109/ultsym.2006.87.
Texto completoRudland, David L. "Predicting Pipe Rupture Frequencies Using xLPR". En ASME 2020 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/pvp2020-21080.
Texto completoInformes sobre el tema "Rupture detection"
Gangrao, Hota V. S., Udaya B. Halabe, John Zondlo, Mark Skidmore, Ben Imes, Jonas Kavi, Andrew Pacifico, Ronald Alexander, Andrew Cvetnick y Patrick Sisler. DTPH56-16-HCAP-02 Glass-Polymer Composite High Pressure Pipes and Joints-Design, Manufacture. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), septiembre de 2018. http://dx.doi.org/10.55274/r0011841.
Texto completoMcCallum y Richard. L52247 Human Factors Analysis of Leak Detection and Response Scoping Study. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), febrero de 2004. http://dx.doi.org/10.55274/r0010251.
Texto completoBarton. L51695 Development of Inspection Vehicle to Detect SCC in Natural Gas Lines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), noviembre de 1993. http://dx.doi.org/10.55274/r0010627.
Texto completoBarton, Card y Pope. L51637 Development of an Ultrasonic Stress Corrosion Cracking Detection Vehicle. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), noviembre de 1990. http://dx.doi.org/10.55274/r0010608.
Texto completoWright, Louise y Louise Crocker. PR-670-183826-R03 Extended Evaluation of LSM-Magnetostrictive Pipe Models. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), mayo de 2021. http://dx.doi.org/10.55274/r0012097.
Texto completoBruce. L51642 Field Nondestructive Examination of ERW Pipe Seams. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), junio de 1991. http://dx.doi.org/10.55274/r0010587.
Texto completoFinch, Graeme y Stuart Harmon. PR-670-183826-R01 Assessment of Science Behind LSM for Pipeline Integrity. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), septiembre de 2020. http://dx.doi.org/10.55274/r0011803.
Texto completoFinch, Graeme y Stuart Harmon. PR-670-183826-R02 Extended Evaluation of LSM - Magnetic Measurements of Corrosion Flaws. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), noviembre de 2021. http://dx.doi.org/10.55274/r0012189.
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