Salil Prabhakar Fingerprint Classification and Matching Using A FilterBank

BIOMETRIC SYSTEMS, DESIGN AND APPLICATIONS Edited by Zahid Riaz. pot

Traditional recognition systems have the abilities to recognize the human using various techniques like feature based recognition, face geometry based recognition, classiﬁer design and model based methods. In Zhao et al. (2003) the authors give a comprehensive survey of face recognition and some commercially available face recognition software. Subspace projection method like PCA was ﬁrstly used by Sirvovich and Kirby Sirovich & Kirby (1987) , which were latterly adopted by M. Turk and A. Pentland introducing the famous idea of eigenfaces Turk & Pentland (1991). This chapter focuses on the modeling of human face using a three dimensional model for shape model ﬁtting, texture and temporal information extraction and then low dimensional parameters for recognition purposes. The model using shape and texture parameters is called Active Appearance Model (AAMs), introduced by Cootes et. al. Cootes et al. (1998)Edwards, Taylor & Cootes (1998). For face recognition using AAM, Edwards et al Edwards, Cootes & Taylor (1998) use weighted distance classiﬁer called Mahalanobis distance. In Edwards et al. (1996) the authors used separate information for shape and gray level texture. They isolate the sources of variation by maximizing the interclass variations using discriminant analysis, similar to Linear Discriminant Analysis (LDA), the technique which was used for Fisherfaces representation Belheumeur et al. (1997). Fisherface approach is similar to the eigenface approach however outperforms in the presence of illuminations. In Wimmer et al. (2009) the authors have utilized shape and temporal features collectively to form a feature vector for facial expressions recognition. These models utilize the shape information based on a point distribution of various landmarks points marked on the face image. Blanz et al. Blanz & Vetter (2003) use state-of-the-art morphable model from laser scaner data for face recognition by synthesizing 3D face. This model is not as efﬁcient as AAM but more realistic. In our approach a wireframe model known as Candide-III Ahlberg (2001) has been utilized. In order to perform face recognition applications many researchers have applied model based approach. Riaz et al Riaz, Mayer, Wimmer, Beetz & Radig (2009) apply similar features for explaining face recognition using 2D model. They use expression invariant technique for face recognition, which is also used in 3D scenarios by Bronstein et al Bronstein et al. (2004) without 3D reconstruction of the faces and using geodesic distance. Park et. al. Park & Jain (2007) apply 3D model for face recognition on videos from CMU Face in Action (FIA) database. They reconstruct a 3D model acquiring views from 2D model ﬁtting to the images.

ADVANCES IN DATA MINING KNOWLEDGE DISCOVERY AND APPLICATIONS pot

Figure 35. Graph between ‘calculated seasonal index’ and ‘average index’ of ‘Sales’ dataset 6. Conclusion The book chapter presents a unified data mining theory and then the mathematical formulation of the unified data mining theory (UDMT). The data mining processes; clustering, classification and visualization are unified by means of mathematical functions. The chosen data mining algorithms are proved to be as functions i.e. the algorithms are used as functions. The first function takes the set of data as input, applies K-means clustering data mining algorithm and produces the set of clusters as output. The second function takes the set of clusters as input, applies the C4.5 (Decision Tree) data mining algorithm and produces the set of rules as output and finally the third function takes the set of rules as input, applies data visualization data mining algorithm and produces the set of 2D graphs as output. The functions are the mappings from the set of data to the set of clusters to the set of rules to the set of 2D graphs. From the set of 2D graphs one can interpret and evaluate the results to discover the knowledge i.e. the knowledge is extracted from the given dataset through the unified process of the composition of clustering, classification and visualization followed by interpretation and evaluation of the results. Thus, we attempt to unify the processes of data mining life cycle. In summary we can say, first pass the set of data through the composition of clustering, classification and visualization and then the obtained results are interpreted and evaluated to extract the knowledge. The proposed unified data mining theory covers all the pertinent essentials of the unified theory i.e. generates truly applicable explanations and predictions of the real world problems and does not contradict itself, therefore, we can say that it is comprehensiveness, precise, consistent and correct. The UDMT is tested on variety of datasets and the knowledge is discovered through the unified processes of data mining. On the basis of UDMT, a tool namely; UDMTool, multiagent systems, is developed, which takes dataset as input and

BÁO CÁO TOÁN HỌC: " PARITY SYSTEMS AND THE DELTA-MATROID INTERSECTION PROBLEM" POT

If (U, Ω) is a paired set, then for every element u in U , we denote by u e the element that belongs to the same pair as u and is distinct from u. Consider a pair of 2-matroids, Q 1 = (U, Ω, r 1 ) and Q 2 = (U, Ω, r 2 ), defined on the same partitioned set (U, Ω). Set R = r 1 + r 2 . Then P = (U, Ω, R) is a parity system, which we call the sum of Q 1 and Q 2 . Furthermore a solution to Problem 3.8 for P will give rise to a solution to Problem 2.7 for Q 1 and Q 2 . We shall be especially interested in the case when P is a sum of a 2-matroid Q = (U, Ω, r) and the converse 2-matroid Q e = (U, Ω, r), where e r e is defined by the relation r(A) = e r( A), for every subtransversal e A of Ω. In this case ν(P ) = | Ω | if and only if Q has two complementary bases. Thus Problem 3.8

BÁO CÁO SINH HỌC RESEARCH ARTICLE AUDIO SIGNAL PROCESSING USING TIME FREQUENCY APPROACHES CODING CLASSIFICATION FINGERPRINTING AND WATERMARKING PPTX

(c) Figure 10: Octave distribution over three frequency bands for a rock signal. To further improve the discriminatory power of this parameter the distribution of this parameter is grouped into three frequency bands 0–5 kHz, 5–10 kHz, and 10–20 kHz. This is done since analyzing the audio signals in subbands will provide more precise information about their audio characteristics [ 49 ]. The bounds for frequency bands were arrived considering the fact that most of the audio content lies well within 10 kHz range so this band needs to be looked more in detail hence broken further into 0–5 kHz and 5 kHz to 10 kHz and the remaining as one band between 10 kHz to 20 kHz. By this frequency division we get an indirect measure of signal envelope contribution from each frequency band. From Figure 9 even though we see di ﬀ erence in the distribution of octaves between rock-like and classical music, it becomes more evident when the distribution is divided into three frequency bands as shown for a sample rock and a classical signal in Figures 10 and 11 . Dividing the octave distribution into frequency bands basically reveal the pattern in which the temporal structures occur over the range of frequencies. As music is the combination of di ﬀ erent temporal structures with di ﬀ erent frequencies occurring at same or di ﬀ erent time instants, each type of music exhibit a unique average pattern. Based on the subtle di ﬀ erences between patterns to be detected, the division of octave distribution over fine frequency intervals and the dimension of the feature set can be controlled.

GIÁO ÁN 8 (TUẦN 24)

- Ask Ss to work in pairs , asking and answering the questions ( Using the information in the matching ) - Call on some pairs to demonstrate for the class.. 4.Consolidation:[r]

WIMAX NEW DEVELOPMENTS 2011 PART 7 DOC

Fig. 18. Measured results of 3.3~3.6GHz mini WiMAX bandpass filter Fig. 19. Measured results of 3.0~3.6GHz high performance WiMax bandpass filter The band pass filter in Figure 17 b) has performances with pass band from 3.0GHz~3.6GHz with minimum insertion loss of less than 2.5dB and ultra wide stop band from 3.8GHz to 10GHz as shown in Figure 19. The stop band rejection is better than 55dB from 4GHz to 9.5 GHz. The band pass filter has compact size of 25mm X 15mm X 1.5 mm. The other strength is the self-packaging format of surface mounting which is convenient for integration and free of RF leakage.

STRINGS AND PATTERN MATCHING PATTERN MATCHING

˚ Đ Đ ã ke ã ke á t thu á t thu ù c qua ù c qua ù ù tr tr ì ì nh t nh t ì ì m kie m kie á m ch á m ch ư ư a a ? ? ̈ ̈ Đe Đ e å å traû tra û lơ lơ øi nh i như ø ư õng câu ho õng câu ho ûi trên ta ca i trên ta caà û àn n quay quay la la ïi toa i toa ï ùn n ù ho

ASSESSING THE ACCURACY OF REMOTELY SENSED DATA - CHAPTER 5 PPT

In this normalization process, differences in sample sizes used to generate the matrices are eliminated and therefore, individual cell values within the matrix are directly comparable. In addition, because as part of the iterative process, the rows and columns are totaled (i.e., marginals), the resulting normalized matrix is more indicative of the off-diagonal cell values (i.e., the errors of omission and commis- sion). In other words, all the values in the matrix are iteratively balanced by row and column, thereby incorporating information from that row and column into each individual cell value. This process then changes the cell values along the major diagonal of the matrix (correct classifications), and therefore a normalized overall accuracy can be computed for each matrix by summing the major diagonal and dividing by the total of the entire matrix.

COMPUTATIONAL INTELLIGENCE IN AUTOMOTIVE APPLICATIONS EPISODE 1 PART 5 DOCX

4.3 Analysis of Object Actions and Interactions The objects are classiﬁed into persons and vehicles based on their footage area. The interaction among persons and vehicles can then be analyzed at semantic level as described in [29]. Each object is associated with spatio-temporal interaction potential that probabilistically describes the region in which the object can be subsequent time. The shape of the potential region depends on the type of object (vehicle/pedestrian) and speed (larger region for higher speed), and is modeled as a circular region around the current position. The intersection of interaction potentials of two objects represents the possibility of interaction between them as shown in Fig. 12a. They are categorized as safe or unsafe depending on the site context such as walkway or driveway, as well as motion context in terms of trajectories. For example, as shown in Fig. 12b, a person standing on walkway is normal scenario, whereas the person standing on driveway or road represents a potentially dangerous situation. Also, when two objects are moving fast, the possibility of collision is higher than when they are traveling slowly. This domain knowledge can be fed into the system in order to predict the severity of the situation.

CHAPTER 1 – PHYLOGENETIC AND FUNCTIONAL CLASSIFICATION OF ABC (ATP BINDING CASSETTE) SYSTEMS

CHAPTER 1 – PHYLOGENETIC AND FUNCTIONAL CLASSIFICATION OF ABC (ATP BINDING CASSETTE) SYSTEMS CHAPTER 1 – PHYLOGENETIC AND FUNCTIONAL CLASSIFICATION OF ABC (ATP BINDING CASSETTE) SYSTEMS CHAPTER 1 – PHYLOGENETIC AND FUNCTIONAL CLASSIFICATION OF ABC (ATP BINDING CASSETTE) SYSTEMS CHAPTER 1 – PHYLOGENETIC AND FUNCTIONAL CLASSIFICATION OF ABC (ATP BINDING CASSETTE) SYSTEMS CHAPTER 1 – PHYLOGENETIC AND FUNCTIONAL CLASSIFICATION OF ABC (ATP BINDING CASSETTE) SYSTEMS CHAPTER 1 – PHYLOGENETIC AND FUNCTIONAL CLASSIFICATION OF ABC (ATP BINDING CASSETTE) SYSTEMS

NETWORK SECURITY ALGORITHMS POT

into their Web server script directories. If perl is executable from the cgi directory, then an attacker can execute arbitrary commands on the Web server. This observation has led to a commonly used technique to detect attacks in so- called signature-based intrusion detection systems such as Snort. The idea is that a router or monitor has a set of rules, much like classifi ers. However, the Snort rules go beyond classifi ers by allowing a 5-tuple rule specifying the type of packet (e.g., port number equal to Web traffi c) plus an arbitrary string that can appear anywhere in the packet payload.

BÁO CÁO HÓA HỌC STUDY OF STABILITY OF TIME DOMAIN FEATURES FOR ELECTROMYOGRAPHIC PATTERN RECOGNITION PPTX

There are several limitations in this study. First, we lim- ited our study to time-domain features. The implementa- tion of frequency and time-frequency domain features with other types of classifiers is worth investigating in the future. Another limitation is that muscle fatigue during use of EMG-based HMIs is mainly due to repetitive, long- term muscle use; the muscle fatigue in this study was intensity-induced (short-term) because of the time con- straints for conducting the experiments. Additionally, because the level of muscle fatigue was not controlled across subjects, some subjects demonstrated very low level of muscle fatigue and slight changes in EMG signals. Based on the results of this study, relying only on "opti- mal" EMG features is not sufficient to overcome the vari- ations in EMG signals caused by the considered disturbances. Additional solutions, such as effective training strategies and adaptive pattern recognition [16], are promising, although the challenges in making these potential solutions clinically viable still exist. Continued engineering effort is demanded towards development of a practical and robust HMI based on EMG pattern recog- nition.

Developing Trustworthy Database Systems for Medical Care

Developing Trustworthy Database Systems for Medical Care includes about Security and Safety of Medical Care Environment; Access Control; Using Trust and Roles for Access Control; Classification Algorithm for Access Controlto Detect Malicious Users.

Advanced DNA fingerprint genotyping based on a model developed from real chip electrophoresis data

Large-scale comparative studies of DNA fingerprints prefer automated chip capillary electrophoresis over conventional gel planar electrophoresis due to the higher precision of the digitalization process. However, the determination of band sizes is still limited by the device resolution and sizing accuracy. Band matching, therefore, remains the key step in DNA fingerprint analysis. Most current methods evaluate only the pairwise similarity of the samples, using heuristically determined constant thresholds to evaluate the maximum allowed band size deviation; unfortunately, that approach significantly reduces the ability to distinguish between closely related samples. This study presents a new approach based on global multiple alignments of bands of all samples, with an adaptive threshold derived from the detailed migration analysis of a large number of real samples. The proposed approach allows the accurate automated analysis of DNA fingerprint similarities for extensive epidemiological studies of bacterial strains, thereby helping to prevent the spread of dangerous microbial infections.

SOLUTION MANUAL FOR BEGINNING ALGEBRA 1ST EDITION BY CLARK

Write the problem vertically, carefully matching place values, and subtract.. Write the problem vertically, carefully matching place values, and subtract.[r]

BÁO CÁO HÓA HỌC: " HYBRID 3D FRACTAL CODING WITH NEIGHBOURHOOD VECTOR QUANTISATION" POT

The model states that the content of the current image is related in some way to the contents of an adjacent image in the sequence by means of function F , this function be- ing the motion model employed by the estimation algorithm. This is intuitively a sensible assumption in that a scene con- sists of the same objects whose position varies slowly over time. The motion vectors are used to predict the next frame in a self-referencing manner and the residual between the signal and the prediction is expected to be sparse. Motion compensation, essentially DPCM on frames, therefore as- sumes certain stochastic relations. The proposed neighbour-

SUSTAINABLE RFID SOLUTIONS PART 7 PPTX

2. Related work Recent advances in Information and Communication Technology leads to rapid growth of technology especially in monitoring system to improve any glitch and errors. Single-based authentication system seems unable to monitor and authenticate effectively due to easy to hack and break out. Since that, the introduction of Radio Frequency Identification (RFID) has taken place as an alternative to the previous authentication systems such as biometrics and bar code system as well as smart card technologies. However, the integration of those technologies is expected to provide an effective monitoring system and a very high secured system that can perform and monitoring to mitigate the ratio of unauthorized person access. Nowadays, the trend of RFID is clear that the technology is playing an essential role especially in various field such as in engineering, medical, business, construction (Corporation, 2005; EraBuilder, 2006), library (Shahid, 2005), farming management (Bakery, et al., 2007) and etc. Several methods and technologies have been used to develop monitoring systems.

Assessing the feasibility of increasing spatial resolution of remotely sensed image using HNN super-resolution mapping combined with a forward model

The soft-classified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural netw ork (HNN) to predi[r]

APPROACHES FOR CLASSIFYING THE INDICATIONS FOR COLONOSCOPY USING DETAILED CLINICAL DATA

Accurate indication classification is critical for obtaining unbiased estimates of colonoscopy effectiveness and quality improvement efforts, but there is a dearth of published systematic classification approaches.

BÁO CÁO HÓA HỌC RESEARCH ARTICLE PHONEME AND SENTENCE LEVEL ENSEMBLES FOR SPEECH RECOGNITION POT

6.1.2. Error Expectation for Boosting. In traditional super- vised settings we are provided with a set of examples and labels, which constitute our training set, and thus it is possible to apply algorithms such as boosting. However, this becomes problematic when labels are noisy; (see, e.g., [ 35 ]). Such an example is a typical speech recognition data set. Most of the time such a data set is composed of a set of sentences, with a corresponding set of transcriptions. However, while the transcriptions may be accurate as far as the intention of the speakers or the hearing of the transcriber is concerned, subsequent translation of the transcription into phonetic labels is bound to be error prone, as it is quite possible for either the speaker to mispronounce words, or for the model that performs the automatic segmentation to make mistakes. In such a situation, adapting a model so that it minimises the errors made on the segmented transcriptions might not automatically lead into a model that minimises the word error rate, which is the real goal of a speech recognition system.

BÁO CÁO HÓA HỌC RESEARCH ARTICLE PARAMETRIC TIME FREQUENCY ANALYSIS AND ITS APPLICATIONS IN MUSIC CLASSIFICATION PDF

Copyright © 2010 Ying Shen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Analysis of nonstationary signals, such as music signals, is a challenging task. The purpose of this study is to explore an e ﬃ cient and powerful technique to analyze and classify music signals in higher frequency range (44.1 kHz). The pursuit methods are good tools for this purpose, but they aimed at representing the signals rather than classifying them as in Y. Paragakin et al., 2009. Among the pursuit methods, matching pursuit (MP), an adaptive true nonstationary time-frequency signal analysis tool, is applied for music classification. First, MP decomposes the sample signals into time-frequency functions or atoms. Atom parameters are then analyzed and manipulated, and discriminant features are extracted from atom parameters. Besides the parameters obtained using MP, an additional feature, central energy, is also derived. Linear discriminant analysis and the leave-one-out method are used to evaluate the classification accuracy rate for di ﬀ erent feature sets. The study is one of the very few works that analyze atoms statistically and extract discriminant features directly from the parameters. From our experiments, it is evident that the MP algorithm with the Gabor dictionary decomposes nonstationary signals, such as music signals, into atoms in which the parameters contain strong discriminant information su ﬃ cient for accurate and e ﬃ cient signal classifications.

THINKING IN C PHẦN 7 PPTX

The Main( ) method is prepended with an [STAThread] attribute, which sets the threading model to “single-threaded apartment.” We’ll discuss this attribute briefly in Chapter 15. The last method is the private method button1_Click( ), which was attached to button1’s Click event property in the InitializeComponent( ) method. In this method we directly manipulate the Text property of the label1 control. Some obvious observations about the output of the visual designer: It works with code that is both readable and (despite the warning) editable, the visual designer works within the monolithic InitializeComponent( ) except that it creates event-handler methods that are in the same Control class being defined, and the code isn’t “tricky” other than the [STAThread] attribute and the Dispose( ) method (a method which is not necessary unless the Control or one of its subcontrols contains non-managed resources, as discussed in Chapter 5). Less obviously, taken together, the visual designer does implicitly impose “an overall ordering principle” to the system. The visual designer constructs

BÁO CÁO HÓA HỌC: " RESEARCH ARTICLE DIGITAL-SIGNAL-TYPE IDENTIFICATION USING AN EFFICIENT IDENTIFIER" PPT

In the past, signal-type identification relied mostly on operators scanning the radio frequency spectrum with a wide-band receiver and checking it visually on some sort of display [ 1 ]. Clearly, these methods relied very much on the operators’ skills and abilities. These limitations then led to the development of more automated modulation recogniz- ers. One semiautomatic approach was to run the received signal through a number of demodulators and then have an operator to determine the modulation format by listening to the output of each demodulator. This approach is however not very practical anymore due to the new digital techniques that transfer both voice and data. Then techniques for au- tomatic signal-type identification started to emerge. The re-

Using internet resources in teaching Russian as a foreign language

The article talks about the urgency and practical necessity of using Internet resources in the teaching process of Russian as a foreign language, the advantages and classification of Internet resources.

BÁO CÁO Y HỌC QUALITY EVALUATION OF MYCELIAL ANTRODIA CAMPHORATA USING HIGH PERFORMANCE LIQUID CHROMATOGRAPHY HPLC COUPLED WITH DIODE ARRAY DETECTOR AND MASS SPECTROMETRY DAD MS PPS

Comprehensive chemical profile of AC The appropriate solvent should be used to extract as many groups of representative chemical classes and compounds as possible to depict the chemical profile of a medicinal material. Methanol and n-hexane were employed for extracting compounds from mycelial and fruiting body AC [18,21]. In the present study, five sol- vents of different polarities (water, methanol, ethanol, chloroform, and n-hexane) were evaluated with regard to their extraction efficiency. We found that methanol was able to extract most chemical compounds. This sol- vent was chosen to maximize the number of compounds extracted from our AC samples.

BÁO CÁO HÓA HỌC RESEARCH ARTICLE A NOVEL FACE SEGMENTATION ALGORITHM FROM A VIDEO SEQUENCE FOR REAL TIME FACE RECOGNITION POTX

be regarded as picture recognition algorithm. Therefore, face presented for recognition to these approaches should be e ﬃ - ciently segmented, that is, aligned properly to achieve a good recognition rate. The shape of the face di ﬀ ers from person to person. Segmenting a face uniformly, invariant to shape and pose, suitable for recognition, in real-time is therefore very challenging. Thus, face segmentation “online” in “real-time” sense from a video sequence still emerges as a challenging problem in the successful implementation of a face recogni- tion system. In this work, we have proposed a method which accommodates these practical situations to segment a face ef- ficiently from a video sequence. The segmented face is then handed over to a recognition algorithm based on principal component analysis and linear discriminant analysis to rec- ognize the person online.

Hệ thống đóng mở cửa bằng vân tay (có code) (english)

Fingerprint sensor modules, like the one in the following figure, madefingerprint recognition more accessible and easy to add to your projects. This meansthat is is super easy to make fingerprint collection, registration, comparison and search

ANTENNAS WITH NON-FOSTER MATCHING NETWORKS PHẦN 3 DOCX

A conceptual representation of the simplified ideal active matching network together with the two-port antenna model is shown conceptually in Fig. 12. The design equations for the components of the active matching network can be readily extracted from [3, 4] as follows. To design the active matching network, we first fit the antenna impedance to a simple model. Since the antenna is an electrically small monopole, the real part of the antenna impedance is assumed to vary as the square of frequency, and the imaginary part is modeled as a series LC.

Evaluation of the performance of supervised classification alogorithums in image classification

This study presents a land use pattern classification of satellite imagery. The Machine learning algorithms are overseen to pattern classifications. The supervised classifier is identifying the classes using trained set. Compiled classification has to be improvised using efficient algorithms with appropriate threshold values. The statistical significance of satellite image classifies into essential classes is of greater importance in remote sensing pattern classification methods.

Nghiên cứu, chế tạo mô đun phát tín hiệu mã pha trong radar dải sóng dm

A microwave power amplifier is fabricated that have output pulse power o f 90W using a rTiicroslrip tcclinique for input/outpul matching network..[r]

BÁO CÁO HÓA HỌC ROBUST RECONSTRUCTION ALGORITHM FOR COMPRESSED SENSING IN GAUSSIAN NOISE ENVIRONMENT USING ORTHOGONAL MATCHING PURSUIT WITH PARTIALLY KNOWN SUPPORT AND RANDOM SUBSAMPLING DOC

was 256. The average sparsity rate (k/N) of blocks in an image was 0.1. Peak signal-to- noise ratio (PSNR) and visual inspection were used for performance evaluation. All PSNRs shown in the graph were average PSNRs. Since the compression step in CS consists mostly of linear operations, Gaussian noise corrupting the signal in the earlier states is approximated as the Gaussian noise corrupting the compressed measurement vector. The state where the noise corrupted the image was not specified; therefore, we simply corrupted the compressed measurement vector by different level of Gaussian noise indicated by its variance ( σ 2 ).

báo cáo hóa học:" Robust reconstruction algorithm for compressed sensing in Gaussian noise environment using orthogonal matching pursuit with partially known support and random subsampling" pdf

DATA ANALYSIS AND MODELING FOR ENGINEERING AND MEDICAL APPLICATIONS

59 Table 4.3 Summary of parameter tuning result using validation dataset for heart disease.... 60 Table 4.4 Classification result correct classification on test set using cardiovascular [r]

MANIPULATING TEXT

can format text into pages with header information such as date, time, file name, and page num- ber. Here is an example: $ dpkg-query -l | sort | pr --column=2 | less Paginate package list in 2 cols In this example, the rpm -qa command lists all software packages installed on your system and pipes that list to the sort command, to be sorted alphabetically. Next that list is piped to the pr command, which converts the single-column list into two columns ( --columns=2 ) and paginates it. Finally, the less command enables you to page through the text.

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