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Статті в журналах з теми "MINUTIA MATCHING"

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BHOWMICK, PARTHA, ARIJIT BISHNU, BHARGAB BIKRAM BHATTACHARYA, MALAY KUMAR KUNDU, C. A. MURTHY, and TINKU ACHARYA. "DETERMINATION OF MINUTIAE SCORES FOR FINGERPRINT IMAGE APPLICATIONS." International Journal of Image and Graphics 05, no. 03 (July 2005): 537–71. http://dx.doi.org/10.1142/s0219467805001896.

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Many Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching. Minutiae are the terminations and bifurcations of the ridge lines in a fingerprint image. A gray-scale fingerprint image that has undergone binarization, followed by thinning, in order to extract the minutiae, may contain hundreds of minutiae, all of which are not so vivid and obvious in the original image. Thus, the set of minutiae that are well-defined and more prominent than the rest should be given higher relevance and importance in the process of minutiae matching. In this work, a gray-scale fingerprint image is first preprocessed to produce a thinned binary image. Next, a method to assign a score value to each of the extracted minutiae is proposed, based on certain topographical properties of a minutia. The score associated to a minutia signifies its robustness and prominence. A minutia with a higher score value should be considered with higher priority in the matching scheme to yield better results. Experimental results on several standard databases have been reported.
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Loyola-González, Octavio, Emilio Francisco Ferreira Mehnert, Aythami Morales, Julian Fierrez, Miguel Angel Medina-Pérez, and Raúl Monroy. "Impact of Minutiae Errors in Latent Fingerprint Identification: Assessment and Prediction." Applied Sciences 11, no. 9 (May 4, 2021): 4187. http://dx.doi.org/10.3390/app11094187.

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We study the impact of minutiae errors in the performance of latent fingerprint identification systems. We perform several experiments in which we remove ground-truth minutiae from latent fingerprints and evaluate the effects on matching score and rank-n identification using two different matchers and the popular NIST SD27 dataset. We observe how missing even one minutia from a fingerprint can have a significant negative impact on the identification performance. Our experimental results show that a fingerprint which has a top rank can be demoted to a bottom rank when two or more minutiae are missed. From our experimental results, we have noticed that some minutiae are more critical than others to correctly identify a latent fingerprint. Based on this finding, we have created a dataset to train several machine learning models trying to predict the impact of each minutia in the matching score of a fingerprint identification system. Finally, our best-trained model can successfully predict if a minutia will increase or decrease the matching score of a latent fingerprint.
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BENHAMMADI, FARID, and KADDA BEGHDAD BEY. "EMBEDDED FINGERPRINT MATCHING ON SMART CARD." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 02 (March 2013): 1350006. http://dx.doi.org/10.1142/s0218001413500067.

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This paper describes an embedded minutia-based matching algorithm using the reference point neighborhoods minutiae. The proposed matching algorithm is implemented in restricted environments such as smart card devices requiring careful monitoring of both memory and processing time usage. The proposed algorithm uses a circular tessellation to encode fingerprint features in neighborhood minutia localization binary codes. The objective of the present study is the development of a new matching approach which reduces both computing time and required space memory for fingerprint matching on Java Card. The main advantage of our approach is avoiding the implicit alignment of fingerprint images during the matching process while improving the fingerprint verification accuracy. Tests carried out on the public fingerprint databases DB1-a and DB2-a of FVC2002 have shown the effectiveness of our approach.
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Gao, Qinghai. "Toward Constructing Cancellable Templates using K-Nearest Neighbour Method." International Journal of Computer Network and Information Security 9, no. 5 (May 8, 2017): 1–10. http://dx.doi.org/10.5815/ijcnis.2017.05.01.

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The privacy of biometric data needs to be protected. Cancellable biometrics is proposed as an effective mechanism of protecting biometric data. In this paper a novel scheme of constructing cancellable fingerprint minutiae template is proposed. Specifically, each real minutia point from an original template is mapped to a neighbouring fake minutia in a user-specific randomly generated synthetic template using the k-nearest neighbour method. The recognition template is constructed by collecting the neighbouring fake minutiae of the real minutiae. This scheme has two advantages: (1) An attacker needs to capture both the original template and the synthetic template in order to construct the recognition template; (2) A compromised recognition template can be cancelled easily by replacing the synthetic template. Single-neighboured experiments of self-matching, nonself-matching, and imposter matching are carried out on three databases: DB1B from FVC00, DB1B from FVC02, and DB1 from FVC04. Double-neighboured tests are also conducted for DB1B from FVC02. The results show that the constructed recognition templates can perform more accurately than the original templates and it is feasible to construct cancellable fingerprint templates with the proposed approach.
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ZHU, EN, JIAN-PING YIN, GUO-MIN ZHANG, and CHUN-FENG HU. "FINGERPRINT MINUTIAE RELATIONSHIP REPRESENTATION AND MATCHING BASED ON CURVE COORDINATE SYSTEM." International Journal of Image and Graphics 05, no. 04 (October 2005): 729–44. http://dx.doi.org/10.1142/s0219467805001987.

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A minutiae relationship representation and matching method based on curve coordinate system is proposed. For each minutia, a curve coordinate system is established, and the coordinates of other minutiae in this coordinate system is computed. Thus, the coordinate relationship between each pair of minutiae can be evaluated. These relationships are used for pairing minutiae between the template fingerprint and the query fingerprint by means of transferring reference minutiae. The algorithm is tested on FVC2004DBs which include many highly distorted fingerprints. Results have shown that the proposed algorithm achieves improved matching accuracy and is able to cope with highly distorted fingerprints.
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Soetarmono, Anggya N. D. "IDENTIFIKASI SIDIK JARI DENGAN MENGGUNAKAN STRUKTUR MINUTIA." Teknika 1, no. 1 (July 1, 2012): 36–46. http://dx.doi.org/10.34148/teknika.v1i1.5.

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Анотація:
Penelitian ini membahas tentang sistem identifikasi personal dengan menggunakan kesesuaian biometrik pada pola sidik jari. Sesuai atau tidak sesuainya sebuah sidik jari dapat diketahui setelah melampaui serangkaian proses. Dimulai dari akuisisi citra sidik jari, memperbaiki kualitas citra, kemudian menggali fitur-fitur minutia yang ada pada citra sidik jari, hingga akhirnya dapat diukur nilai kesesuaiannya. Minutiae based matching adalah metode yang dipilih untuk mengukur tingkat kesesuaian pola sidik jari karena metode ini diyakini akan memberikan tingkat akurasi yang lebih baik jika dibandingkan dengan metode pattern based matching yang mana pada metode tersebut hanya membandingkan citra dari dua buah sidik jari.
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Cao, Kai, Xin Yang, Xinjian Chen, Xunqiang Tao, Yali Zang, Jimin Liang, and Jie Tian. "Minutia handedness: A novel global feature for minutiae-based fingerprint matching." Pattern Recognition Letters 33, no. 10 (July 2012): 1411–21. http://dx.doi.org/10.1016/j.patrec.2012.03.007.

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Soleimani, Hossein, and Mohsen Ahmadi. "Fast and efficient minutia‐based palmprint matching." IET Biometrics 7, no. 6 (April 11, 2018): 573–80. http://dx.doi.org/10.1049/iet-bmt.2017.0128.

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Tico, M., and P. Kuosmanen. "Fingerprint matching using an orientation-based minutia descriptor." IEEE Transactions on Pattern Analysis and Machine Intelligence 25, no. 8 (August 2003): 1009–14. http://dx.doi.org/10.1109/tpami.2003.1217604.

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Selvarani, P., and N. Malarvizhi. "Multibiometric authentication with MATLAB simulation." International Journal of Engineering & Technology 7, no. 1.7 (February 5, 2018): 47. http://dx.doi.org/10.14419/ijet.v7i1.7.9389.

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Multimodal Biometric Authentication has been used as more security purpose for establishing the user Identification, Authentication and Verification purpose. Multimodal Biometric like Fingerprint and iris are used in this research work for authentication purpose using Matlab simulation. Fingerprint recognition process like Image Enhancement, binarization, Segmentation, thinning, Minutia marking, and Matching are performed with various techniques like Histogram Equalization, Adaptive Binarization, Morphological operations, Minutiae based techniques etc.,Iris recognition process like Segmentation, Normalization, Encoding and Matching are performed with various techniques like Canny edge detection, Daughman’s Rubber sheet model, Hamming Distance etc., can be applied for Fingerprint and iris recognition for authentication purpose. Finally Performance the measure of Precision, Recall, F-Score and Accuracy has evaluated in both fingerprint and iris. It can be concluded Iris Accuracy is higher 0.96% compared with fingerprint accuracy 0.81%.
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Дисертації з теми "MINUTIA MATCHING"

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Li, Tuo. "Fingerprint Identification by Improved Method of Minutiae Matching." Miami University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=miami1484672769912832.

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Noor, Azad. "A new algorithm for minutiae extraction and matching in fingerprint." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7473.

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A novel algorithm for fingerprint template formation and matching in automatic fingerprint recognition has been developed. At present, fingerprint is being considered as the dominant biometric trait among all other biometrics due to its wide range of applications in security and access control. Most of the commercially established systems use singularity point (SP) or ‘core’ point for fingerprint indexing and template formation. The efficiency of these systems heavily relies on the detection of the core and the quality of the image itself. The number of multiple SPs or absence of ‘core’ on the image can cause some anomalies in the formation of the template and may result in high False Acceptance Rate (FAR) or False Rejection Rate (FRR). Also the loss of actual minutiae or appearance of new or spurious minutiae in the scanned image can contribute to the error in the matching process. A more sophisticated algorithm is therefore necessary in the formation and matching of templates in order to achieve low FAR and FRR and to make the identification more accurate. The novel algorithm presented here does not rely on any ‘core’ or SP thus makes the structure invariant with respect to global rotation and translation. Moreover, it does not need orientation of the minutiae points on which most of the established algorithm are based. The matching methodology is based on the local features of each minutiae point such as distances to its nearest neighbours and their internal angle. Using a publicly available fingerprint database, the algorithm has been evaluated and compared with other benchmark algorithms. It has been found that the algorithm has performed better compared to others and has been able to achieve an error equal rate of 3.5%.
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Henriksson, Marcus. "Analys av fingeravtryck." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1219.

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This report describes a system for verification of fingerprints against a previous created template. It describes how and why a fingerprint image must be processed before it can be used to either identify or verify a person. The method is based on special features of a fingerprint, called minutiae points. The whole process from image to matching is described, every step in the process with image enhancement, binarization, thinning and how to find the minutiae points. Also what false minutiae points are, how they arise, why they deteriorate the result, and how to handle them, is discussed.

Finally a test of the system with a large number of fingerprints is presented, to see how good the system is according to security and reliability about not accepting prints from other fingers or reject the fingerprints, which are from the same finger as the template. Many proposals about how the performance and the security of the system can be improved are also presented.

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Filla, David. "Biometrie otisku prstu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-219256.

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This project deals with fingerprint biometrics. Describes the origin and significance of ridges. Project denote the significance and detection of singular points. The way of classication fingerprint to the vlase usány by the singular points. It contains a list of types of minutiae and their detection. There is basic methods for matching fingerprints. The minutae-based matching method is realize in program Matlab.
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Blommé, Johan. "Evaluation of biometric security systems against artificial fingers." Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1145.

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Verification of users’ identities are normally carried out via PIN-codes or ID- cards. Biometric identification, identification of unique body features, offers an alternative solution to these methods.

Fingerprint scanning is the most common biometric identification method used today. It uses a simple and quick method of identification and has therefore been favored instead of other biometric identification methods such as retina scan or signature verification.

In this report biometric security systems have been evaluated based on fingerprint scanners. The evaluation method focuses on copies of real fingers, artificial fingers, as intrusion method but it also mentions currently used algorithms for identification and strengths and weaknesses in hardware solutions used.

The artificial fingers used in the evaluation were made of gelatin, as it resembles the surface of human skin in ways of moisture, electric resistance and texture. Artificial fingers were based on ten subjects whose real fingers and artificial counterpart were tested on three different fingerprint scanners. All scanners tested accepted artificial fingers as substitutes for real fingers. Results varied between users and scanners but the artificial fingers were accepted between about one forth and half of the times.

Techniques used in image enhancement, minutiae analysis and pattern matching are analyzed. Normalization, binarization, quality markup and low pass filtering are described within image enhancement. In minutiae analysis connectivity numbers, point identification and skeletonization (thinning algorithms) are analyzed. Within pattern matching, direction field analysis and principal component analysis are described. Finally combinations of both minutiae analysis and pattern matching, hybrid models, are mentioned.

Based on experiments made and analysis of used techniques a recommendation for future use and development of fingerprint scanners is made.

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Mohamed, Abdul Cader Akmal Jahan. "Finger biometric system using bispectral invariants and information fusion techniques." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134464/1/Akmal%20Jahan_Mohamed%20Abdul%20Cader_Thesis.pdf.

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Contactless hand biometric systems are better accepted than contact prints as they are hygienic and accelerate data acquisition. This research is one of the few investigating contactless biometrics of the full hand by proposing a novel algorithm based on ridge orientation information along lines connecting key points, higher order spectral features, and fusion. It was investigated with contactless finger images acquired from 81 users, and found to be robust to hand orientation and image size, and provide acceptable performance using two fingers with fusion. The algorithm has potential to use in high throughput applications where contact sensing may be slow.
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KUMAR, AJAY. "FINGERPRINT RECOGNITION." Thesis, 2011. http://dspace.dtu.ac.in:8080/jspui/handle/repository/13880.

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M.TECH
The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. Automatic minutiae detection is an extremely critical process, especially in low-quality fingerprints where noise and contrast deficiency can originate pixel configurations similar to minutiae or hide real minutiae. The technique describe here, is consists of minutiae extraction and minutiae matching. the minutia extraction algorithm proposed here, is much faster and more reliable and implemented for extracting features from an input fingerprint image. For minutia matching, an alignment-based elastic matching algorithm has been developed. The proposed algorithm results in an efficient, robust and fast representation of fingerprints which accurately retains the fidelity in minutiae (ridge endings and bifurcations).
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TIEN, SHAO-HUA, and 田韶華. "Fingerprint Recognition Method Based on Fusion of Spatial Statistical Features and Minutia Matching." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/x98wy4.

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碩士
國立中央大學
資訊工程學系在職專班
103
Product get smaller and technological improve every day, relatively small area of the fingerprint sensor to capture the DPI is also getting smaller and smaller, resolution or image complexity will affect the image of the fingerprint identification result, the traditional approach has been to identify a single one inadequate use of feature points presented in this recognition and non-recognition feature points plus two kinds of identification method to fusion, non-feature point identification method uses a statistical and probability neural network, coupled with training through fingerprint classification to achieve their goals in decision fusion experiments on the max and two-stage and other fusion methods, and finally decision fusion experiment error rate lower than the previous two individual identification party.
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Chen, Guan-you, and 陳冠佑. "Fingerprint Minutiae Matching with LBP Texture." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/86076627486817221560.

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Анотація:
碩士
國立中央大學
資訊工程學系
103
The minutiae-based matching is the main stream method in fingerprint recognition which is an algorithm tries to find out the matched minutiae between two fingerprints. According to the amount of matched Minutiae, we can determine whether these two fingerprints are same or not. Due to the noise in the fingerprint images, image pre-processing has to be proceeded in order to reduce the noises, otherwise those extracted spurious Minutiae will influence the correctness of results. Therefore, recently, there are plenty of methods proposing the combination of multiple fingerprint features to identify two fingerprints. In this paper, we propose an improved minutiae matching method by integrating the Local Binary Pattern (LBP) feature, which compares LBP texture features in the adjacent region of Minutiae in order to select the reference points we want and guarantee the precision of identification. The experiment results show that our method can outperform the traditional Minutiae-based method. In FVC2000 and the fingerprint database we build, both Error Equal Rate (EER) of the outcomes are better than the traditional way.
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Gwo-Cheng, Chao, and 趙國成. "A Fingerprint Verification System based on Minutiae Matching." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/69420330587510232317.

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Анотація:
碩士
國立臺灣科技大學
資訊工程系
93
Fingerprint based identification has been known and used for a long time. Owing to the uniqueness and immutability, fingerprints are today the most widely used biometric features. Fingerprint verification is based on the minutiae of the fingerprints. Extracting minutiae from fingerprint patterns is one of the most important steps in automatic system for fingerprint identification. This model, adopted in most automatic systems, is based on a two-class minutiae classification: endpoint and bifurcation .The accuracy of the minutiae will affect the correctness of the fingerprint matching; therefore the fingerprint enhancement will be done to reduce the false minutiae. In this thesis, an effective fingerprint verification system is implemented by passing the image pre/post-processing, feature extraction and matching processes. We describe an improved method on fingerprint enhancement and post-processing. We directly enhance the fingerprint on gray-scale image and reduce the most false minutiae in the post-processing step. For minutiae matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the corresponding point pairs between input and template minutiae. It also has the ability to adaptively compensate for the nonlinear deformations between fingerprints.
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Книги з теми "MINUTIA MATCHING"

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Michael, McCabe R., and National Institute of Standards and Technology (U.S.), eds. Fingerprint minutiae from latent and matching tenprint images. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 2000.

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Fail Safe Employment Techniques (Firm), ed. Fail safe employment techniques: A guide to the world of work : matching skills to more than 20,000 jobs : an unbeatable method to scan thousands of potential careers in minutes. Bellevue, Wash: Fail Safe Employment Techniques, 1985.

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NIST SPECIAL DATABASE 27 FINGERPRINT MINUTIAE FROM LATENT MATCHING TENPRINT IMAGES... NISTIR 6534... U.S. DEPARTMENT OF COMMERCE. [S.l: s.n., 2001.

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4

Rush, David N., and Peter W. Nickerson. Rejection. Edited by Jeremy R. Chapman. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0283_update_001.

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Rejection of the transplanted kidney is an important cause of graft loss despite modern cross-matching techniques and immunosuppressive agents. The incidence of acute rejection episodes in the first post-transplant year is down to less than 15% in low-risk recipients, but as many as one-third of allograft losses over 10 years result from alloimmunity. Rejection may occur at any time following transplantation, from minutes—hyperacute, to days—acute, or in the longer term—chronic. Rejection can be predominantly through either T-cell-mediated or antibody-mediated mechanisms. It may present clinically as either abrupt or insidious dysfunction of the graft, or it may be subclinical and thus silent, detected only by protocol biopsy or other technology. The prevention and treatment of T-cell-mediated rejection is usually successful with current immunosuppressive agents. Antibody-mediated rejection, on the other hand, is not easily treated and is the principal cause of late renal allograft loss. This chapter presents the concepts and details of this central issue in clinical transplantation.
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Sciences, Planet of. 100 Days of Telling the Time - Practice Worksheets Workbook with Answers ,fill in the-Blank, Drawing Hands on a Clock Face : Ages 7-9: Hours, Quarter Hours, Five Minutes, Minutes, Matching Times. Independently Published, 2020.

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Muders, Thomas, and Christian Putensen. Pressure-controlled mechanical ventilation. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0096.

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Beside reduction in tidal volume limiting peak airway pressure minimizes the risk for ventilator-associated-lung-injury in patients with acute respiratory distress syndrome. Pressure-controlled, time-cycled ventilation (PCV) enables the physician to keep airway pressures under strict limits by presetting inspiratory and expiratory pressures, and cycle times. PCV results in a square-waved airway pressure and a decelerating inspiratory gas flow holding the alveoli inflated for the preset time. Preset pressures and cycle times, and respiratory system mechanics affect alveolar and intrinsic positive end-expiratory (PEEPi) pressures, tidal volume, total minute, and alveolar ventilation. When compared with flow-controlled, time-cycled (‘volume-controlled’) ventilation, PCV results in reduced peak airway pressures, but higher mean airway. Homogeneity of regional peak alveolar pressure distribution within the lung is improved. However, no consistent data exist, showing PCV to improve patient outcome. During inverse ratio ventilation (IRV) elongation of inspiratory time increases mean airway pressure and enables full lung inflation, whereas shortening expiratory time causes incomplete lung emptying and increased PEEPi. Both mechanisms increase mean alveolar and transpulmonary pressures, and may thereby improve lung recruitment and gas exchange. However, when compared with conventional mechanical ventilation using an increased external PEEP to reach the same magnitude of total PEEP as that produced intrinsically by IRV, IRV has no advantage. Airway pressure release ventilation (APRV) provides a PCV-like squared pressure pattern by time-cycled switches between two continuous positive airway pressure levels, while allowing unrestricted spontaneous breathing in any ventilatory phase. Maintaining spontaneous breathing with APRV is associated with recruitment and improved ventilation of dependent lung areas, improved ventilation-perfusion matching, cardiac output, oxygenation, and oxygen delivery, whereas need for sedation, vasopressors, and inotropic agents and duration of ventilator support decreases.
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Частини книг з теми "MINUTIA MATCHING"

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Sarier, Neyire Deniz. "Private Minutia-Based Fingerprint Matching." In Information Security Theory and Practice, 52–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24018-3_4.

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Qi, Jin, Yangsheng Wang, Zhongchao Shi, Ke Xu, and Xuying Zhao. "Fingerprint Matching Integrating the Global Orientation Field with Minutia." In Biometric Authentication, 337–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_47.

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Medina-Pérez, Miguel Angel, Andrés Gutiérrez-Rodríguez, and Milton García-Borroto. "Improving Fingerprint Matching Using an Orientation-Based Minutia Descriptor." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 121–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10268-4_14.

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Cappelli, Raffaele, Matteo Ferrara, and Davide Maltoni. "Minutiae-Based Fingerprint Matching." In Intelligent Systems Reference Library, 117–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28457-1_7.

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Asha, S., and C. Chellappan. "Partial Fingerprint Matching Using Minutiae Subset." In Intelligent Computing, Networking, and Informatics, 445–52. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1665-0_42.

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Ratha, Nalini K., Jonathan H. Connell, and Ruud M. Bolle. "An Analysis of Minutiae Matching Strength." In Lecture Notes in Computer Science, 223–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45344-x_32.

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Parziale, Giuseppe, and Albert Niel. "A Fingerprint Matching Using Minutiae Triangulation." In Biometric Authentication, 241–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_34.

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Benhammadi, Farid, Hamid Hentous, Kadda Bey-Beghdad, and Mohamed Aissani. "Fingerprint Matching Using Minutiae Coordinate Systems." In Pattern Recognition and Image Analysis, 529–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492542_65.

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Chen, Jiali, and Zhenhua Guo. "Palmprint Matching by Minutiae and Ridge Distance." In Cloud Computing and Security, 371–82. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48674-1_33.

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Patel, Ronakkumar B., Dilendra Hiran, and Jayeshbhai Patel. "Biometric Fingerprint Recognition Using Minutiae Score Matching." In Lecture Notes on Data Engineering and Communications Technologies, 463–78. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4474-3_52.

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Тези доповідей конференцій з теми "MINUTIA MATCHING"

1

Xuefeng Liang and T. Asano. "Fingerprint Matching Using Minutia Polygons." In 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.571.

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Czovny, Raphael K., Olga R. P. Bellon, Luciano Silva, and Henrique S. G. Costa. "Minutia Matching using 3D Pore Clouds." In 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, 2018. http://dx.doi.org/10.1109/icpr.2018.8546036.

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Baig, Wajih Ullah, Umar Munir, Adeel Ejaz, and Kashif Sardar. "Minutia Texture Cylinder Codes for Fingerprint Matching." In 2019 International Conference on Frontiers of Information Technology (FIT). IEEE, 2019. http://dx.doi.org/10.1109/fit47737.2019.00024.

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Luo, Yuxuan, Jianjiang Feng, and Jie Zhou. "Fingerprint matching based on global minutia cylinder code." In 2014 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2014. http://dx.doi.org/10.1109/btas.2014.6996231.

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Lahby, Mohamed, Yassine Ismaili, Abdelbaki Attioui, and Abderrahim Sekkaki. "Performance analysis of minutia-based fingerprint matching algorithms." In 2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA). IEEE, 2016. http://dx.doi.org/10.1109/sita.2016.7772324.

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Wu, Chunsheng, Liu Zhigang, and Feng Caigang. "Palmprint Minutia Point Matching Algorithm and GPU Application." In The 5th International Conference on Computer Engineering and Networks. Trieste, Italy: Sissa Medialab, 2015. http://dx.doi.org/10.22323/1.259.0030.

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Wen, Wen, Zhi Qi, Zhi Li, Junhao Zhang, Yu Gong, and Peng Cao. "A Robust and Efficient Minutia-Based Fingerprint Matching Algorithm." In 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR). IEEE, 2013. http://dx.doi.org/10.1109/acpr.2013.43.

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Sutarno, Muhamad Visat, and Achmad Imam Kistijantoro. "Minutia cylinder code-based fingerprint matching optimization using GPU." In 2017 International Conference on Data and Software Engineering (ICoDSE). IEEE, 2017. http://dx.doi.org/10.1109/icodse.2017.8285880.

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JIN, SHENGPING, MEILAN ZENG, and DINGFANG CHEN. "THE FINGERPRINT IMAGE NOISE REDUCING AND MINUTIA MATCHING IN VERIFICATION." In Proceedings of the Third International Conference on WAA. World Scientific Publishing Company, 2003. http://dx.doi.org/10.1142/9789812796769_0120.

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Zang, Jiong, Jie Yuan, Fei Shi, and Si-dan Du. "A Fingerprint Matching Algorithm of Minutia Based on Local Characteristic." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.710.

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Звіти організацій з теми "MINUTIA MATCHING"

1

Williams, Thomas. Microbial Mating-type Matching memory Game. University of Dundee, 2023. http://dx.doi.org/10.20933/100001286.

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Анотація:
Did you know different microbes have different numbers of mating-types? Print and cut out the attached files to see if you can find all the matching mating-types in this fun memory game and discover more about the lives and appearances of viruses, bacteria, fungi, and protists! Play with 1-4 people age 2+, with each game lasting around 5 minutes.
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Mathew, Jijo K., Christopher M. Day, Howell Li, and Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.

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Анотація:
Agencies use a variety of technologies and data providers to obtain travel time information. The best quality data can be obtained from second-by-second tracking of vehicles, but that data presents many challenges in terms of privacy, storage requirements and analysis. More frequently agencies collect or purchase segment travel time based upon some type of matching of vehicles between two spatially distributed points. Typical methods for that data collection involve license plate re-identification, Bluetooth, Wi-Fi, or some type of rolling DSRC identifier. One of the challenges in each of these sampling techniques is to employ filtering techniques to remove outliers associated with trip chaining, but not remove important features in the data associated with incidents or traffic congestion. This paper describes a curated data set that was developed from high-fidelity GPS trajectory data. The curated data contained 31,621 vehicle observations spanning 42 days; 2550 observations had travel times greater than 3 minutes more than normal. From this baseline data set, outliers were determined using GPS waypoints to determine if the vehicle left the route. Two performance measures were identified for evaluating three outlier-filtering algorithms by the proportion of true samples rejected and proportion of outliers correctly identified. The effectiveness of the three methods over 10-minute sampling windows was also evaluated. The curated data set has been archived in a digital repository and is available online for others to test outlier-filtering algorithms.
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Dorna, Guadalupe, and Gastón Gertner. Argentina: Lessons Learned from a Remote Tutoring Pilot. Inter-American Development Bank, September 2023. http://dx.doi.org/10.18235/0005110.

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Анотація:
This document presents the results of a remote tutoring program implemented in Argentina (in the City of Buenos Aires and the Province of Mendoza). Tutoring sessions were delivered by public teacher college institutions, covering foundational mathematics content through a 20-minute weekly phone call for an 8-weeks period. The study focused on families with children enrolled in primary public schools aged 10 to 13 years old. We estimate null effects in academic performance in our intention to treat and treatment on the treated estimators from a randomized controlled trial among students in the City of Buenos Aires. The matching estimator identifies an average impact of tutoring for the treated group of 0.15 standard deviations in academic performance, which is statistically significant at 15%. We also explore the relationship between the number of sessions completed by students and the level of commitment of caregivers and tutors serving such students, showing that tutors' commitment is a significant predictor of completed sessions by students. Finally, we provide some recommendations for scaling up in Argentina and the region.
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