Search results for: LSB Matching

Authors: Jamuna Bhandari

Abstract:

String matching also known as pattern matching is one of primary concept for network security. In this area the effectiveness and efficiency of string matching algorithms is important for applications in network security such as network intrusion detection, virus detection, signature matching and web content filtering system. This paper presents brief review on some of string matching techniques used for network security.

Keywords: Filtering, honeypot, network telescope, pattern, string, signature.

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Authors: Pinaki Pratim Acharjya, Dibyendu Ghoshal

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Image matching methods play a key role in deciding correspondence between two image scenes. This paper presents a method for the matching of digital images using mathematical morphology. The proposed method has been applied to real life images. The matching process has shown successful and promising results.

Keywords: Digital image, gradients, image matching, mathematical morphology.

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Authors: Huynh Quyet Thang, Vo Sy Nam

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Schema matching plays a key role in many different applications, such as schema integration, data integration, data warehousing, data transformation, E-commerce, peer-to-peer data management, ontology matching and integration, semantic Web, semantic query processing, etc. Manual matching is expensive and error-prone, so it is therefore important to develop techniques to automate the schema matching process. In this paper, we present a solution for XML schema automated matching problem which produces semantic mappings between corresponding schema elements of given source and target schemas. This solution contributed in solving more comprehensively and efficiently XML schema automated matching problem. Our solution based on combining linguistic similarity, data type compatibility and structural similarity of XML schema elements. After describing our solution, we present experimental results that demonstrate the effectiveness of this approach.

Keywords: XML Schema, Schema Matching, SemanticMatching, Automatic XML Schema Matching.

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Authors: Katrin Zaiß, Tim Schlüter, Stefan Conrad

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Ontology Matching is a task needed in various applica-tions, for example for comparison or merging purposes. In literature,many algorithms solving the matching problem can be found, butmost of them do not consider instances at all. Mappings are deter-mined by calculating the string-similarity of labels, by recognizinglinguistic word relations (synonyms, subsumptions etc.) or by ana-lyzing the (graph) structure. Due to the facts that instances are oftenmodeled within the ontology and that the set of instances describesthe meaning of the concepts better than their meta information,instances should definitely be incorporated into the matching process.In this paper several novel instance-based matching algorithms arepresented which enhance the quality of matching results obtainedwith common concept-based methods. Different kinds of formalismsare use to classify concepts on account of their instances and finallyto compare the concepts directly.KeywordsInstances, Ontology Matching, Semantic Web

Keywords: Instances, Ontology Matching, Semantic Web

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Authors: Zhengnan Shi

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In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).

Keywords: self-stabilization, popular matching, algorithm, distributed computing, fault tolerance

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Authors: Yuzana, Khin Marlar Tun

Abstract:

Personal name matching system is the core of essential task in national citizen database, text and web mining, information retrieval, online library system, e-commerce and record linkage system. It has necessitated to the all embracing research in the vicinity of name matching. Traditional name matching methods are suitable for English and other Latin based language. Asian languages which have no word boundary such as Myanmar language still requires sounds alike matching system in Unicode based application. Hence we proposed matching algorithm to get analogous sounds alike (phonetic) pattern that is convenient for Myanmar character spelling. According to the nature of Myanmar character, we consider for word boundary fragmentation, collation of character. Thus we use pattern conversion algorithm which fabricates words in pattern with fragmented and collated. We create the Myanmar sounds alike phonetic group to help in the phonetic matching. The experimental results show that fragmentation accuracy in 99.32% and processing time in 1.72 ms.

Keywords: natural language processing, name matching, phonetic matching

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Authors: Bi Kun, Gu Nai-jie, Tu Kun, Liu Xiao-hu, Liu Gang

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Traditional parallel single string matching algorithms are always based on PRAM computation model. Those algorithms concentrate on the cost optimal design and the theoretical speed. Based on the distributed string matching algorithm proposed by CHEN, a practical distributed string matching algorithm architecture is proposed in this paper. And also an improved single string matching algorithm based on a variant Boyer-Moore algorithm is presented. We implement our algorithm on the above architecture and the experiments prove that it is really practical and efficient on distributed memory machine. Its computation complexity is O(n/p + m), where n is the length of the text, and m is the length of the pattern, and p is the number of the processors.

Keywords: Boyer-Moore algorithm, distributed algorithm, parallel string matching, string matching.

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Authors: Rajender Singh Chillar, Barjesh Kochar

Abstract:

All Text processing systems allow their users to search a pattern of string from a given text. String matching is fundamental to database and text processing applications. Every text editor must contain a mechanism to search the current document for arbitrary strings. Spelling checkers scan an input text for words in the dictionary and reject any strings that do not match. We store our information in data bases so that later on we can retrieve the same and this retrieval can be done by using various string matching algorithms. This paper is describing a new string matching algorithm for various applications. A new algorithm has been designed with the help of Rabin Karp Matcher, to improve string matching process.

Keywords: Algorithm, Complexity, Matching-patterns, Pattern, Rabin-Karp, String, text-processing.

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Authors: Shao-Tzu Huang, Chen-Chien Hsu, Wei-Yen Wang

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Matching high dimensional features between images is computationally expensive for exhaustive search approaches in computer vision. Although the dimension of the feature can be degraded by simplifying the prior knowledge of homography, matching accuracy may degrade as a tradeoff. In this paper, we present a feature matching method based on k-means algorithm that reduces the matching cost and matches the features between images instead of using a simplified geometric assumption. Experimental results show that the proposed method outperforms the previous linear exhaustive search approaches in terms of the inlier ratio of matched pairs.

Keywords: Feature matching, k-means clustering, scale invariant feature transform, linear exhaustive search.

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Authors: K.M.Goh, M.M.Mokji, S.A.R. Abu-Bakar

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Speeded-Up Robust Feature (SURF) is commonly used for feature matching in stereovision because of their robustness towards scale changes and rotational changes. However, SURF feature cannot cope with large viewpoint changes or skew distortion. This paper introduces a method which can help to improve the wide baseline-s matching performance in term of accuracy by rectifying the image using two vanishing points. Simplified orientation correction was used to remove the false matching..

Keywords: Affine, orientation, projective, SURF.

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Authors: Hossein Mardani, Neil Buchanan, Robert Cahill, Vincent Fusco

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In this paper, we study the input impedance characteristics of axial mode helical antennas to find an effective way for matching it to 50 Ω. The study is done on the important matching parameters such as like wire diameter and helix to the ground plane gap. It is intended that these parameters control the matching without detrimentally affecting the radiation pattern. Using transmission line theory, a simple broadband technique is proposed, which is applicable for perfect matching of antennas with similar design parameters. We provide design curves to help to choose the proper dimensions of the matching section based on the antenna’s unmatched input impedance. Finally, using the proposed technique, a 4-turn axial mode helix is designed at 2.5 GHz center frequency and the measurement results of the manufactured antenna will be included. This parametric study gives a good insight into the input impedance characteristics of axial mode helical antennas and the proposed impedance matching approach provides a simple, useful method for matching these types of antennas.

Keywords: Antenna, helix, helical, axial mode, wireless power transfer, impedance matching.

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Authors: Kim Nee Goh, Viknesh Kumar Naleyah

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Online trading is an alternative to conventional shopping method. People trade goods which are new or pre-owned before. However, there are times when a user is not able to search the items wanted online. This is because the items may not be posted as yet, thus ending the search. Conventional search mechanism only works by searching and matching search criteria (requirement) with data available in a particular database. This research aims to match current search requirements with future postings. This would involve the time factor in the conventional search method. A Car Matching Alert System (CMAS) prototype was developed to test the matching algorithm. When a buyer-s search returns no result, the system saves the search and the buyer will be alerted if there is a match found based on future postings. The algorithm developed is useful and as it can be applied in other search context.

Keywords: Matching algorithm, online trading, search, future postings, car matching

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Authors: André Smith, Amr Abdel-Dayem

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This paper presents an overview of the history and development of stereo matching algorithms. Details from its inception, up to relatively recent techniques are described, noting challenges that have been surmounted across these past decades. Different components of these are explored, though focus is directed towards the local matching techniques. While global approaches have existed for some time, and demonstrated greater accuracy than their counterparts, they are generally quite slow. Many strides have been made more recently, allowing local methods to catch up in terms of accuracy, without sacrificing the overall performance.

Keywords: Developmental survey, local stereo matching, stereo correspondence.

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Authors: Swapnil Gupta, C. Pandu Rangan

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A uniquely restricted matching is defined to be a matching M whose matched vertices induces a sub-graph which has only one perfect matching. In this paper, we make progress on the open question of the status of this problem on interval graphs (graphs obtained as the intersection graph of intervals on a line). We give an algorithm to compute maximum cardinality uniquely restricted matchings on certain sub-classes of interval graphs. We consider two sub-classes of interval graphs, the former contained in the latter, and give O(|E|^2) time algorithms for both of them. It is to be noted that both sub-classes are incomparable to proper interval graphs (graphs obtained as the intersection graph of intervals in which no interval completely contains another interval), on which the problem can be solved in polynomial time.

Keywords: Uniquely restricted matching, interval graph, design and analysis of algorithms, matching, induced matching, witness counting.

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Authors: Jason Zalev, Reza Sedaghat

Abstract:

This paper describes a complex energy signal model that is isomorphic with digital human fingerprint images. By using signal models, the problem of fingerprint matching is transformed into the signal processing problem of finding a correlation between two complex signals that differ by phase-rotation and time-scaling. A technique for minutiae matching that is independent of image translation, rotation and linear-scaling, and is resistant to missing minutiae is proposed. The method was tested using random data points. The results show that for matching prints the scaling and rotation angles are closely estimated and a stronger match will have a higher correlation.

Keywords: Affine Invariant, Fingerprint Recognition, Matching, Minutiae.

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Authors: Shahram Mohammadi, Ali Frajzadeh

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A lot of matching algorithms with different characteristics have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. In this paper we introduce a novel approach for feature extraction in which the extracted features are independent of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher speed and accuracy. In this new approach first for any fingerprint a reference point and a reference orientation is determined and then based on this information features are converted into polar coordinates. Due to high speed and accuracy of this approach and small volume of extracted features and easily execution of matching operation this approach is the most appropriate for real time applications.

Keywords: Matching, Minutiae, Reference point, Reference orientation

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Authors: Raju Bhukya, DVLN Somayajulu

Abstract:

Pattern matching is one of the fundamental applications in molecular biology. Searching DNA related data is a common activity for molecular biologists. In this paper we explore the applicability of a new pattern matching technique called Index based Forward Backward Multiple Pattern Matching algorithm(IFBMPM), for DNA Sequences. Our approach avoids unnecessary comparisons in the DNA Sequence due to this; the number of comparisons of the proposed algorithm is very less compared to other existing popular methods. The number of comparisons rapidly decreases and execution time decreases accordingly and shows better performance.

Keywords: Comparisons, DNA Sequence, Index.

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Authors: Chakkrit Snae

Abstract:

Names are important in many societies, even in technologically oriented ones which use e.g. ID systems to identify individual people. Names such as surnames are the most important as they are used in many processes, such as identifying of people and genealogical research. On the other hand variation of names can be a major problem for the identification and search for people, e.g. web search or security reasons. Name matching presumes a-priori that the recorded name written in one alphabet reflects the phonetic identity of two samples or some transcription error in copying a previously recorded name. We add to this the lode that the two names imply the same person. This paper describes name variations and some basic description of various name matching algorithms developed to overcome name variation and to find reasonable variants of names which can be used to further increasing mismatches for record linkage and name search. The implementation contains algorithms for computing a range of fuzzy matching based on different types of algorithms, e.g. composite and hybrid methods and allowing us to test and measure algorithms for accuracy. NYSIIS, LIG2 and Phonex have been shown to perform well and provided sufficient flexibility to be included in the linkage/matching process for optimising name searching.

Keywords: Data mining, name matching algorithm, nominaldata, searching system.

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Authors: Hajar Sadeghi, Payman Moallem, S. Amirhassn Monadjemi

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This paper presents a new feature based dense stereo matching algorithm to obtain the dense disparity map via dynamic programming. After extraction of some proper features, we use some matching constraints such as epipolar line, disparity limit, ordering and limit of directional derivative of disparity as well. Also, a coarseto- fine multiresolution strategy is used to decrease the search space and therefore increase the accuracy and processing speed. The proposed method links the detected feature points into the chains and compares some of the feature points from different chains, to increase the matching speed. We also employ color stereo matching to increase the accuracy of the algorithm. Then after feature matching, we use the dynamic programming to obtain the dense disparity map. It differs from the classical DP methods in the stereo vision, since it employs sparse disparity map obtained from the feature based matching stage. The DP is also performed further on a scan line, between any matched two feature points on that scan line. Thus our algorithm is truly an optimization method. Our algorithm offers a good trade off in terms of accuracy and computational efficiency. Regarding the results of our experiments, the proposed algorithm increases the accuracy from 20 to 70%, and reduces the running time of the algorithm almost 70%.

Keywords: Chain Correspondence, Color Stereo Matching, Dynamic Programming, Epipolar Line, Stereo Vision.

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Authors: Yuan Zheng

Abstract:

3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information.

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Authors: Andr´as R¨ovid, Takeshi Hashimoto

Abstract:

The paper focuses on the problem of the point correspondence matching in stereo images. The proposed matching algorithm is based on the combination of simpler methods such as normalized sum of squared differences (NSSD) and a more complex phase correlation based approach, by considering the noise and other factors, as well. The speed of NSSD and the preciseness of the phase correlation together yield an efficient approach to find the best candidate point with sub-pixel accuracy in stereo image pairs. The task of the NSSD in this case is to approach the candidate pixel roughly. Afterwards the location of the candidate is refined by an enhanced phase correlation based method which in contrast to the NSSD has to run only once for each selected pixel.

Keywords: Stereo matching, Sub-pixel accuracy, phase correlation, SVD, NSSD.

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Authors: Weitao Lin

Abstract:

To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: Natural Language Processing, Chinese event detection, rules matching, dependency parsing.

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Authors: Ibrahim El rube'

Abstract:

In this paper, a method for matching image segments using triangle-based (geometrical) regions is proposed. Triangular regions are formed from triples of vertex points obtained from a keypoint detector (SIFT). However, triangle regions are subject to noise and distortion around the edges and vertices (especially acute angles). Therefore, these triangles are expanded into parallelogramshaped regions. The extracted image segments inherit an important triangle property; the invariance to affine distortion. Given two images, matching corresponding regions is conducted by computing the relative affine matrix, rectifying one of the regions w.r.t. the other one, then calculating the similarity between the reference and rectified region. The experimental tests show the efficiency and robustness of the proposed algorithm against geometrical distortion.

Keywords: Image matching, key point detection, affine invariant, triangle-shaped segments.

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Authors: Bokyung Sung, Jungsoo Kim, Jinman Kwun, Junhyung Park, Jihye Ryeo, Ilju Ko

Abstract:

In this paper, we propose a practical digital music matching system that is robust to variation in sound qualities. The proposed system is subdivided into two parts: client and server. The client part consists of the input, preprocessing and feature extraction modules. The preprocessing module, including the music onset module, revises the value gap occurring on the time axis between identical songs of different formats. The proposed method uses delta-grouped Mel frequency cepstral coefficients (MFCCs) to extract music features that are robust to changes in sound quality. According to the number of sound quality formats (SQFs) used, a music server is constructed with a feature database (FD) that contains different sub feature databases (SFDs). When the proposed system receives a music file, the selection module selects an appropriate SFD from a feature database; the selected SFD is subsequently used by the matching module. In this study, we used 3,000 queries for matching experiments in three cases with different FDs. In each case, we used 1,000 queries constructed by mixing 8 SQFs and 125 songs. The success rate of music matching improved from 88.6% when using single a single SFD to 93.2% when using quadruple SFDs. By this experiment, we proved that the proposed method is robust to various sound qualities.

Keywords: Digital Music, Music Matching, Variation in Sound Qualities, Robust Matching method.

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Authors: K. Thulasimani, K. G. Srinivasagan

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Driver fatigue is an important factor in the increasing number of road accidents. Dynamic template matching method was proposed to address the problem of real-time driver fatigue detection system based on eye-tracking. An effective vision based approach was used to analyze the driver’s eye state to detect fatigue. The driver fatigue system consists of Face detection, Eye detection, Eye tracking, and Fatigue detection. Initially frames are captured from a color video in a car dashboard and transformed from RGB into YCbCr color space to detect the driver’s face. Canny edge operator was used to estimating the eye region and the locations of eyes are extracted. The extracted eyes were considered as a template matching for eye tracking. Edge Map Overlapping (EMO) and Edge Pixel Count (EPC) matching function were used for eye tracking which is used to improve the matching accuracy. The pixel of eyeball was tracked from the eye regions which are used to determine the fatigue state of the driver.

Keywords: Driver fatigue detection, Driving safety, Eye tracking, Intelligent transportation system, Template matching.

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Authors: Aleem Khalid Alvi, M. Yousuf Bin Azhar, Mehmood Usman, Suleman Mumtaz, Sameer Rafiq, RaziUr Rehman, Israr Ahmed

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Sign language recognition has been a topic of research since the first data glove was developed. Many researchers have attempted to recognize sign language through various techniques. However none of them have ventured into the area of Pakistan Sign Language (PSL). The Boltay Haath project aims at recognizing PSL gestures using Statistical Template Matching. The primary input device is the DataGlove5 developed by 5DT. Alternative approaches use camera-based recognition which, being sensitive to environmental changes are not always a good choice.This paper explains the use of Statistical Template Matching for gesture recognition in Boltay Haath. The system recognizes one handed alphabet signs from PSL.

Keywords: Gesture Recognition, Pakistan Sign Language, DataGlove, Human Computer Interaction, Template Matching, BoltayHaath

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Authors: Roman V. Yampolskiy, Venu Govindaraju

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Functioning of a biometric system in large part depends on the performance of the similarity measure function. Frequently a generalized similarity distance measure function such as Euclidian distance or Mahalanobis distance is applied to the task of matching biometric feature vectors. However, often accuracy of a biometric system can be greatly improved by designing a customized matching algorithm optimized for a particular biometric application. In this paper we propose a tailored similarity measure function for behavioral biometric systems based on the expert knowledge of the feature level data in the domain. We compare performance of a proposed matching algorithm to that of other well known similarity distance functions and demonstrate its superiority with respect to the chosen domain.

Keywords: Behavioral Biometrics, Euclidian Distance, Matching, Similarity Measure.

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Authors: Ali Alzaabi, Georges Alquié, Hussain Tassadaq, Ali Seba

Abstract:

This article presents the developments of efficient algorithms for tablet copies comparison. Image recognition has specialized use in digital systems such as medical imaging, computer vision, defense, communication etc. Comparison between two images that look indistinguishable is a formidable task. Two images taken from different sources might look identical but due to different digitizing properties they are not. Whereas small variation in image information such as cropping, rotation, and slight photometric alteration are unsuitable for based matching techniques. In this paper we introduce different matching algorithms designed to facilitate, for art centers, identifying real painting images from fake ones. Different vision algorithms for local image features are implemented using MATLAB. In this framework a Table Comparison Computer Tool “TCCT" is designed to facilitate our research. The TCCT is a Graphical Unit Interface (GUI) tool used to identify images by its shapes and objects. Parameter of vision system is fully accessible to user through this graphical unit interface. And then for matching, it applies different description technique that can identify exact figures of objects.

Keywords: Harris Extraction and SIFT Matching

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Authors: Andy Handouyahia, Tony Haddad, Frank Eaton

Abstract:

Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.

Keywords: Treatment effect, causal inference, observational studies, Propensity score based matching, Kernel Matching, Inverse Probability Weighting, Estimation methods for incremental effect.

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Authors: Jianwei Wu

Abstract:

Based on the one-bit-matching principle and by turning the de-mixing matrix into an orthogonal matrix via certain normalization, Ma et al proposed a one-bit-matching learning algorithm on the Stiefel manifold for independent component analysis [8]. But this algorithm is not adaptive. In this paper, an algorithm which can extract kurtosis and its sign of each independent source component directly from observation data is firstly introduced.With the algorithm , the one-bit-matching learning algorithm is revised, so that it can make the blind separation on the Stiefel manifold implemented completely in the adaptive mode in the framework of natural gradient.

Keywords: Independent component analysis, kurtosis, Stiefel manifold, super-gaussians or sub-gaussians.

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