Thematische Bibliographien / Car identification

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Bücher
  4. Buchteile
  5. Konferenzberichte
  6. Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Car identification“

Autor: Grafiati
Veröffentlicht am 28. Juni 2021
Zuletzt aktualisiert am 1. Februar 2022

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Zeitschriftenartikel zum Thema "Car identification"

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Rutten, Michael J., Kathy D. Bacon, Katie L. Marlink, Mark Stoney, Camie L. Meichsner, Fred P. Lee, Susan A. Hobson et al. „Identification of a functional Ca2+-sensing receptor in normal human gastric mucous epithelial cells“. American Journal of Physiology-Gastrointestinal and Liver Physiology 277, Nr. 3 (01.09.1999): G662—G670. http://dx.doi.org/10.1152/ajpgi.1999.277.3.g662.

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The purpose of the present study was to determine whether human gastric mucous epithelial cells express a functional Ca2+-sensing receptor (CaR). Human gastric mucous epithelial cells were isolated from surgical tissues and cultured on glass coverslips, plastic dishes, or porous membrane filters. Cell growth was assessed by the MTT assay, CaR localization was detected by immunohistochemistry and confocal microscopy, CaR protein expression was assessed by Western immunoblotting, and intracellular Ca2+ concentration ([Ca2+]i) was determined by fura 2 spectrofluorometry. In paraffin sections of whole stomach, we found strong CaR immunohistochemical staining at the basolateral membrane, with weak CaR-staining at the apical membrane in mucous epithelial cells. Confocal microscopy of human gastric mucous epithelial cell cultures showed abundant CaR immunofluorescence at the basolateral membrane and little to no CaR immunoreactivity at the apical membrane. Western immunoblot detection of CaR protein in cell culture lysates showed two significant immunoreactive bands of 140 and 120 kDa. Addition of extracellular Ca2+ to preconfluent cultures of human gastric mucous epithelial cells produced a significant proliferative response. Changes in [Ca2+]iwere also observed in response to graded doses of extracellular Ca2+ and Gd3+. The phospholipase C inhibitor U-73122 specifically inhibited Gd3+-induced changes in [Ca2+]iin the gastric mucous epithelial cell cultures. In conclusion, we have identified the localization of a functional CaR in human gastric mucous epithelial cells.
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Cima, Robert R., Ivan Cheng, Mary E. Klingensmith, Naibedya Chattopadhyay, Olga Kifor, Steven C. Hebert, Edward M. Brown und David I. Soybel. „Identification and functional assay of an extracellular calcium-sensing receptor in Necturusgastric mucosa“. American Journal of Physiology-Gastrointestinal and Liver Physiology 273, Nr. 5 (01.11.1997): G1051—G1060. http://dx.doi.org/10.1152/ajpgi.1997.273.5.g1051.

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In mammals and amphibians, increases in extracellular Ca2+ can activate bicarbonate secretion and other protective functions of gastric mucosa. We hypothesized that the recently cloned extracellular Ca2+-sensing receptor (CaR) is functioning in the gastric mucosa. In Necturus maculosus gastric mucosa, reverse transcription-polymerase chain reaction using primers based on previously cloned CaR sequences amplified a 326-bp DNA fragment that had 84% nucleotide sequence identity with the rat kidney CaR. Immunohistochemical localization of the CaR using specific anti-CaR antiserum revealed its presence on the basal aspect of gastric epithelial cells. In microelectrode studies of Necturus antral mucosa, exposure to elevated Ca2+ (4.8 mM) and the CaR agonists NPS-467 and neomycin sulfate resulted in significant hyperpolarizations of basal membrane electrical potentials and increases in apical-to-basal membrane resistance ratios. Circuit analysis revealed that these changes reflected specific decreases in basolateral membrane resistance. Inhibition of prostaglandin synthesis using indomethacin significantly attenuated these effects. We conclude that the CaR is present and functioning in Necturus gastric antrum.
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Venture, Gentiane, Wisama Khalil, Maxime Gautier und Philippe Bodson. „Dynamic Identification of a Car“. IFAC Proceedings Volumes 37, Nr. 22 (April 2004): 733–38. http://dx.doi.org/10.1016/s1474-6670(17)30431-7.

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Mahmood, Sanner H., Oulla G. Hassan, Ayad M. Kwad und Safa F. Abass. „Auto Opening Door and Car Identification“. Journal of Computer and Communications 04, Nr. 15 (2016): 132–41. http://dx.doi.org/10.4236/jcc.2016.415013.

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Venture, Gentiane, Maxime Gautier, Wisama Khalil und Philippe Bodson. „Parametric identification of the car dynamics“. IFAC Proceedings Volumes 36, Nr. 16 (September 2003): 285–90. http://dx.doi.org/10.1016/s1474-6670(17)34775-4.

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Russo, Michele, Riccardo Russo und Agsotino Volpe. „Car Parameters Identification by Handling Manoeuvres“. Vehicle System Dynamics 34, Nr. 6 (29.12.2000): 423–36. http://dx.doi.org/10.1076/vesd.34.6.423.2053.

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Sugarindra, Muchamad, und Rian Notia Pratama. „Kano Model for Identification Car Modification Features of Mobile Application“. MATEC Web of Conferences 221 (2018): 03003. http://dx.doi.org/10.1051/matecconf/201822103003.

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Modification was an activity to replace the object more attractive especially car modification. Lately, car modification become the one of the promising business since that were providing high profits. The owner of car look for the accessories for their car frequently. Then, the owner of car modification should increasing their facility to make the consumer satisfied. Furthermore, if the consumer satisfied with the service than it provided high profit. For increasing high profit than the owner of car modification should made the innovation. One of the innovation was car modification with mobile application (apps.) by Kano model. The aims of this study was to identify the features in car modification using Kano model. Kano model used to identify consumer needs that divided into 3 category. There are must be, one dimensional and attractive. The result from open questionnaire would be proceed by Kano model. This study revealed that feature of selection car body colour, feature of selection lamp model and feature engine cap model of into one dimensional category, feature of selection car velg, and matching the tire into must be category and feature of selection cutting sticker, and selection of bumper model into attractive category, and priority to develop are feature of selection car body colour, cutting sticker and selection of bumper model. This category should be the reference to be the resource for car modification apps.
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Tawfeek, M., S. Shedid, I. El-Sherif und Y. Hendawy. „INTEGRATION OF CAR SECURITY LEVELS USING TRANSPONDER KEY: DOUBLE IDENTIFICATION CAR CODE“. International Conference on Applied Mechanics and Mechanical Engineering 15, Nr. 15 (01.05.2012): 1–9. http://dx.doi.org/10.21608/amme.2012.37255.

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Kurup, Nithin. „Car Theft Identification, Tracking and Control System“. IOSR Journal of Computer Engineering 4, Nr. 2 (2012): 31–34. http://dx.doi.org/10.9790/0661-0423134.

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Venture, Gentiane, Wisama Khalil, Maxime Gautier und Philippe Bodson. „DYNAMIC MODELLING AND IDENTIFICATION OF A CAR“. IFAC Proceedings Volumes 35, Nr. 1 (2002): 181–86. http://dx.doi.org/10.3182/20020721-6-es-1901.01498.

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Dissertationen zum Thema "Car identification"

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Miwa, Tomio, Takaaki Sakai und Taka Morikawa. „Route Identification and Travel Time Prediction Using Probe-Car Data“. ITS Japan, 2004. http://hdl.handle.net/2237/10030.

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Jolicoeur, Marie-Pierre. „Model identification of a car suspension testbed for robust vibration control“. Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=98974.

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Road irregularities are a source of structure-borne noise in a car cabin. An active suspension using an Hinfinity robust feedback controller is designed to reduce this vibration-induced noise. To define the control law on this suspension, a quarter-car suspension is first modeled through its resonance modes. Frequency responses are extracted from experimental measurements which are then curve-fitted to obtain the nominal model of the suspension and its parametric uncertainty. The vibration-induced noise in the frequency range 60-250 Hz is then reduced using robust feedback controllers. An Hinfinity controller and two mu-synthesis controllers are designed and compared. Simulation of these controllers using Simulink result in a reduction in vibration at resonance peaks of up to 31 dB.
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Ehlert, Anett. „The identification of some requirements for an improved car following model“. Thesis, University of Newcastle Upon Tyne, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.399291.

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Tran, Michael. „Neural network identification of quarter-car passive and active suspension systems“. Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-09292009-020158/.

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Benod, Cindy. „Identification de ligands pour les récepteurs nucléaires humains PXR (NR112) et CAR (NR113)“. Montpellier 1, 2007. http://www.theses.fr/2007MON13504.

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Les récepteurs nucléaires humains PXR (Pregnane X Receptor, NR1I2) et CAR (Constitutive Androstane Receptor, NR1I3) modulent l'expression de plusieurs familles de gènes impliquées dans des voies de détoxification de l'organisme. Ainsi, des agonistes affins et spécifiques de ces deux récepteurs pourraient être utilisés pour protéger l’organisme des effets néfastes dus à l’accumulation d’agents toxiques endogènes et exogènes. Par ailleurs, des antagonistes de PXR et CAR permettraient de traiter certains cancers ou d’éviter des interactions médicamenteuses. Ce projet a donc consisté à mettre en place une stratégie allant de l’identification de ces ligands par une méthode de conception rationnelle basée sur la structure 3D de PXR et CAR, à leur caractérisation biologique, voire à leur optimisation moléculaire pour améliorer leur activité. Ce travail a ainsi permis l’identification d’un agoniste et de 9 antagonistes pour CAR. Pour PXR, un agoniste doté d’une forte activité a été identifié.
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Kumstát, Petr. „Řízení rizik ve společnosti AT CAR, s.r.o“. Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318553.

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Risk management in company AT CAR, s.r.o. with focus on its branch Brno is the main topic of this thesis. As for the risk management itself, the most important tasks are identification, analysis and reducing the possible risks. These processes are described and discussed in the theoretical part of the thesis, while it also introduces all important terms related to this topic. In the analytical part, the risks are identified using appropriate methods such as SLEPTE analysis, Porter’s Five Forces and 7S model. The risks identified are thereafter evaluated using the scoring method. In the last part, recommendations and measures for reducing the risk are presented.
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Andersen, Erik. „Multibody Dynamics Modeling and System Identification for a Quarter-Car Test Rig with McPherson Strut Suspension“. Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/33197.

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For controller design, design of experiments, and other dynamic simulation purposes there is a need to be able to predict the dynamic response and joint reaction forces of a quarter-car suspension. This need is addressed by this study through development and system identification of both a linear and a non-linear multibody dynamics McPherson strut quarter-car suspension model. Both models are developed using a method customary to multibody dynamics so that the same numerical integrator can be used to compare their respective performances. This method involves using the Lagrange multiplier form of the constrained equations of motion to assemble a set of differential algebraic equations that characterize each modelâ s dynamic response. The response of these models to a band-limited random tire displacement time array is then simulated using a Hilber-Hughes-Taylor integrator. The models are constructed to match the dynamic response of a state-of-the-art quarter-car test rig that was designed, constructed, and installed at the Institute for Advanced Learning and Research (IALR) for the Performance Engineering Research Lab (PERL). Attached to the experimental quarter-car rig was the front left McPherson strut suspension from a 2004 Porsche 996 Grand American Cup GS Class race car. This quarter-car rig facilitated acquisition of the experimental reference data to which the simulated data is compared. After developing these models their optimal parameters are obtained by performing system identification. The performance of both models using their respective optimal parameters is presented and discussed in the context of the basic linearity of the experimental suspension. Additionally, a method for estimating the loads applied to the experimental quarter-car rig bearings is developed. Finally, conclusions and recommendations for future research and applications are presented.
Master of Science
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Banik, Prakriti. „Vision and Radar Fusion for Identification of Vehicles in Traffic“. Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/55121.

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This report presents a method for estimating the presence and duration of preceding and lead vehicle in front of a motorcycle using an object detection algorithm guided by radar data. The video and radar data were collected as part of a large transportation project. The data are recorded by the ego vehicle during a trip while in a naturalistic research study. The goal is to validate objects detected by radar using vision, to identify moving preceding vehicles and the lead vehicle. The proposed approach takes advantage of radar data in locating the vehicles and other targets and then validates the targets as vehicles using Dual-Tree Branch-and-Bound (Kokkinos, 2011) object detection algorithm. Localization, detection and tracking took 0.0385 seconds per frame on average. Precision and recall of lead vehicle detection is 98.61% and 90.53% respectively. The algorithm presents a comprehensive approach to localize target vehicles in video. The radar object coordinates are mapped on the video frame using perspective projection map- ping. Then persistent radar objects are determined by analyzing their trajectory on video frames. When a radar object appears for three consecutive frames, its called a persistent object. A region of interest (ROI) around the persistent radar object is cropped from the frame, and passed to the object detection algorithm to determine if the persistent object is a car. Once a car is detected the validation of the radar object is complete. We track the detected car in the following frames and refresh the detection after every fourteen frames. The car detection algorithm runs whenever a new persistent radar object is introduced. After validating radar objects, at each timestamp, the lead vehicle is determined using radar object's forward and lateral distance. The time from detecting a lead vehicle to the time when the vehicle disappears or another vehicle becomes lead vehicle, is recorded to get the epochs of following driving mode for that lead vehicle. Finally, the detection result is integrated with MATLAB lane detection system to make a complete system for lead vehicle detection and tracking. The video of interest has 240x720 resolution and approximately 15 frames per second. The car detection algorithm takes 0.1960 seconds on average to detect one car in a machine with Windows operating system and 4GB RAM. But as the detection algorithm is not run for each frame it saves time. Since no annotated motorcycle video dataset is publicly available, two videos of 52 seconds and 26 seconds were manually annotated to test the performance of the approach. The current approach works almost at real time. The algorithm has been tested and results have been reported on 1 video.
Master of Science
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Breuker, Cyril. „Etude des xénorécepteurs CAR (NR1I3) et PXR (NR1I2) : identification d’un nouveau gène cible de CAR (SPOT14) et d’une nouvelle isoforme de PXR (PXR-small) dans l'hépatocyte humain“. Thesis, Montpellier 1, 2010. http://www.theses.fr/2010MON13522.

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CAR (Constitutive Androstane Receptor, NR1I3) et PXR (Pregnane X Receptor, NR1I2) sont deux récepteurs nucléaires dédiés à la reconna issance et à l'élimination de molécules lipophiles potentiellement toxiques pour l'organisme. Ces facteurs de transcription peuvent être activés par des ligands d'origines et de structures diverses (médicaments, polluants environnementaux, produits de l'alimentation et de phytothérapies). L'activation de ces récepteurs entraîne l'expression des gènes majeurs de la fonction de détoxication entéro-hépatique (CYP450, transférases, transporteurs) permettant l'élimination de ces toxiques. Dans ce travail, nous avons dans un premier temps 1) montré que CAR contrôle l'expression de Spot14, une protéine pro-lipogénique, et 2) nous avons identifié une nouvelle isoforme de PXR (PXR-small) codant uniquement pour le domaine de liaison des ligands de PXR. Nous avons pu déterminer les origines de transcription par 5'-RACE PCR et montrer que PXR-small représente environ 10% de l'ensemble des transcrits de PXR dans le tissu hépatique sain par une approche de PCR qua ntitative. Nous avons pu détecter sa présence par western-blot sur des extraits de protéines nucléaires issus de tissus hépatiques et de lignées cellulaires hépatiques. Par des expériences de gel retard, nous avons observé que cette nouvelle isoforme tronquée, qui ne code que pour le LBD de PXR, ne peut pas se lier à l'ADN. Des expériences de gènes rapporteurs suggèrent que cette isoforme se comporte comme un dominant négatif de PXR. Enfin, la présence d'un ilot CpG situé juste en amont de PXR-small suggère que cette nouvelle isoforme pourrait être régulée épigénétiquement par méthylation, notamment dans les cellules tumorales
CAR (Constitutive Androstane Receptor, NR1I3) and PXR (Pregnane X Receptor, NR1I2) are two nuclear receptors devoted to the recognition and elimination of lipohilic molecules potentially toxic to the body.These transcription factors can be activated by ligands of different origins and structures (drugs, environmental pollutants, food products and herbal medicine...). The activation of these receptors leads to the expression of major genes of the detoxification process (CYP450, transferases, transporters) leading to the elimination of these toxics. In this work, we 1) showed that Spot14, a pro-lipogenic protein, is a target gene of CAR, then 2) we identified a novel isoform of PXR (PXR-small), coding only the ligand binding domain of PXR. By using 5'-RACE PXR, we established the origins of transcription of PXR-small and by quantitative PCR we observed that PXR-small represents about 10% of all PXR transcripts in human liver. By using western blo t, we detect its presence on nuclear protein extracts from liver tissues and hepatic cell lines. In Electromobility shift essays experiments, we observed that PXR-small cannot bind to DNA, while reporter essay experiments suggest that this isoform acts as a dominant negative of PXR. Finally, the presence of a CpG island just upstream of PXR-small suggests that this novel isoform might be regulated epigenetically by methylation, more particularly in tumor cells
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Koornneef, Maarten, Claire M. Bernaards, Hedwig Hofstetter und Ingrid J. M. Hendriksen. „Business car owners are less physically active than other adults: A cross-sectional study“. Elsevier, 2017. https://publish.fid-move.qucosa.de/id/qucosa%3A72782.

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Active transport contributes to increased daily physical activity (PA). Car ownership is associated with less frequent active transport and less PA. For business car ownership this relation is unknown. Therefore, we explored whether business car owners and their adult household members comply less with the Dutch moderate to vigorous physical activity (MVPA) guideline and are more sedentary than private car owners and persons without a car. From October 2011 to September 2012 questions about use and availability of cars in the household were included in the survey Injuries and Physical Activity in the Netherlands. Multiple linear regression was used to compare six mutual exclusive groups of ownership and availability of (business and/or private) cars in the household. Business car owners complied less (15.8 percent points) with the MVPA guideline than the other respondents. They also reported 1.5 h more sitting time during workdays than the other respondents, but after adjusting for covariates, this difference was no longer significant. We concluded that owners of a business car in the Netherlands are at higher risk of not complying with the MVPA guideline and tend to spend more hours sitting during workdays than other adults. Further research in this group, e.g. with objective instruments to measure physical activity and sedentary behavior, is recommended. Policy makers on transport and fiscal arrangements, employers, employees, occupational health professionals and car lease companies should be aware of this possible health risk.
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Bücher zum Thema "Car identification"

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A, Clark John. HO slot car identification and price guide. Gas City, IN: L-W Book Sales, 1995.

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Collingwood, Larry. What car would you drive if--?: A fun quiz book about car models and their manufacturers. [U.S.?]: Xlibris Corp, 2010.

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American car spotter's guide, 1981-1990. Osceola, WI, USA: Motorbooks International, 1990.

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Monstrous American car spotter's guide 1920-1980. Osceola, Wis., USA: Motorbooks International, 1986.

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Inc, Krause Publications, Hrsg. Ultimate car spotter's guide, 1946-1969. Iola, WI: Krause Publications, 1998.

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Dana, Johnson. Toy car collector's guide: Identification and values for diecast, white metal, other automotive toys & models. Paducah, Ky: Collector Books, 2002.

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Hostetler, Mark E. That gunk on your car: A unique guide to insects of North America. Berkeley, Calif: Ten Speed Press, 1997.

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Havert, Bill. Nature guide to the mountains of Southern California by car & on foot. Idyllwild, CA: Earth Trails Publications, 1996.

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Leopard geckos: Identification, care & breeding. Neptune City, N.J: T.F.H. Publications, 1994.

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Edgar, Jim. Illinois disabled persons identification card. [Springfield, Ill.]: Jim Edgar, Secretary of State, 1986.

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Buchteile zum Thema "Car identification"

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Schütz, Thomas, Hans-Joachim Kretschmann und Dieter Müller. „Automated Identification of Neuroanatomical Structures in CT- and MR-Images“. In CAR’89 Computer Assisted Radiology / Computergestützte Radiologie, 287–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-52311-3_51.

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DeLucia, Diana C., und John K. Lee. „Identification of Cell Surface Targets for CAR T Cell Immunotherapy“. In Methods in Molecular Biology, 45–54. New York, NY: Springer US, 2019. http://dx.doi.org/10.1007/978-1-0716-0203-4_2.

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Hou, Yanfang, Guohua Han, Yaozhen Zhao und Xueying Xu. „Disturbing Noise Identification and Sound Quality Research on Car Generator“. In Lecture Notes in Electrical Engineering, 535–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33832-8_41.

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Muresan, Vlad, Valentin Sita, Iulia Clitan und Adrian Barstan. „Identification and Control of a Car Speed Dynamics Using Artificial Intelligence“. In Mining Intelligence and Knowledge Exploration, 189–204. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05918-7_17.

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Lettieri, Antonio, und Carmine Maria Pappalardo. „Experimental Identification of a Car Dynamic Model Using the Numerical Algorithms for Subspace State-Space System Identification“. In Advances in Design, Simulation and Manufacturing III, 14–23. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50491-5_2.

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Shile, P. E., M. P. Chwialkowski, D. Pfeifer, R. W. Parkey und R. M. Peshock. „Automated Identification of the Spine in Magnetic Resonance Images: A Reference Point for Automated Processing“. In CAR’89 Computer Assisted Radiology / Computergestützte Radiologie, 678–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-52311-3_120.

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Mesbah, N. F., und S. M. Yusof. „Systematic Way for Problem Identification of Car Braking System by Using TRIZ“. In The Malaysia-Japan Model on Technology Partnership, 147–53. Tokyo: Springer Japan, 2014. http://dx.doi.org/10.1007/978-4-431-54439-5_13.

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Rundo, Francesco, Francesca Trenta, Roberto Leotta, Concetto Spampinato, Vincenzo Piuri, Sabrina Conoci, Ruggero Donida Labati, Fabio Scotti und Sebastiano Battiato. „Advanced Temporal Dilated Convolutional Neural Network for a Robust Car Driver Identification“. In Pattern Recognition. ICPR International Workshops and Challenges, 184–99. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68793-9_13.

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Puneet, N. P., Abhinandan Hegale, Hemantha Kumar und K. V. Gangadharan. „Optimal Parameters Identification of Quarter Car Simulink Model for Better Ride Comfort and Road Holding“. In Recent Advances in Computational Mechanics and Simulations, 623–36. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8315-5_53.

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Roseiro, Luis, Carlos Alcobia, Pedro Ferreira, Abderrahmane Baïri, Najib Laraqi und Nacim Alilat. „Identification of the Forces in the Suspension System of a Race Car Using Artificial Neural Networks“. In Intelligent Systems, Control and Automation: Science and Engineering, 469–77. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4722-7_44.

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Konferenzberichte zum Thema "Car identification"

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Hammar, Karima, Tounsia Djamah und Maamar Bettayeb. „Fractional Hammerstein CAR system identification“. In 2017 6th International Conference on Systems and Control (ICSC). IEEE, 2017. http://dx.doi.org/10.1109/icosc.2017.7958743.

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Dirschmid, Werner. „Parameter Identification for Noise Prediction in Car Structures“. In Passenger Car Conference & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1990. http://dx.doi.org/10.4271/901754.

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Ambrosio-Lázaro, Roberto C., Luis Alberto Quezada-Téllez und Oscar A. Rosas-Jaimes. „Parameter Identification on Helly’s Car-Following Model“. In International Conference of Control, Dynamic Systems, and Robotics. Avestia Publishing, 2018. http://dx.doi.org/10.11159/cdsr18.107.

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Ueno, Kazuki, und Jun'ichi Yamaguchi. „Passing car identification using Hough data verification“. In 2013 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2013). IEEE, 2013. http://dx.doi.org/10.1109/fcv.2013.6485484.

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Jazayeri, A., H. Cai, J. Y. Zheng und M. Tuceryan. „Motion based vehicle identification in car video“. In 2010 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2010. http://dx.doi.org/10.1109/ivs.2010.5548082.

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Martinelli, Fabio, Francesco Mercaldo, Vittoria Nardone und Antonella Santone. „Car hacking identification through fuzzy logic algorithms“. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015464.

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Gallo, Gionatan, Mario Luca Bernardi, Marta Cimitile und Pietro Ducange. „An Explainable Approach for Car Driver Identification“. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2021. http://dx.doi.org/10.1109/fuzz45933.2021.9494566.

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Dai Qiang Wang, ShiYou Gao, Yu Qing Chen, Yi Wang und Qiao Liu. „Intelligent Control system based on CAN-bus for car doors and windows“. In 2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication (2009 ASID). IEEE, 2009. http://dx.doi.org/10.1109/icasid.2009.5276906.

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Venture, Gentiane, Philippe Bodson, Maxime Gautier und Wisama Khalil. „Identification of the Dynamic Parameters of a Car“. In SAE 2003 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2003. http://dx.doi.org/10.4271/2003-01-1283.

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Lahalle, E., D. Poulton und J. Oksman. „CAR identification from nonuniformly sampled values using LMS“. In 48th Midwest Symposium on Circuits and Systems, 2005. IEEE, 2005. http://dx.doi.org/10.1109/mwscas.2005.1594073.

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Berichte der Organisationen zum Thema "Car identification"

1

Utsugi, Akio, und Motoyuki Akamatsu. Analysis of Car-Following Behavior Using Dynamic Probabilistic Models~Identification of Driving Mode Transition Using Dynamic Bayesian Networks. Warrendale, PA: SAE International, Mai 2005. http://dx.doi.org/10.4271/2005-08-0241.

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Taylor, James S., und Mary C. Hulgan. Electro-Optic Identification Research Program: Computer Aided Identification (CAI) and Automatic Target Recognition (ATR). Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada624974.

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Guyette, Francis X., David Hostler, Juan C. Puyana, John S. Cole, Michael R. Pinsky und Brian Suffoletto. Early Identification of Circulatory Shock in Critical Care Transport. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada494638.

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Dy, Sydney M., Julie M. Waldfogel, Danetta H. Sloan, Valerie Cotter, Susan Hannum, JaAlah-Ai Heughan, Linda Chyr et al. Integrating Palliative Care in Ambulatory Care of Noncancer Serious Chronic Illness: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), Februar 2020. http://dx.doi.org/10.23970/ahrqepccer237.

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Objectives. To evaluate availability, effectiveness, and implementation of interventions for integrating palliative care into ambulatory care for U.S.-based adults with serious life-threatening chronic illness or conditions other than cancer and their caregivers We evaluated interventions addressing identification of patients, patient and caregiver education, shared decision-making tools, clinician education, and models of care. Data sources. We searched key U.S. national websites (March 2020) and PubMed®, CINAHL®, and the Cochrane Central Register of Controlled Trials (through May 2020). We also engaged Key Informants. Review methods. We completed a mixed-methods review; we sought, synthesized, and integrated Web resources; quantitative, qualitative and mixed-methods studies; and input from patient/caregiver and clinician/stakeholder Key Informants. Two reviewers screened websites and search results, abstracted data, assessed risk of bias or study quality, and graded strength of evidence (SOE) for key outcomes: health-related quality of life, patient overall symptom burden, patient depressive symptom scores, patient and caregiver satisfaction, and advance directive documentation. We performed meta-analyses when appropriate. Results. We included 46 Web resources, 20 quantitative effectiveness studies, and 16 qualitative implementation studies across primary care and specialty populations. Various prediction models, tools, and triggers to identify patients are available, but none were evaluated for effectiveness or implementation. Numerous patient and caregiver education tools are available, but none were evaluated for effectiveness or implementation. All of the shared decision-making tools addressed advance care planning; these tools may increase patient satisfaction and advance directive documentation compared with usual care (SOE: low). Patients and caregivers prefer advance care planning discussions grounded in patient and caregiver experiences with individualized timing. Although numerous education and training resources for nonpalliative care clinicians are available, we were unable to draw conclusions about implementation, and none have been evaluated for effectiveness. The models evaluated for integrating palliative care were not more effective than usual care for improving health-related quality of life or patient depressive symptom scores (SOE: moderate) and may have little to no effect on increasing patient satisfaction or decreasing overall symptom burden (SOE: low), but models for integrating palliative care were effective for increasing advance directive documentation (SOE: moderate). Multimodal interventions may have little to no effect on increasing advance directive documentation (SOE: low) and other graded outcomes were not assessed. For utilization, models for integrating palliative care were not found to be more effective than usual care for decreasing hospitalizations; we were unable to draw conclusions about most other aspects of utilization or cost and resource use. We were unable to draw conclusions about caregiver satisfaction or specific characteristics of models for integrating palliative care. Patient preferences for appropriate timing of palliative care varied; costs, additional visits, and travel were seen as barriers to implementation. Conclusions. For integrating palliative care into ambulatory care for serious illness and conditions other than cancer, advance care planning shared decision-making tools and palliative care models were the most widely evaluated interventions and may be effective for improving only a few outcomes. More research is needed, particularly on identification of patients for these interventions; education for patients, caregivers, and clinicians; shared decision-making tools beyond advance care planning and advance directive completion; and specific components, characteristics, and implementation factors in models for integrating palliative care into ambulatory care.
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Durik, Amanda, Steven McGee, Linda Huber und Jennifer Duck. The Cat is Alive and Well: Curiosity Motivates Exploration for High Interest Learners. The Learning Partnership, April 2015. http://dx.doi.org/10.51420/conf.2015.1.

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Two studies were conducted to examine how individual interest predicts interactions with domain content and subsequent free-choice exploration. Particular focus was on learners’ acquisition of knowledge and identification of content that triggered curiosity. College student participants reported their individual interest, learned about a topic in ecology (Study 1, N = 85) and astronomy (Study 2, N = 184), responded to prompts for memory of the learning content and curiosity questions, and then had the opportunity to explore additional content related to the topic. In both studies individual interest interacted with whether students’ curiosity was triggered by particular content. In academic domains, individual interest in conjunction with curiosity may be the best predictor of continued behavioral exploration. The results are discussed in the context of the four-phase model of interest development.
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Ozcelik, Hilmi, Hamdi Jarjanazi und Noel Pabalan. Cloning and Characterization of Expanded CAG-Repeat Containing Sequence(s): Identification of Candidate Breast Cancer Predisposition (Gene(s). Fort Belvoir, VA: Defense Technical Information Center, Juni 2005. http://dx.doi.org/10.21236/ada442469.

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Ozcelik, Hilmi. Cloning and Characterization of Expanded CAG-Repeat Containing Sequence(s): Identification of Candidate Breast Cancer Predisposition Gene(s). Fort Belvoir, VA: Defense Technical Information Center, Juni 2004. http://dx.doi.org/10.21236/ada427658.

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Blundell, S. Micro-terrain and canopy feature extraction by breakline and differencing analysis of gridded elevation models : identifying terrain model discontinuities with application to off-road mobility modeling. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40185.

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Elevation models derived from high-resolution airborne lidar scanners provide an added dimension for identification and extraction of micro-terrain features characterized by topographic discontinuities or breaklines. Gridded digital surface models created from first-return lidar pulses are often combined with lidar-derived bare-earth models to extract vegetation features by model differencing. However, vegetative canopy can also be extracted from the digital surface model alone through breakline analysis by taking advantage of the fine-scale changes in slope that are detectable in high-resolution elevation models of canopy. The identification and mapping of canopy cover and micro-terrain features in areas of sparse vegetation is demonstrated with an elevation model for a region of western Montana, using algorithms for breaklines, elevation differencing, slope, terrain ruggedness, and breakline gradient direction. These algorithms were created at the U.S. Army Engineer Research Center – Geospatial Research Laboratory (ERDC-GRL) and can be accessed through an in-house tool constructed in the ENVI/IDL environment. After breakline processing, products from these algorithms are brought into a Geographic Information System as analytical layers and applied to a mobility routing model, demonstrating the effect of breaklines as obstacles in the calculation of optimal, off-road routes. Elevation model breakline analysis can serve as significant added value to micro-terrain feature and canopy mapping, obstacle identification, and route planning.
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Hayes, Anne M. Assessment as a Service Not a Place: Transitioning Assessment Centers to School-Based Identification Systems. RTI Press, April 2020. http://dx.doi.org/10.3768/rtipress.2020.op.0064.2004.

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The World Health Organization and World Bank (2011) estimate that there are more than 1 billion people with disabilities in the world. To address this population’s diverse needs, the United Nations drafted their Convention on the Rights of Persons with Disabilities (CRPD) in 2006. Article 24 (Education) of the CRPD requires ratifying countries to develop an inclusive education system to address the educational needs of students with disabilities alongside their peers without disabilities. Despite substantive improvements and movement toward inclusive education, many low- and middle-income countries (LMICs) continue to struggle with accurately identifying and supporting students with disabilities, including knowing how to effectively screen, evaluate, and qualify students for additional services (Hayes, Dombrowski, Shefcyk, & Bulat, 2018a). These challenges stem from the lack of policies, practices, and qualified staff related to screening and identification. As a result, many students with less-apparent disabilities—such as children with learning disabilities—remain unidentified and do not receive the academic supports they need to succeed in school (Friend & Bursuck, 2012). This guide attempts to address the lack of appropriate, useful disability screening and identification systems and services as countries look to educate all students in inclusive settings. Specifically, this guide introduces viable options for screening and identification related to vision, hearing, and learning disabilities in inclusive classrooms in LMICs. It also provides guidance on how LMICs can transition from an assessment-center model toward a school-based identification model that better serves an inclusive education system.
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Hayes, Anne M., Eileen Dombrowski, Allison H. Shefcyk und Jennae Bult. Learning Disabilities Screening and Evaluation Guide for Low- and Middle-Income Countries. RTI Press, April 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0052.1804.

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Learning disabilities are among the most common disabilities experienced in childhood and adulthood. Although identifying learning disabilities in a school setting is a complex process, it is particularly challenging in low- and middle-income countries that lack the appropriate resources, tools, and supports. This guide provides an introduction to learning disabilities and describes the processes and practices that are necessary for the identification process. It also describes a phased approach that countries can use to assess their current screening and evaluation services, as well as determine the steps needed to develop, strengthen, and build systems that support students with learning disabilities. This guide also provides intervention recommendations that teachers and school administrators can implement at each phase of system development. Although this guide primarily addresses learning disabilities, the practices, processes, and systems described may be also used to improve the identification of other disabilities commonly encountered in schools.
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