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Journal articles on the topic 'Car identification'

Author: Grafiati

Published: 28 June 2021

Last updated: 1 February 2022

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1

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, no. 3 (September 1, 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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2

Cima, Robert R., Ivan Cheng, Mary E. Klingensmith, Naibedya Chattopadhyay, Olga Kifor, Steven C. Hebert, Edward M. Brown, and 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, no. 5 (November 1, 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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3

Venture, Gentiane, Wisama Khalil, Maxime Gautier, and Philippe Bodson. "Dynamic Identification of a Car." IFAC Proceedings Volumes 37, no. 22 (April 2004): 733–38. http://dx.doi.org/10.1016/s1474-6670(17)30431-7.

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4

Mahmood, Sanner H., Oulla G. Hassan, Ayad M. Kwad, and Safa F. Abass. "Auto Opening Door and Car Identification." Journal of Computer and Communications 04, no. 15 (2016): 132–41. http://dx.doi.org/10.4236/jcc.2016.415013.

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5

Venture, Gentiane, Maxime Gautier, Wisama Khalil, and Philippe Bodson. "Parametric identification of the car dynamics." IFAC Proceedings Volumes 36, no. 16 (September 2003): 285–90. http://dx.doi.org/10.1016/s1474-6670(17)34775-4.

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6

Russo, Michele, Riccardo Russo, and Agsotino Volpe. "Car Parameters Identification by Handling Manoeuvres." Vehicle System Dynamics 34, no. 6 (December 29, 2000): 423–36. http://dx.doi.org/10.1076/vesd.34.6.423.2053.

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7

Sugarindra, Muchamad, and 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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8

Tawfeek, M., S. Shedid, I. El-Sherif, and Y. Hendawy. "INTEGRATION OF CAR SECURITY LEVELS USING TRANSPONDER KEY: DOUBLE IDENTIFICATION CAR CODE." International Conference on Applied Mechanics and Mechanical Engineering 15, no. 15 (May 1, 2012): 1–9. http://dx.doi.org/10.21608/amme.2012.37255.

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9

Kurup, Nithin. "Car Theft Identification, Tracking and Control System." IOSR Journal of Computer Engineering 4, no. 2 (2012): 31–34. http://dx.doi.org/10.9790/0661-0423134.

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10

Venture, Gentiane, Wisama Khalil, Maxime Gautier, and Philippe Bodson. "DYNAMIC MODELLING AND IDENTIFICATION OF A CAR." IFAC Proceedings Volumes 35, no. 1 (2002): 181–86. http://dx.doi.org/10.3182/20020721-6-es-1901.01498.

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11

Chattopadhyay, Naibedya, Ivan Cheng, Kimberly Rogers, Daniela Riccardi, Amy Hall, Ruben Diaz, Steven C. Hebert, David I. Soybel, and Edward M. Brown. "Identification and localization of extracellular Ca2+-sensing receptor in rat intestine." American Journal of Physiology-Gastrointestinal and Liver Physiology 274, no. 1 (January 1, 1998): G122—G130. http://dx.doi.org/10.1152/ajpgi.1998.274.1.g122.

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The extracellular calcium ([Formula: see text])-sensing receptor (CaR) plays vital roles in [Formula: see text] homeostasis, but no data are available on its expression in small and large intestine. Polymerase chain reaction products amplified from reverse-transcribed duodenal RNA using CaR-specific primers showed >99% homology with the rat kidney CaR. Northern analysis with a CaR-specific cRNA probe demonstrated 4.1- and 7.5-kb transcripts in all intestinal segments. Immunohistochemistry with CaR-specific antisera showed clear basal staining of epithelial cells of small intestinal villi and crypts and modest apical staining of the former, whereas there was both basal and apical staining of colonic crypt epithelial cells. In situ hybridization and immunohistochemistry also demonstrated CaR expression in Auerbach’s myenteric plexus of small and large intestines and in the submucosa in the region of Meissner’s plexus. Our results reveal CaR expression in several cell types of small and large intestine, in which it may modulate absorptive and/or secretomotor functions.

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12

Oshida, Keiyu, Naresh Vasani, Carlton Jones, Tanya Moore, Susan Hester, Stephen Nesnow, Scott Auerbach, et al. "Identification of Chemical Modulators of the Constitutive Activated Receptor (CAR) in a Gene Expression Compendium." Nuclear Receptor Signaling 13, no. 1 (January 2015): nrs.13002. http://dx.doi.org/10.1621/nrs.13002.

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The nuclear receptor family member constitutive activated receptor (CAR) is activated by structurally diverse drugs and environmentally-relevant chemicals leading to transcriptional regulation of genes involved in xenobiotic metabolism and transport. Chronic activation of CAR increases liver cancer incidence in rodents, whereas suppression of CAR can lead to steatosis and insulin insensitivity. Here, analytical methods were developed to screen for chemical treatments in a gene expression compendium that lead to alteration of CAR activity. A gene expression biomarker signature of 83 CAR-dependent genes was identified using microarray profiles from the livers of wild-type and CAR-null mice after exposure to three structurally-diverse CAR activators (CITCO, phenobarbital, TCPOBOP). A rank-based algorithm (Running Fisher's algorithm (p-value < 10-4)) was used to evaluate the similarity between the CAR biomarker signature and a test set of 28 and 32 comparisons positive or negative, respectively, for CAR activation; the test resulted in a balanced accuracy of 97%. The biomarker signature was used to identify chemicals that activate or suppress CAR in an annotated mouse liver/primary hepatocyte gene expression database of ∼1850 comparisons. CAR was activated by 1) activators of the aryl hydrocarbon receptor (AhR) in wild-type but not AhR-null mice, 2) pregnane X receptor (PXR) activators in wild-type and to lesser extents in PXR-null mice, and 3) activators of PPARα in wild-type and PPARα-null mice. CAR was consistently activated by five conazole fungicides and four perfluorinated compounds. Comparison of effects in wild-type and CAR-null mice showed that the fungicide propiconazole increased liver weight and hepatocyte proliferation in a CAR-dependent manner, whereas the perfluorinated compound perfluorooctanoic acid (PFOA) increased these endpoints in a CAR-independent manner. A number of compounds suppressed CAR coincident with increases in markers of inflammation including acetaminophen, concanavalin A, lipopolysaccharide, and 300 nm silica particles. In conclusion, we have shown that a CAR biomarker signature coupled with a rank-based similarity method accurately predicts CAR activation. This analytical approach, when applied to a gene expression compendium, increased the universe of known chemicals that directly or indirectly activate CAR, highlighting the promiscuous nature of CAR activation and signaling through activation of other xenobiotic-activated receptors.

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13

Wang, Tong, Geng Tian, and Cong Han. "Route Identification in Intelligent Traffic System Based on CMOS Image Sensor." Applied Mechanics and Materials 229-231 (November 2012): 1202–5. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1202.

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This paper introduces a method based on image processing technology, which allows model car to identify the route on a white board. Our system uses MC9S12XS128 as the control unit, CMOS camera is applied to capture data, and H-bridge driver circuit supports the motor. In addition, we use the ultrasonic to calculate the distance and wireless data transmission module to protect the car from a crash. Finally, we establish an algorithm which controls the car and recognize dotted lines in order to overtake the other model car at speed-change area.

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14

Kang, Chung Hyo, Yeongrin Kim, Heung Kyoung Lee, So Myoung Lee, Hye Gwang Jeong, Sang Un Choi, and Chi Hoon Park. "Identification of Potent CD19 scFv for CAR T Cells through scFv Screening with NK/T-Cell Line." International Journal of Molecular Sciences 21, no. 23 (December 1, 2020): 9163. http://dx.doi.org/10.3390/ijms21239163.

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CD19 is the most promising target for developing chimeric-antigen receptor (CAR) T cells against B-cell leukemic cancer. Currently, two CAR-T-cell products, Kymriah and Yescarta, are approved for leukemia patients, and various anti-CD19 CAR T cells are undergoing clinical trial. Most of these anti-CD19 CAR T cells use FMC63 single-chain variable fragments (scFvs) for binding CD19 expressed on the cancer cell surface. In this study, we screened several known CD19 scFvs for developing anti-CD19 CAR T cells. We used the KHYG-1 NK/T-cell line for screening of CD19 scFvs because it has advantages in terms of cell culture and gene transduction compared to primary T cells. Using our CAR construct backbone, we made anti-CD19 CAR constructs which each had CD19 scFvs including FMC63, B43, 25C1, BLY3, 4G7, HD37, HB12a, and HB12b, then made each anti-CD19 CAR KHYG-1 cells. Interestingly, only FMC63 CAR KHYG-1 and 4G7 CAR KHYG-1 efficiently lysed CD19-positive cell lines. In addition, in Jurkat cell line, only these two CAR Jurkat cell lines secreted IL-2 when co-cultured with CD19-positive cell line, NALM-6. Based on these results, we made FMC63 CAR T cells and 4G7 CAR T cells from PBMC. In in vitro lysis assay, 4G7 CAR T cells lysed CD19-positive cell line as well as FMC63 CAR T cells. In in vivo assay with NOD.Cg-PrkdcscidIl2rgtm1Wjl/SzJ (NSG) mice, 4G7 CAR T cells eradicated NALM-6 as potently as FMC63 CAR T cells. Therefore, we anticipate that 4G7 CAR T cells will show as good a result as FMC63 CAR T cells for B-cell leukemia patients.

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15

Mazlan, Muhammad Syamil, Isredza Rahmi A Hamid, and Hazalila Kamaludin. "Radio Frequency Identification (RFID) Based Car Parking System." JOIV : International Journal on Informatics Visualization 2, no. 4-2 (September 10, 2018): 318. http://dx.doi.org/10.30630/joiv.2.4-2.173.

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Radio Frequency Identification (RFID) technology is widely used in various applications such as attendance system, tracking system, monitoring system or parking system. Currently, the existing parking system used manual entrance through security guard to access the premise. Therefore, the company need to hire security guard to monitor the premise. In addition, the security guards need to monitor all movement of vehicle or person that enter or leave the premise. As a result, unauthorized vehicle or person can easily access the building. To address this problem, we proposed a parking system using RFID technology that can monitor vehicle’s movement that enter or leave the specific area or place by scanning the RFID tag. The potential benefit is it can improve security for both security guards and users. Besides that, this parking system can facilitate access control for users and improve traffic flow during peaks period. There are five modules in the proposed parking systems which are user registration, vehicle registration, RFID tag, staff and report generation.

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16

Sani, M. S. M., M. M. Rahman, M. M. Noor, K. Kadirgama, and M. H. N. Izham. "Identification of Dynamics Modal Parameter for Car Chassis." IOP Conference Series: Materials Science and Engineering 17 (February 1, 2011): 012038. http://dx.doi.org/10.1088/1757-899x/17/1/012038.

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17

Vanamo, J., B. Windshügel, J. Jyrkkärinne, A. Poso, W. Sippl, and P. Honkakoski. "Identification of novel CAR agonists for drug development." European Journal of Pharmaceutical Sciences 34, no. 1 (June 2008): S32. http://dx.doi.org/10.1016/j.ejps.2008.02.086.

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18

Li, Hong Ying. "Design of Computer Vision and Image Processing Technology Based Car Keys Tooth Identification Detection System." Advanced Materials Research 1079-1080 (December 2014): 1061–63. http://dx.doi.org/10.4028/www.scientific.net/amr.1079-1080.1061.

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This paper can be used as acar key toothed recognition and detection technology and computer vision, imageprocessing technology combined with interdisciplinary applications. Car lockassembly complicated procedures, identification and car keys tooth detection isone of the key aspects of automotive lock assembly, lock a direct impact on theefficiency of the assembly process. The system can effectively improve theexisting car key tooth detection technology to reduce the cost of car keystooth detection recognition, while also rapid and accurate identification, sothat the entire lock assembly process much more efficient.

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19

Maglich, Jodi M., Derek J. Parks, Linda B. Moore, Jon L. Collins, Bryan Goodwin, Andrew N. Billin, Catherine A. Stoltz, et al. "Identification of a Novel Human Constitutive Androstane Receptor (CAR) Agonist and Its Use in the Identification of CAR Target Genes." Journal of Biological Chemistry 278, no. 19 (February 27, 2003): 17277–83. http://dx.doi.org/10.1074/jbc.m300138200.

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20

Jia, Chao, Wen Qian An, Xu Fang Bo, and Xiao Fang Chen. "Methods of Path Identification and Processing in Freescale Intelligence Car." Applied Mechanics and Materials 631-632 (September 2014): 606–9. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.606.

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It is based on the Eighth National College "Freescale" intelligent vehicle competition, this contest requirements to make a model car which can identify the road on the model vehicle platforms independently. If the model car completes contest in accordance with the line for the shortest time that it is winning. Therefore, researching various types of track and the path tracking approach of each group model car is particularly important. First it describes the various types of track, and then describes track recognition principle of each group by using corresponding sensors in detail, finally it analysis how to use sensor to deal with all kinds of circuit method, so that the model car can be quickly and securely through a variety of track, and in the shortest time to reach the end.

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21

Squires, PE. "Non-Ca2+-homeostatic functions of the extracellular Ca2+-sensing receptor (CaR) in endocrine tissues." Journal of Endocrinology 165, no. 2 (May 1, 2000): 173–77. http://dx.doi.org/10.1677/joe.0.1650173.

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The extracellular Ca(2+)-sensing receptor (CaR) links changes in the concentration of extracellular Ca(2+) to changes in cell function. For cells involved in the control of systemic Ca(2+) concentration, this provides an efficient receptor-mediated mechanism to rapidly counteract slight fluctuations in the circulating concentration of Ca(2+). However, all cells that express the CaR are not necessarily involved in Ca(2+) homeostasis. The recent localisation of CaR expression on a variety of cell types more usually associated with non-Ca(2+)-homeostatic endocrine function may have serious repercussions for the interpretation of data in those systems which routinely culture cells under standard hypercalcaemic conditions. This short commentary considers the literature surrounding the identification of the CaR and the potential effects of its localisation on endocrine cells not directly involved in the control of systemic Ca(2+ )homeostasis.

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22

Busson, Roger, André De Bruyn, Piet Herdewijn, Martine Maes, and Eric Messens. "IDENTIFICATION OF THE EXOPOLYSACCHARIDE AMYLOVORAN BY NMR[1]." Journal of Carbohydrate Chemistry 20, no. 2 (March 31, 2001): 109–20. http://dx.doi.org/10.1081/car-100103952.

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23

Arai, Yoshinori, and Kaoru Hirota. "Car Type/Name Recognition System Based on The Concept of Fixation." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 4 (August 20, 1999): 274–81. http://dx.doi.org/10.20965/jaciii.1999.p0274.

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The concept of the "Fixation", meaning to monitor features for identifying transport vehicles is proposed. And a framework of the "Fuzzy Hierarchical Pattern Recognition using a Fixation Feedback (FHPR/FF)" " algorithm is introduced. The experiment system, for identifying car types and car names where 70 images are taken for 14 miniature cars from 5 directions, is constructed. Forced recognition of 92.9% is achieved for car types and 89.7% for car names. The proposed experiment system is the basis for real running vehicle identification confirmed by perfect identification of 5 images for each model.

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24

Campa, Cristiana, Ivan Donati, Amedeo Vetere, Amelia Gamini, and Sergio Paoletti. "SYNTHESIS OF GLYCOSYLAMINES: IDENTIFICATION AND QUANTIFICATION OF SIDE PRODUCTS." Journal of Carbohydrate Chemistry 20, no. 3-4 (April 30, 2001): 263–73. http://dx.doi.org/10.1081/car-100104862.

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25

Okundamiya, M. S., J. O. Emagbetere, and F. O. Edeko. "Design and Implementation of a GSM Activated Automobile Demobilizer with Identification Capability." Advanced Materials Research 62-64 (February 2009): 89–98. http://dx.doi.org/10.4028/www.scientific.net/amr.62-64.89.

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The incidence of car theft in Nigeria has grown to nearly epidemic proportion. On daily basis, the numbers of stolen cars reported over the media are on the increase. Alarms and other deterrents are not enough. There is actually little one can do to prevent a car from being stolen. However, with a Global System for Mobile communication (GSM) activated automobile demobilizer with identification capability one can virtually take control of the virtually impossible incidence and hence increase the possibility of car recovery. This paper is aimed at implementing a security device capable of safeguarding cars from theft as well as provides picture and audio information of the culprits in an attempt to steal the car. To realize this work, use was made of a GSM phone

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26

Susanti, Roza, and Budhi Bakhtiar. "PENGATURAN PORTAL PADA PENGURUTAN PARKIR MOBIL DENGAN MENGGUNAKAN RFId DAN PC." Elektron : Jurnal Ilmiah 1, no. 2 (December 18, 2009): 61–72. http://dx.doi.org/10.30630/eji.1.2.22.

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The number of vehicles increasing day by day. It will trigger the demand of parking area, especially for car park. To overcome this problem, we offer a solution, by creating a miniatur car parking. This Car park only for members whose can park their car in it. Each car will be equiped by a RFId tag (RFid card) and the RFId sensor (Radio Frequency Identification) which will detecting this card . The main function of the RFid card is to detecting every car come and go from the car parking area. The data are readed from the card need to be checked and verified with the database of member identification (Id) by using Visual Basic 6.0 as the interface. The serial port RS 232 used as the interface to connect RFId sensor and Personal computer. The program in AT89S51 microcontroller will control the motor rotation for opening or closing the parking area gate.

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27

Arthur, J. M., G. P. Collinsworth, T. W. Gettys, L. D. Quarles, and J. R. Raymond. "Specific coupling of a cation-sensing receptor to G protein alpha-subunits in MDCK cells." American Journal of Physiology-Renal Physiology 273, no. 1 (July 1, 1997): F129—F135. http://dx.doi.org/10.1152/ajprenal.1997.273.1.f129.

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Extracellular cations such as Ca2+ stimulate a G protein-coupled, cation-sensing receptor (CaR). We used microphysiometry to determine whether an extracellular cation-sensing mechanism exists in Madin-Darby canine kidney (MDCK) cells. The CaR agonists Ca2+ and Gd3+ caused cellular activation in a concentration-dependent manner. mRNA for the CaR was identified by reverse transcription and polymerase chain reaction (PCR) using nested CaR-specific primers, identification of an appropriately located restriction site, and sequencing of the subcloned fragment obtained by PCR. G protein activation was evaluated using the GTP photoaffinity label [alpha-32P]GTP azidoanalide (AA-GTP). After stimulation with Gd3+ and cross-linking, plasma membranes were solubilized and immunoprecipitated with antisera specific for Gq/11 alpha and Gi alpha family members. Gd3+ increased incorporation of AA-GTP into Gq/11 alpha precipitates by 146 +/- 48% and into G alpha i-2 and G alpha i-3 to a lesser extent but not into G alpha i-1. Direct effects of Gd3+ on the G proteins were ruled out using partially purified mammalian G proteins expressed in Escherichia coli or Sf9 cells. We conclude that MDCK cells possess a cell-surface CaR that activates Gq/11 alpha, G alpha i-2, and G alpha i-3 but not G alpha i-1.

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Et. al., Nouria Kaream Khoorshed,. "Car Surveillance Video Summarization Based On Car Plate Detection." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 11, 2021): 1132–44. http://dx.doi.org/10.17762/turcomat.v12i6.2431.

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Today, video is a common medium for sharing information. Navigating the internet to download a certain form of video, it takes a long time, a lot of bandwidth, and a lot of disk space. Since sending video over the internet is too costly, therefore video summarization has become a critical technology. Monitoring vehicles of people from a security and traffic perspective is a major issue. This monitoring depends on the identification of the license plate of vehicles. The proposed system includes training and testing stages. Training stage comprises: video preprocessing, Viola-Jones training, and Support Vector Machine (SVM) optimization. Testing stage contains: test video preprocessing, car plate (detection, cropping, resizing, and grouping detecting test car plate, feature extraction using HOG feature. The total time of local recorded videos is (19.5 minutes), (15.5 minutes) for training, and (4 minutes) for testing. This means, (79.5%) for training and (20.5%) for testing. The proposed video summarization has got maximum accuracy of (86%) by using Viola-Jones and SVM by reducing the number of original video frames from (7077) frames to (1200) frames. The accuracy of the Viola-Jones object detection process for training 700 images is (97%). The accuracy of the SVM classifier is (99.6%).

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29

Barbaro, A. "Identification of a carbonized body found inside a car." International Congress Series 1239 (January 2003): 869–71. http://dx.doi.org/10.1016/s0531-5131(02)00232-7.

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30

Venture, Gentiane, Wisama Kbalil, Maxime Gautier, and Philippe Bodson. "Experimental identification of the dynamic parameters of a car." IFAC Proceedings Volumes 36, no. 17 (September 2003): 61–66. http://dx.doi.org/10.1016/s1474-6670(17)33370-0.

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31

Wang, Jianfeng, Yiqun Liu, Liang Ding, Jun Li, Haibo Gao, Yuhan Liang, and Tianyao Sun. "Neural Network Identification of a Racing Car Tire Model." Journal of Engineering 2018 (May 29, 2018): 1–11. http://dx.doi.org/10.1155/2018/4143794.

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In order to meet the demands of small race car dynamics simulation, a new method of parameter identification in the Magic Formula tire model is presented in this work, based on an analysis of the Magic Formula tire model structure. A high-precision tire model used for vehicle dynamics simulation is established via this method. It is difficult for students to build a high-precision tire model because of the complexity of widely used tire models such as Magic Formula and UniTire. At a pure side slip condition, building a lateral force model is an example, which illustrate the utilization of a multilayer feed-forward neural network to build an intelligent tire model conveniently. In order to fully understand the difference between the two models, a two-degrees-of-freedom (2 DOF) vehicle model is established. The advantages, disadvantages, and applicable scope of the two tire models are discussed after comparing the simulation results of the 2 DOF model with the Magic Formula and intelligent tire model.

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32

Taskin, Y., N. Yagiz, and I. Yuksek. "Lumped parameter identification of a quarter car test rig." Journal of Physics: Conference Series 410 (February 8, 2013): 012089. http://dx.doi.org/10.1088/1742-6596/410/1/012089.

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33

Schiehlen, Werner, Christoph Tobias, and Marc Wewel. "Modelling and Parameter Identification of a Formula Student Car." PAMM 10, no. 1 (November 16, 2010): 57–58. http://dx.doi.org/10.1002/pamm.201010021.

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34

Deshpande, Mangesh S., and Raghunath S. Holambe. "Robust speaker identification in the presence of car noise." International Journal of Biometrics 3, no. 3 (2011): 189. http://dx.doi.org/10.1504/ijbm.2011.040815.

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35

Santoso, Mega Putra Yogia. "Central Lock Car Security System Design Using E-KTP Identification." Jurnal Jartel: Jurnal Jaringan Telekomunikasi 9, no. 4 (December 25, 2019): 1–7. http://dx.doi.org/10.33795/jartel.v9i4.139.

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Currently, most motorized vehicle safety technologies, especially cars, still rely heavily on the manufacturer's default safety system from the car system itself. By using a security system from the factory default there are still shortcomings because a motorized vehicle or car can still be used by anyone and there is no age limit in its use. For that, we need a car safety system that is able to prevent the occurrence of car theft and underage drivers. The purpose of this research is to design a central lock security system for motor vehicles, especially cars, using e-KTP identification to improve the security system and reduce underage drivers. For the identification process of e-KTP ID using the RFID reader MFRC522. The RFID reader is connected to the Arduino Nano as a controller. The results of the research used the RFID reader to read e-KTP ID in a vertical and horizontal position with a distance of less than 12 mm. When there is an acrylic barrier and a glass barrier the maximum reading distance is less than 9 mm and the plate barrier cannot be read. The existence of obstacles makes reading the e-KTP card will be reduced.

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Shirzad-Ghaleroudkhani, Nima, and Mustafa Gül. "Inverse Filtering for Frequency Identification of Bridges Using Smartphones in Passing Vehicles: Fundamental Developments and Laboratory Verifications." Sensors 20, no. 4 (February 21, 2020): 1190. http://dx.doi.org/10.3390/s20041190.

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This paper puts forward a novel methodology of employing inverse filtering technique to extract bridge features from acceleration signals recorded on passing vehicles using smartphones. Since the vibration of a vehicle moving on a bridge will be affected by various features related to the vehicle, such as suspension and speed, this study focuses on filtering out these effects to extract bridge frequencies. Hence, an inverse filter is designed by employing the spectrum of vibration data of the vehicle when moving off the bridge to form a filter that will remove the car-related frequency content. Later, when the same car is moving on the bridge, this filter is applied to the spectrum of recorded data to suppress the car-related frequencies and amplify the bridge-related frequencies. The effectiveness of the proposed methodology is evaluated with experiments using a custom-built robot car as the vehicle moving over a lab-scale simply supported bridge. Nine combinations of speed and suspension stiffness of the car have been considered to investigate the robustness of the proposed methodology against car features. The results demonstrate that the inverse filtering method offers significant promise for identifying the fundamental frequency of the bridge. Since this approach considers each data source separately and designs a unique filter for each data collection device within each car, it is robust against device and car features.

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Munro, Eileen. "What tools do we need to improve identification of child abuse?" Child Abuse Review 14, no. 6 (2005): 374–88. http://dx.doi.org/10.1002/car.921.

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Bernardi, Mario Luca, Marta Cimitile, Fabio Martinelli, and Francesco Mercaldo. "Driver and Path Detection through Time-Series Classification." Journal of Advanced Transportation 2018 (2018): 1–20. http://dx.doi.org/10.1155/2018/1758731.

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Driver identification and path kind identification are becoming very critical topics given the increasing interest of automobile industry to improve driver experience and safety and given the necessity to reduce the global environmental problems. Since in the last years a high number of always more sophisticated and accurate car sensors and monitoring systems are produced, several proposed approaches are based on the analysis of a huge amount of real-time data describing driving experience. In this work, a set of behavioral features extracted by a car monitoring system is proposed to realize driver identification and path kind identification and to evaluate driver’s familiarity with a given vehicle. The proposed feature model is exploited using a time-series classification approach based on a multilayer perceptron (MLP) network to evaluate their effectiveness for the goals listed above. The experiment is done on a real dataset composed of totally 292 observations (each observation consists of a given person driving a given car on a predefined path) and shows that the proposed features have a very good driver and path identification and profiling ability.

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Wu, Weijia, Yan Huo, Xueying Ding, Yuhong Zhou, Shengying Gu, and Yuan Gao. "Identification of the risks in CAR T-cell therapy clinical trials in China: a Delphi study." Therapeutic Advances in Medical Oncology 12 (January 2020): 175883592096657. http://dx.doi.org/10.1177/1758835920966574.

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Aims: Within the past few years, there has been tremendous growth in clinical trials of chimeric antigen receptor (CAR) T-cell therapies. Unlike those of many small-molecule pharmaceuticals, CAR T-cell therapy clinical trials are fraught with risks due to the use of live cell products. The aim of this study is to reach a consensus with experts on the most relevant set of risks that practically occur in CAR T-cell therapy clinical trials. Methods: A Delphi method of consensus development was used to identify the risks in CAR T-cell therapy clinical trials, comprising three survey rounds. The expert panel consisted of principal investigators, clinical research physicians, members of institutional ethics committees, and Good Clinical Practice managers. Results: Of the 24 experts invited to participate in this Delphi study, 20 participants completed Round 1, Round 2, and Round 3. Finally, consensus (defined as >80% agreement) was achieved for 54 risks relating to CAR T-cell clinical trials. Effective interventions related to these risks are needed to ensure the proper protection of subject health and safety. Conclusion: The Delphi method was successful in gaining a consensus on risks relevant to CAR T-cell clinical trials in a geographically diverse expert association. It is hoped that this work can benefit future risk-based quality management in clinical trials and can potentially promote the better development of CAR T-cell therapy products.

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Thibault, Isabelle, Robert Pauzé, Éric Lavoie, Marie Mercier, Caroline Pesant, Johana Monthuy-Blanc, and Marie-Pierre Gagnon-Girouard. "Identification des pratiques prometteuses dans le traitement de l’anorexie mentale." Mosaïque 42, no. 1 (June 14, 2017): 379–90. http://dx.doi.org/10.7202/1040260ar.

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L’anorexie mentale inquiète, d’une part, car elle est associée à de nombreuses complications médicales et, d’autre part, car elle est liée à un mauvais pronostic. Face à ces constats, il est impératif que les traitements les plus efficaces soient offerts aux personnes présentant une anorexie mentale. Cet article vise à présenter une revue systématique de la littérature portant sur les modalités thérapeutiques prometteuses dans le domaine de l’anorexie mentale. Parmi celles-ci, notons le traitement ambulatoire, l’importance d’une équipe multidisciplinaire ainsi que différentes approches psychothérapeutiques, dont l’approche familiale.

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Yang, Wen Chuan, Guang Jie Lin, and Jiang Yong Wang. "A MapReduce Clone Car Identification Model over Traffic Data Stream." Applied Mechanics and Materials 346 (August 2013): 117–22. http://dx.doi.org/10.4028/www.scientific.net/amm.346.117.

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Accompany the widely use of Intelligent Traffic in China, all traffic input data streams to the Traffic Surveillance Center (TSC). Some metropolitan TSC, such as in Beijing, produces up to 18 million records and 1T image data arriving every hour. Normally, the job of the TSC is to monitor and retain data. There is a tendency to put more capability into the TSC, such as ad-hoc query for clone car identification and feedback abnormal traffic information. Thus we definitely need to think about what can be kept in working storage and how to analysis it. Obviously, the ordinary database cannot handle the massive dataset and complex ad-hoc query. MapReduce is a popular and widely used fine grain parallel runtime, which is developed for high performance processing of large scale dataset. In this paper, we propose CarMR, a MapReduce Clone Car Identification system based on Hive/Hadoop frameworks. A distributed file system HDFS is used in CarMR for fast data sharing and query. CarMR supports fast locating clone car and also optimizes the route to catch fugitive. Our results show that the model achieves a higher efficiency.

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Pascussi, Jean Marc, Maryvonne Busson-Le Coniat, Patrick Maurel, and Marie-José Vilarem. "Transcriptional Analysis of the Orphan Nuclear Receptor Constitutive Androstane Receptor (NR1I3) Gene Promoter: Identification of a Distal Glucocorticoid Response Element." Molecular Endocrinology 17, no. 1 (January 1, 2003): 42–55. http://dx.doi.org/10.1210/me.2002-0244.

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Abstract The constitutive androstane receptor (CAR, NR1I3) transcriptionally activates cytochrome P450 2B6, 2C9, and 3A4 when activated by xenobiotics, such as phenobarbital. Information on the human CAR promoter was obtained by searching the NCBI human genome database. A contig (NT026945) corresponding to a fragment of chromosome 1q21 was found to contain the complete CAR gene. These data were confirmed using chromosomal in situ hybridization. Both primer extension and 5′-rapid amplification of the cDNA end PCR analysis were carried out to determine the transcriptional start site of human CAR, which was found to be 32 nucleotides downstream of a potential TATA box (CATAAAA). In addition, we found that the 5′-untranslated region of CAR mRNA is 110 nucleotides shorter than previously reported. Using genomic PCR, we amplified and cloned approximately 4.9 kb (−4711/+144) of the CAR gene promoter. The activity of this promoter was measured by transient transfection. Deletion analysis suggested the presence of a glucocorticoid responsive element in its distal region (−4477/−4410). From cotransfection experiments, mutagenesis, and gel shift assays, we identified a glucocorticoid response element at −4447/−4432 that was recognized and transactivated by the human glucocorticoid receptor. Finally, using the chromatin immunoprecipitation assay, we demonstrated that the glucocorticoid receptor binds to the distal region of CAR promoter in cultured hepatocytes only in the presence of dexamethasone. Identification of this functional element provides a rational mechanistic basis for CAR induction by glucocorticoids. CAR appears to be a primary glucocorticoid receptor-response gene.

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Nelson, Michelle H., Hannah M. Knochelmann, Stefanie R. Bailey, Logan W. Huff, Jacob S. Bowers, Kinga Majchrzak-Kuligowska, Megan M. Wyatt, et al. "Identification of human CD4+ T cell populations with distinct antitumor activity." Science Advances 6, no. 27 (July 2020): eaba7443. http://dx.doi.org/10.1126/sciadv.aba7443.

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How naturally arising human CD4+ T helper subsets affect cancer immunotherapy is unclear. We reported that human CD4+CD26high T cells elicit potent immunity against solid tumors. As CD26high T cells are often categorized as TH17 cells for their IL-17 production and high CD26 expression, we posited these populations would have similar molecular properties. Here, we reveal that CD26high T cells are epigenetically and transcriptionally distinct from TH17 cells. Of clinical importance, CD26high and TH17 cells engineered with a chimeric antigen receptor (CAR) regressed large human tumors to a greater extent than enriched TH1 or TH2 cells. Only human CD26high T cells mediated curative responses, even when redirected with a suboptimal CAR and without aid by CD8+ CAR T cells. CD26high T cells cosecreted effector cytokines, produced cytotoxic molecules, and persisted long term. Collectively, our work underscores the promise of CD4+ T cell populations to improve durability of solid tumor therapies.

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Wang, Hong, Xian Li, and Shuang Liu. "The Design of a Car License Plate Identification System Based on AdaBoost Algorithm." Advanced Materials Research 181-182 (January 2011): 588–93. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.588.

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Design and implement a car license plate identification system with the applications of Viola and Jones algorithm. This algorithm which is based on the AdaBoost method is trained and optimized for the best performance using large database of car license plate images. The final license plate identification system obtained a cascade of classifiers consisting of 8 stages with 1310 Haar-like features. Once the license plates have sufficient visibility and there are no other objects similar to the plate in images, this system operates perfectly and shows high correct identification rate with low false positive rate. And as integral image allows the Haar-like features to be calculated very fast, the system also finished the identification rapidly.

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Aleksandrowicz, Piotr, Michał Stopel, and Dariusz Skibicki. "Identification parameters for accident reconstruction software at frontal car impact." Materials Testing 62, no. 5 (May 4, 2020): 441–47. http://dx.doi.org/10.3139/120.111502.

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Feng, Hu, and Sun Guoji. "Detection and magnitude identification of abrupt faults for car process." IFAC Proceedings Volumes 33, no. 20 (July 2000): 113–18. http://dx.doi.org/10.1016/s1474-6670(17)38035-7.

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Meissonnier, J., J.-C. Fauroux, G. Gogu, and C. Montezin. "Geometric Identification of an Elastokinematic Model in a Car Suspension." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 220, no. 9 (August 21, 2006): 1209–20. http://dx.doi.org/10.1243/09544070jauto239.

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Zong, Fang, Meng Zeng, Zhengbing He, and Yixin Yuan. "Bus-Car Mode Identification: Traffic Condition–Based Random-Forests Method." Journal of Transportation Engineering, Part A: Systems 146, no. 10 (October 2020): 04020113. http://dx.doi.org/10.1061/jtepbs.0000442.

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YUKAWA, Tomohiro, Takeshi TOI, and Nobuyuki OKUBO. "Force identification and vibration reduction of body in hybrid car." Proceedings of Conference of Kanto Branch 2003.9 (2003): 401–2. http://dx.doi.org/10.1299/jsmekanto.2003.9.401.

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Venture, G., P. J. Ripert, W. Khalil, M. Gautier, and P. Bodson. "Modeling and Identification of Passenger Car Dynamics Using Robotics Formalism." IEEE Transactions on Intelligent Transportation Systems 7, no. 3 (September 2006): 349–59. http://dx.doi.org/10.1109/tits.2006.880620.

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