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Journal articles on the topic 'K-character'

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1

Wijaya, Aditya Surya, Nurul Chamidah, and Mayanda Mega Santoni. "Pengenalan Karakter Tulisan Tangan Dengan K-Support Vector Nearest Neighbor." IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 9, no. 1 (April 30, 2019): 33. http://dx.doi.org/10.22146/ijeis.38729.

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Handwritten characters are difficult to be recognized by machine because people had various own writing style. This research recognizes handwritten character pattern of numbers and alphabet using K-Nearest Neighbour (KNN) algorithm. Handwritten recognition process is worked by preprocessing handwritten image, segmentation to obtain separate single characters, feature extraction, and classification. Features extraction is done by utilizing Zone method that will be used for classification by splitting this features data to training data and testing data. Training data from extracted features reduced by K-Support Vector Nearest Neighbor (K-SVNN) and for recognizing handwritten pattern from testing data, we used K-Nearest Neighbor (KNN). Testing result shows that reducing training data using K-SVNN able to improve handwritten character recognition accuracy.
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Kim, Ju-Lee, and Fiona Murnaghan. "Character expansions and unrefined minimal K -types." American Journal of Mathematics 125, no. 6 (2003): 1199–234. http://dx.doi.org/10.1353/ajm.2003.0043.

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3

Jarvis, Tyler J., Ralph Kaufmann, and Takashi Kimura. "Stringy K-theory and the Chern character." Inventiones mathematicae 168, no. 1 (December 8, 2006): 23–81. http://dx.doi.org/10.1007/s00222-006-0026-x.

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4

Liu, Wen Bo, and Tao Wang. "The Character Recognition of Vehicle's License Plate Based on BP Neural Networks." Applied Mechanics and Materials 513-517 (February 2014): 3805–8. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3805.

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This paper based on license plate image preprocessing ,license plate localization, and character segment ,using BP neural network algorithm to identify the license plate characters. Through k-l algorithm of characters on the feature extraction and recognition of license plate character respectively then taking the extraction of license plate character features into the character classifier to the training. When the end of training, extracting the net-work weights and offset matrix, and storing in the computer. To take the identified character images input to the MATLAB, and with the preservation weights and offset matrix operations, obtain the final results of recognition.
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Conner, P. E., and Noriko Yui. "The Additive Characters of the Witt Ring of an Algebraic Number Field." Canadian Journal of Mathematics 40, no. 3 (June 1, 1988): 546–88. http://dx.doi.org/10.4153/cjm-1988-024-x.

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For an algebraic number field K there is a similarity between the additive characters defined on the Witt ring W(K), [20], [11], [17], [14, p. 131], and the local root numbers associated to a real orthogonal representation of the absolute Galois group of K, [18], [5]. Using results of Deligne and of Serre, [16], we shall derive in (5.3) a formula expressing the value, at a prime in K, of the additive character on a Witt class in terms of the rank modulo 2, the stable Hasse-Witt invariant and the local root number associated to the real quadratic character defined by the square class of the discriminant. Thus we are able to separate out the contributions made to the value of the additive character by each of the standard Witt class invariants.
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6

BUI, H. M., and MICAH B. MILINOVICH. "CENTRAL VALUES OF DERIVATIVES OF DIRICHLET L-FUNCTIONS." International Journal of Number Theory 07, no. 02 (March 2011): 371–88. http://dx.doi.org/10.1142/s1793042111004125.

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Let [Formula: see text] be the set of even, primitive Dirichlet characters ( mod q). Using the mollifier method, we show that L(k)(½, χ) ≠ 0 for almost all the characters [Formula: see text] when k and q are large. Here L(s, χ) is the Dirichlet L-function associated to the character χ.
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Cunningham, Clifton, and David Roe. "FROM THE FUNCTION-SHEAF DICTIONARY TO QUASICHARACTERS OF -ADIC TORI." Journal of the Institute of Mathematics of Jussieu 17, no. 1 (October 13, 2015): 1–37. http://dx.doi.org/10.1017/s1474748015000286.

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We consider the rigid monoidal category of character sheaves on a smooth commutative group scheme $G$ over a finite field $k$, and expand the scope of the function-sheaf dictionary from connected commutative algebraic groups to this setting. We find the group of isomorphism classes of character sheaves on $G$, and show that it is an extension of the group of characters of $G(k)$ by a cohomology group determined by the component group scheme of $G$. We also classify all morphisms in the category character sheaves on $G$. As an application, we study character sheaves on Greenberg transforms of locally finite type Néron models of algebraic tori over local fields. This provides a geometrization of quasicharacters of $p$-adic tori.
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8

Biswas, Sazzad Ali. "Epsilon factors of symplectic type characters in the wild case." Forum Mathematicum 33, no. 2 (February 20, 2021): 569–77. http://dx.doi.org/10.1515/forum-2020-0281.

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Abstract By work of John Tate we can associate an epsilon factor with every multiplicative character of a local field. In this paper, we determine the explicit signs of the epsilon factors for symplectic type characters of K × {K^{\times}} , where K / F {K/F} is a wildly ramified quadratic extension of a non-Archimedean local field F of characteristic zero.
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9

Bonanzinga, Maddalena, and Maria Vittoria Cuzzupè. "On topological groups with remainder of character k." Applied General Topology 17, no. 1 (April 11, 2016): 51. http://dx.doi.org/10.4995/agt.2016.4376.

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<p style="margin: 0px;">In [A.V. Arhangel'skii and J. van Mill, On topological groups with a first-countable remainder, Top. Proc. <span id="OBJ_PREFIX_DWT1099_com_zimbra_phone" class="Object">42 (2013), 157-163</span>] it is proved that the character of a non-locally compact topological group with a first countable remainder doesn't exceed $\omega_1$ and a non-locally compact topological group of character $\omega_1$ having a compactification whose reminder is first countable is given. We generalize these results in the general case of an arbitrary infinite cardinal k.</p><p style="margin: 0px;"> </p>
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10

Ong, Veronica, and Derwin Suhartono. "Using K-Nearest Neighbor in Optical Character Recognition." ComTech: Computer, Mathematics and Engineering Applications 7, no. 1 (March 1, 2016): 53. http://dx.doi.org/10.21512/comtech.v7i1.2223.

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The growth in computer vision technology has aided society with various kinds of tasks. One of these tasks is the ability of recognizing text contained in an image, or usually referred to as Optical Character Recognition (OCR). There are many kinds of algorithms that can be implemented into an OCR. The K-Nearest Neighbor is one such algorithm. This research aims to find out the process behind the OCR mechanism by using K-Nearest Neighbor algorithm; one of the most influential machine learning algorithms. It also aims to find out how precise the algorithm is in an OCR program. To do that, a simple OCR program to classify alphabets of capital letters is made to produce and compare real results. The result of this research yielded a maximum of 76.9% accuracy with 200 training samples per alphabet. A set of reasons are also given as to why the program is able to reach said level of accuracy.
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11

Hu, Jianxun, and Bai-Ling Wang. "Delocalized Chern character for stringy orbifold K-theory." Transactions of the American Mathematical Society 365, no. 12 (June 4, 2013): 6309–41. http://dx.doi.org/10.1090/s0002-9947-2013-05834-5.

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12

Athoillah, Muhammad. "K-Nearest Neighbor for Recognize Handwritten Arabic Character." Jurnal Matematika "MANTIK" 5, no. 2 (October 27, 2019): 83–89. http://dx.doi.org/10.15642/mantik.2019.5.2.83-89.

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Handwritten text recognition is the ability of a system to recognize human handwritten and convert it into digital text. Handwritten text recognition is a form of classification problem, so a classification algorithm such as Nearest Neighbor (NN) is needed to solve it. NN algorithms is a simple algorithm yet provide a good result. In contrast with other algorithms that usually determined by some hypothesis class, NN Algorithm finds out a label on any test point without searching for a predictor within some predefined class of functions. Arabic is one of the most important languages in the world. Recognizing Arabic character is very interesting research, not only it is a primary language that used in Islam but also because the number of this research is still far behind the number of recognizing handwritten Latin or Chinese research. Due to that's the background, this framework built a system to recognize handwritten Arabic Character from an image dataset using the NN algorithm. The result showed that the proposed method could recognize the characters very well confirmed by its average of precision, recall and accuracy.
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13

Tu, Jean-Louis, and Ping Xu. "Chern character for twisted K-theory of orbifolds." Advances in Mathematics 207, no. 2 (December 2006): 455–83. http://dx.doi.org/10.1016/j.aim.2005.12.001.

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14

Shanmugavel, Subramanian, Jagadeesh Kannan, Arjun Vaithilingam Sudhakar, and . "Handwritten Optical Character Extraction and Recognition from Catalogue Sheets." International Journal of Engineering & Technology 7, no. 4.5 (September 22, 2018): 36. http://dx.doi.org/10.14419/ijet.v7i4.5.20005.

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The dataset consists of 20000 scanned catalogues of fossils and other artifacts compiled by the Geological Sciences Department. The images look like a scanned form filled with blue ink ball pen. The character extraction and identification is the first phase of the research and in the second phase we are planning to use the HMM model to extract the entire text from the form and store it in a digitized format. We used various image processing and computer vision techniques to extract characters from the 20000 handwritten catalogues. Techniques used for character extraction are Erode, MorphologyEx, Dilate, canny edge detection, find Counters, Counter Area etc. We used Histogram of Gradients (HOGs) to extract features from the character images and applied k-means and agglomerative clustering to perform unsupervised learning. This would allow us to prepare a labelled training dataset for the second phase. We also tried converting images from RGB to CMYK to improve k-means clustering performance. We also used thresholding to extract blue ink characters from the form after converting the image in HSV color format, but the background noise was significant, and results obtained were not promising. We are researching a more robust method to extract characters that doesn’t deform the characters and takes alignment into consideration.
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15

SAYANJALI, Z., Z. AKHLAGHI, and B. KHOSRAVI. "ON THE REGULARITY OF CHARACTER DEGREE GRAPHS." Bulletin of the Australian Mathematical Society 100, no. 3 (March 8, 2019): 428–33. http://dx.doi.org/10.1017/s0004972719000315.

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Let $G$ be a finite group and let $\text{Irr}(G)$ be the set of all irreducible complex characters of $G$. Let $\unicode[STIX]{x1D70C}(G)$ be the set of all prime divisors of character degrees of $G$. The character degree graph $\unicode[STIX]{x1D6E5}(G)$ associated to $G$ is a graph whose vertex set is $\unicode[STIX]{x1D70C}(G)$, and there is an edge between two distinct primes $p$ and $q$ if and only if $pq$ divides $\unicode[STIX]{x1D712}(1)$ for some $\unicode[STIX]{x1D712}\in \text{Irr}(G)$. We prove that $\unicode[STIX]{x1D6E5}(G)$ is $k$-regular for some natural number $k$ if and only if $\overline{\unicode[STIX]{x1D6E5}}(G)$ is a regular bipartite graph.
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16

JOHNSON, KENNETH W., and EIRINI POIMENIDOU. "A formal power series attached to a class function on a group and its application to the characterisation of characters." Mathematical Proceedings of the Cambridge Philosophical Society 155, no. 3 (July 3, 2013): 465–74. http://dx.doi.org/10.1017/s0305004113000388.

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AbstractIn Frobenius' initial papers on group characters he introduced k-characters in order to give an algorithm to calculate the irreducible factors of the group determinant. We show how his work leads naturally to the construction of a formal power series for any class function on a group, which terminates if and only if the class function is a character. This is then used to obtain a criterion for a class function to be a character.
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17

SARHAN, AHMAD M. "Arabic Character Recognition Using a Combination of k-means and k-NN Algorithms." International Journal of Computer Processing of Languages 22, no. 04 (December 2009): 305–20. http://dx.doi.org/10.1142/s179384060900210x.

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18

Tian, Xue Dong, Xue Sha Jia, Fang Yang, Xin Fu Li, and Xiu Fen Miao. "A Retrieval Method of Ancient Chinese Character Images." Applied Mechanics and Materials 462-463 (November 2013): 432–37. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.432.

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Global and local image retrieval of ancient Chinese characters is a helpful means for character research work. Because of the characteristics of ancient Chinese characters such as complex structures and variant shapes, there exist many theoretical and technical problems in feature extraction, clustering and retrieval of these images. A retrieval method was established with the strategy of “clustering before matching” for the ancient Chinese character images by integrating the structural features of them. Firstly, preprocessed character image area was divided into elastic meshes and the directional elements were extracted to form the feature vectors. Then, K-means algorithm was employed to cluster the character images within global and local areas. Finally, the similar images within selected areas were searched in corresponding cluster and the obtained images were provided to users. The experimental results show that this method is helpful for the improvement of the efficiency of ancient Chinese character study.
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19

Ajao, Jumoke Falilat, David Olufemi Olawuyi, and Odetunji Ode Odejobi. "Yoruba Handwritten Character Recognition using Freeman Chain Code and K-Nearest Neighbor Classifier." Jurnal Teknologi dan Sistem Komputer 6, no. 4 (October 31, 2018): 129–34. http://dx.doi.org/10.14710/jtsiskom.6.4.2018.129-134.

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This work presents a recognition system for Offline Yoruba characters recognition using Freeman chain code and K-Nearest Neighbor (KNN). Most of the Latin word recognition and character recognition have used k-nearest neighbor classifier and other classification algorithms. Research tends to explore the same recognition capability on Yoruba characters recognition. Data were collected from adult indigenous writers and the scanned images were subjected to some level of preprocessing to enhance the quality of the digitized images. Freeman chain code was used to extract the features of THE digitized images and KNN was used to classify the characters based on feature space. The performance of the KNN was compared with other classification algorithms that used Support Vector Machine (SVM) and Bayes classifier for recognition of Yoruba characters. It was observed that the recognition accuracy of the KNN classification algorithm and the Freeman chain code is 87.7%, which outperformed other classifiers used on Yoruba characters.
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20

Fisher, Shirley. "Developing and Implementing a K-12 Character Education Program." Journal of Physical Education, Recreation & Dance 69, no. 2 (February 1998): 21–23. http://dx.doi.org/10.1080/07303084.1998.10605064.

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21

Landweber, Gregory D., and Reyer Sjamaar. "Character formulæ and GKRS multiplets in equivariant K-theory." Selecta Mathematica 19, no. 1 (October 26, 2012): 49–95. http://dx.doi.org/10.1007/s00029-012-0102-6.

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22

Huang, Y. S., K. Liu, C. Y. Suen, and Y. Y. Tang. "A Reliability Design Methodology for Chinese Character Recognition." International Journal of Pattern Recognition and Artificial Intelligence 12, no. 02 (March 1998): 159–72. http://dx.doi.org/10.1142/s0218001498000117.

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This paper proposes a novel method which enables a Chinese character recognition system to obtain reliable recognition. In this method, two thresholds, i.e. class region thresholdRk and disambiguity thresholdAk, are used by each Chinese character k when the classifier is designed based on the nearest neighbor rule, where Rk defines the pattern distribution region of character k, and Ak prevents the samples not belonging to character k from being ambiguously recognized as character k. A novel algorithm to derive the appropriate thresholds Ak and Rk is developed so that a better recognition reliability can be obtained through iterative learning. Experiments performed on the ITRI printed Chinese character database have achieved highly reliable recognition performance (such as 0.999 reliability with a 95.14% recognition rate), which shows the feasibility and effectiveness of the proposed method.
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23

AGARWALA, RICHA, and DAVID FERNÁNDEZ-BACA. "SIMPLE ALGORITHMS FOR PERFECT PHYLOGENY AND TRIANGULATING COLORED GRAPHS." International Journal of Foundations of Computer Science 07, no. 01 (March 1996): 11–21. http://dx.doi.org/10.1142/s0129054196000038.

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This paper presents an O((r–n/m)mrnm) algorithm for determining whether a set of n species has a perfect phylogeny, where m is the number of characters used to describe a species and r is the maximum number of states that a character can be in. The perfect phylogeny algorithm leads to an O((2e/k)ke2k) algorithm for triangulating a k-colored graph having e edges.
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Mukherjee, Prosenjit, Shibaprasad Sen, Kaushik Roy, and Ram Sarkar. "Recognition of Online Handwritten Bangla Characters Using Supervised and Unsupervised Learning Approaches." International Journal of Computer Vision and Image Processing 10, no. 3 (July 2020): 18–30. http://dx.doi.org/10.4018/ijcvip.2020070102.

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This paper explores the domain of online handwritten Bangla character recognition by stroke-based approach. The component strokes of a character sample are recognized firstly and then characters are constructed from the recognized strokes. In the current experiment, strokes are recognized by both supervised and unsupervised approaches. To estimate the features, images of all the component strokes are superimposed. A mean structure has been generated from this superimposed image. Euclidian distances between pixel points of a stroke sample and mean stroke structure are considered as features. For unsupervised approach, K-means clustering algorithm has been used whereas six popular classifiers have been used for supervised approach. The proposed feature vector has been evaluated on 10,000-character database and achieved 90.69% and 97.22% stroke recognition accuracy in unsupervised (using K-means clustering) and supervised way (using MLP [multilayer perceptron] classifier). This paper also discusses about merit and demerits of unsupervised and supervised classification approaches.
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Sharma, Bhu Dev, and Ankita Gaur. "Codes Correcting Limited Patterns of Random Errors Using S-K Metric." Cybernetics and Information Technologies 13, no. 1 (March 1, 2013): 34–45. http://dx.doi.org/10.2478/cait-2013-0004.

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Abstract Coding is essential in all communications and in all multi-operation devices, and errors do occur. For error control, the method in vogue is to use code words with redundant digits. The number of redundant digits is determined based on two things − the number of messages and the kind of errors that need to be controlled. For efficient coding the redundant digits have to be kept to the minimum. In this paper we introduce the idea of limited error patters while using the code alphabet {0,1, 2,..., 1},mod , q Z = q − q when q > 3. We define limitations of the errors in a position by substitution of the character there by a specified number of other characters, rather than by any other character. This is not possible through Hamming approach, because there a character in an error could be substituted by any other of the q-1 characters. The firm mathematical base is provided by use of a metric from the class of S-K metrics, Hamming metric being one of these. The paper gives upper bounds on the codeword lengths for various kinds of “random limited error patterns”. Examples and discussion bring out the tremendous improvement and generalization of Rao Hamming bound.
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Poimenidou, Eirini, and Homer Wolfe. "Total characters and Chebyshev polynomials." International Journal of Mathematics and Mathematical Sciences 2003, no. 38 (2003): 2447–53. http://dx.doi.org/10.1155/s0161171203201046.

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The total characterτof a finite groupGis defined as the sum of all the irreducible characters ofG. K. W. Johnson asks when it is possible to expressτas a polynomial with integer coefficients in a single irreducible character. In this paper, we give a complete answer to Johnson's question for all finite dihedral groups. In particular, we show that, when such a polynomial exists, it is unique and it is the sum of certain Chebyshev polynomials of the first kind in any faithful irreducible character of the dihedral groupG.
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27

Nikonov, I. M., and G. I. Sharygin. "Hopf cyclic cohomology and Chern character of equivariant K-theories." Russian Journal of Mathematical Physics 22, no. 3 (July 2015): 379–88. http://dx.doi.org/10.1134/s1061920815030085.

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28

Park, Efton. "Equivariant $K$-theory and the Chern character for discrete groups." Proceedings of the American Mathematical Society 140, no. 3 (March 1, 2012): 745–47. http://dx.doi.org/10.1090/s0002-9939-2011-10912-2.

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29

Ohno, T. R., G. H. Kroll, J. H. Weaver, L. P. F. Chibante, and R. E. Smalley. "Yb and Yb-K fulleride formation, bonding, and electrical character." Physical Review B 46, no. 16 (October 15, 1992): 10437–41. http://dx.doi.org/10.1103/physrevb.46.10437.

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Dress, Andreas, and Johannes Grabmeier. "The interpolation problem for k-sparse polynomials and character sums." Advances in Applied Mathematics 12, no. 1 (March 1991): 57–75. http://dx.doi.org/10.1016/0196-8858(91)90004-3.

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31

Mathai, Varghese, and Danny Stevenson. "Chern Character in Twisted K -Theory: Equivariant and Holomorphic Cases." Communications in Mathematical Physics 236, no. 1 (May 1, 2003): 161–86. http://dx.doi.org/10.1007/s00220-003-0807-7.

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Tillmann, Ulrike. "K-theory of fine topological algebras, Chern character, and assembly." K-Theory 6, no. 1 (January 1992): 57–86. http://dx.doi.org/10.1007/bf00961335.

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Connes, Alain, and Henri Moscovici. "Transgression and the Chern character of finite-dimensional K-cycles." Communications in Mathematical Physics 155, no. 1 (July 1993): 103–22. http://dx.doi.org/10.1007/bf02100052.

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Ernst, Kaspar, Ping Feng, Arthur Jaffe, and Andrzej Lesniewski. "Quantum K-theory. II. Homotopy invariance of the Chern character." Journal of Functional Analysis 90, no. 2 (May 1990): 355–68. http://dx.doi.org/10.1016/0022-1236(90)90087-2.

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Ballal, Sachin, and Vilas Kharat. "Zariski topology on lattice modules." Asian-European Journal of Mathematics 08, no. 04 (November 17, 2015): 1550066. http://dx.doi.org/10.1142/s1793557115500667.

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Let [Formula: see text] be a lattice module over a [Formula: see text]-lattice [Formula: see text] and [Formula: see text] be the set of all prime elements in lattice modules [Formula: see text]. In this paper, we study the generalization of the Zariski topology of multiplicative lattices [N. K. Thakare, C. S. Manjarekar and S. Maeda, Abstract spectral theory II: Minimal characters and minimal spectrums of multiplicative lattices, Acta Sci. Math. 52 (1988) 53–67; N. K. Thakare and C. S. Manjarekar, Abstract spectral theory: Multiplicative lattices in which every character is contained in a unique maximal character, in Algebra and Its Applications (Marcel Dekker, New York, 1984), pp. 265–276.] to lattice modules. Also we investigate the interplay between the topological properties of [Formula: see text] and algebraic properties of [Formula: see text].
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Huang, Juanjuan, Ihtisham Ul Haq, Chaolan Dai, Sulaiman Khan, Shah Nazir, and Muhammad Imtiaz. "Isolated Handwritten Pashto Character Recognition Using a K-NN Classification Tool based on Zoning and HOG Feature Extraction Techniques." Complexity 2021 (March 24, 2021): 1–8. http://dx.doi.org/10.1155/2021/5558373.

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Handwritten text recognition is considered as the most challenging task for the research community due to slight change in different characters’ shape in handwritten documents. The unavailability of a standard dataset makes it vaguer in nature for the researchers to work on. To address these problems, this paper presents an optical character recognition system for the recognition of offline Pashto characters. The problem of the unavailability of a standard handwritten Pashto characters database is addressed by developing a medium-sized database of offline Pashto characters. This database consists of 11352 character images (258 samples for each 44 characters in a Pashto script). Enriched feature extraction techniques of histogram of oriented gradients and zoning-based density features are used for feature extraction of carved Pashto characters. K-nearest neighbors is considered as a classification tool for the proposed algorithm based on the proposed feature sets. A resultant accuracy of 80.34% is calculated for the histogram of oriented gradients, while for zoning-based density features, 76.42% is achieved using 10-fold cross validation.
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Ridwan, Ridwan, and Widi Wulansari. "Menumbuhkan Karakter Anak Usia Dini Melalui Cerita Boneka Tangan dalam Model Tadzkirah." Proceedings of the ICECRS 2, no. 1 (July 28, 2019): 131. http://dx.doi.org/10.21070/picecrs.v2i1.2408.

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The growth of early childhood character in the golden age is a very important thing that affects behavior and character in the future and it is the responsibility of all parties. Various models, methods and media can be used as a means to grow characters in early childhood. One is using hand puppets through storytelling methods. This research is aimed to know how the use of hand puppet through story with tadzkirah model can grow character in early childhood. Kindergarten / PAUD students will be more interested in recognizing characters as well as emulating those characters in the story. Methods of telling stories with hand puppets in line with the tadzkirah learning model, emphasizing on exemplary (T), guidance on guidance (A), encouragement (D), planting value (Z), continuity principle (K) repetition (R), organizing knowledge and experience (A), touching heart (H). Methods in this study are qualitative methods. The conclusions of this study are the use of hand puppets through story methods and tadzkirah models containing stories of honesty, independence, sense of responsibility and tolerance can grow characters in early childhood.
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LAI, ALAN. "ON THE JLO COCYCLE AND ITS TRANSGRESSION IN ENTIRE CYCLIC COHOMOLOGY." International Journal of Geometric Methods in Modern Physics 10, no. 07 (June 10, 2013): 1350037. http://dx.doi.org/10.1142/s0219887813500370.

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The JLO character formula due to Jaffe–Lesniewski–Osterwalder [Quantum K-theory: the Chern character, Commun. Math. Phys.112 (1988) 75–88] assigns to each Fredholm module a cocycle in entire cyclic cohomology. It descends to define a cohomological Chern character on K-homology. This paper extends the definition of the JLO character formula for Breuer–Fredholm modules, the modules that represent type II noncommutative geometry; and shows that the JLO character formula coincides with the Connes character formula [see M. Benameur and T. Fack, Type II noncommutative geometry. I. Dixmier trace in von Neumann algebras, Adv. Math.199 (2006) 29–87] at the level of entire cyclic cohomology.
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39

Börjesson, Patrik, and Per Berggren. "Morphometric comparisons of skulls of harbour porpoises (Phocoena phocoena) from the Baltic, Kattegat, and Skagerrak seas." Canadian Journal of Zoology 75, no. 2 (February 1, 1997): 280–87. http://dx.doi.org/10.1139/z97-035.

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The population structure of harbour porpoises (Phocoena phocoena) in Swedish waters was studied by means of morphometric comparisons of skulls from 103 specimens. The study was designed to investigate whether harbour porpoises in the Baltic Sea form a distinct population separate from animals found in the Kattegat and Skagerrak seas. The Kattegat–Skagerrak (K-S) sample was divided into summer and winter samples to account for possible migrational movements by Baltic Sea animals between breeding seasons. Both multivariate and univariate statistical analyses showed significant differences between three female samples from the Baltic Sea and the Kattegat and Skagerrak seas. Pairwise comparisons showed differences between the Baltic sample and the K-S summer sample in five characters and between the Baltic sample and K-S winter sample in one character. No differences were found between the K-S summer and winter samples. The multivariate analysis did not show separation of male specimens and only one character was significantly different in the univariate analyses. Pairwise comparisons of adjusted means of this character did not reveal significant differences between the samples. The results show that female harbour porpoises in the Baltic Sea are morphologically distinct from females in the Kattegat and Skagerrak seas and these differences probably would not exist if animals from the two areas interbreed. Harbour porpoises in the Baltic Sea should therefore be managed separately and measures should be taken to prevent bycatches of this likely endangered population.
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40

Kumar Prasad, Binod. "SLOPE AND CURVE CODING TO RECOGNIZE ENGLISH NUMERALS." International Journal of Students' Research in Technology & Management 8, no. 2 (June 16, 2020): 15–20. http://dx.doi.org/10.18510/ijsrtm.2020.823.

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Purpose: Lines and Curves are important parts of characters in any script. Features based on lines and curves go a long way to characterize an individual character as well as differentiate similar-looking characters. The present paper proposes an English numerals recognition system using feature elements obtained from the novel and efficient coding of the curves and local slopes. The purpose of this paper is to recognize English numerals efficiently to develop a reliable Optical Character recognition system. Methodology: K-Nearest Neighbour classification technique has been implemented on a global database MNIST to get an overall recognition accuracy rate of 96.7 %, which is competitive to other reported works in literature. Distance features and slope features are extracted from pre-processed images. The feature elements from training images are used to train K-Nearest-Neighbour classifier and those from test images have been used to classify them. Main Findings: The findings of the current paper can be used in Optical Character Recognition (OCR) of alphanumeric characters of any language, automatic reading of amount on bank cheque, address written on envelops, etc. Implications: Due to the similarity in structures of some numerals like 2, 3, and 8, the system produces respectively lower recognition accuracy rates for them. Novelty: The ways of finding distance and slope features to differentiate the curves in the structure of English Numerals is the novelty of this work.
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41

Angadi, S. A., and M. M. Kodabagi. "A Robust Segmentation Technique for Line, Word and Character Extraction from Kannada Text in Low Resolution Display Board Images." International Journal of Image and Graphics 14, no. 01n02 (January 2014): 1450003. http://dx.doi.org/10.1142/s021946781450003x.

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Reliable extraction/segmentation of text lines, words and characters is one of the very important steps for development of automated systems for understanding the text in low resolution display board images. In this paper, a new approach for segmentation of text lines, words and characters from Kannada text in low resolution display board images is presented. The proposed method uses projection profile features and on pixel distribution statistics for segmentation of text lines. The method also detects text lines containing consonant modifiers and merges them with corresponding text lines, and efficiently separates overlapped text lines as well. The character extraction process computes character boundaries using vertical profile features for extracting character images from every text line. Further, the word segmentation process uses k-means clustering to group inter character gaps into character and word cluster spaces, which are used to compute thresholds for extracting words. The method also takes care of variations in character and word gaps. The proposed methodology is evaluated on a data set of 1008 low resolution images of display boards containing Kannada text captured from 2 mega pixel cameras on mobile phones at various sizes 240 × 320, 480 × 640 and 960 × 1280. The method achieves text line segmentation accuracy of 97.17%, word segmentation accuracy of 97.54% and character extraction accuracy of 99.09%. The proposed method is tolerant to font variability, spacing variations between characters and words, absence of free segmentation path due to consonant and vowel modifiers, noise and other degradations. The experimentation with images containing overlapped text lines has given promising results.
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42

Chitwood, Brandon. "ETERNAL RETURNS: A CHRISTMAS CAROL'S GHOSTS OF REPETITION." Victorian Literature and Culture 43, no. 4 (July 7, 2015): 675–87. http://dx.doi.org/10.1017/s1060150315000200.

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In spite of the supernatural trappings of Charles Dickens's most famous work, A Christmas Carol, critics from G. K. Chesterton to Edmund Wilson have found its equally famous protagonist, Ebenezer Scrooge, to be a real character, more fleshed-out and compelling than many of the characters of Dickens's longer, presumably more “serious” novels. Much of the reaction to A Christmas Carol and its protean anti-hero can be summarized by Stephen Prickett's succinct appraisal in his seminal study, Victorian Fantasy: “The strength of A Christmas Carol lies quite simply in its psychological credibility” (54). Scrooge is a character we can believe in, a character that, as Margaret Atwood suggests, “remains fresh and vital. ‘Scrooge Lives!’ we might write on our T-shirts” (xiii).
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43

Mahanta, Snigdhayan. "Twisted ${K}$ -theory, ${K}$ -homology, and bivariant Chern–Connes type character of some infinite dimensional spaces." Kyoto Journal of Mathematics 54, no. 3 (2014): 597–640. http://dx.doi.org/10.1215/21562261-2693460.

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44

Susanto, Ajib, Daurat Sinaga, Christy Atika Sari, Eko Hari Rachmawanto, and De Rosal Ignatius Moses Setiadi. "A High Performace of Local Binary Pattern on Classify Javanese Character Classification." Scientific Journal of Informatics 5, no. 1 (May 30, 2018): 8. http://dx.doi.org/10.15294/sji.v5i1.14017.

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The classification of Javanese character images is done with the aim of recognizing each character. The selected classification algorithm is K-Nearest Neighbor (KNN) at K = 1, 3, 5, 7, and 9. To improve KNN performance in Javanese character written by the author, and to prove that feature extraction is needed in the process image classification of Javanese character. In this study selected Local Binary Patter (LBP) as a feature extraction because there are research objects with a certain level of slope. The LBP parameters are used between [16 16], [32 32], [64 64], [128 128], and [256 256]. Experiments were performed on 80 training drawings and 40 test images. KNN values after combination with LBP characteristic extraction were 82.5% at K = 3 and LBP parameters [64 64].
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45

Cho, Myeong-Sil. "A Study on Character Education Method for University Students using Board Games - Focusing on K University’s Character Subject -." Humanities Studies East and West 59 (August 31, 2020): 203–32. http://dx.doi.org/10.37498/hsew.2020.08.59.203.

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46

NELSON, G. H., and C. L. BELLAMY. "A revision of the genus Paratyndaris Fisher, 1919 (Coleoptera: Buprestidae: Polycestinae)." Zootaxa 683, no. 1 (October 12, 2004): 1. http://dx.doi.org/10.11646/zootaxa.683.1.1.

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The genus Paratyndaris Fisher, 1919 is revised, and three subgenera are recognized: P. (Knulliella) Cobos, P. (Paratyndaris) Fisher, and P. (Waltersia), subg. nov. [type species: Tyndaris barberi Skinner]. The subgenus P. (Knulliella) contains six species: P. (K.) antillarum Fisher, P. (K.) chamaeleonis (Skinner), P. (K.) mojito B l , P. (K.) pulchra, sp. nov., P. (K.) similis, sp. nov., and P. (K.) suturalis Fall. The subgenus P. (Paratyndaris) contains 26 species: P. (P.) acaciae Knull, P. (P.) albofasciata Knull, P. (P.) anomalis Knull, P. (P.) cincta (Horn), P. (P.) costata, sp. nov., P. (P.) coursetiae Fisher, P. (P.) crandalli Knull, P. (P.) dozieri, sp. nov., P. (P.) grassmani Parker, P. (P.) lateralis (Barr), P. (P.) mexicana Fisher, P. (P.) mimica, sp. nov., P. (P.) nelsoni (Barr), P. (P.) olneyae (Skinner), P. (P.) paralateralis, sp. nov., P. (P.) peninsularis Westcott, P. (P.) prosopis (Skinner), P. (P.) quadrinotata Knull, P. (P.) robusta (Dozier), P. (P.) subcostata (Barr), P. (P.) tucsoni Knull, P. (P.) turbida, sp. nov., P. (P.) uniformis, sp. nov., P. (P.) variabilis Westcott, P. (P.) verityi, sp. nov., and P. (P.) westcotti, sp. nov. The subgenus P. (Waltersia) contains four species: P. (W.) barberi (Skinner), P. (W.) equihuai Westcott, P. (W.) knulli (Barr), and P. (W.) trilobata Westcott. One new synonym is proposed: P. mexicana Fisher (= P. sonorae (Barr)). All taxa included are described and information on variation, type localities, distribution, biology, and comparisons are given for each species. A key to subgenera and species is provided. Habitus photos for all species and selected generic outgroup taxa, drawings of selected key characters, distributional maps and a cladogram of hypothetical generic relationships are presented. Tables of examined taxa, characters and character states and a character state matrix are included.
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47

Goyal, Ankush, and Sha llu. "An Approach of K-Means and ART Network for Character Recognition." International Journal of Engineering Trends and Technology 24, no. 1 (June 25, 2015): 45–49. http://dx.doi.org/10.14445/22315381/ijett-v24p209.

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48

Harada, Megumi, Gregory D. Landweber, and Reyer Sjamaar. "Divided differences and the Weyl character formula in equivariant K-theory." Mathematical Research Letters 17, no. 3 (2010): 507–27. http://dx.doi.org/10.4310/mrl.2010.v17.n3.a10.

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49

Leu, Ming-Guang, and Wen-Ch’ing Winnie Li. "On the series for L(1, x)." Nagoya Mathematical Journal 141 (March 1996): 125–42. http://dx.doi.org/10.1017/s0027763000005559.

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50

Cowling, Michael. "On the characters of unitary representations." Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics 45, no. 1 (August 1988): 62–65. http://dx.doi.org/10.1017/s1446788700032262.

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AbstractLet G be a locally compact group, and let D(G) be a dense subalgebra of the convolution algebra L1(G). Suppose that π is a unitary representation of G and that, for each u in D(G), π(u)) is a trace-class operator. Then the linear functional u → tr(π(u)) (the trace of π(u)) is called the D-character of π. We give a simple proof that the D-character of such a representation determines the representation up to unitary equivalence. As an application, we give an easy proof of the result of Harish-Chandra that the K-finite characters of unitary representations of semisimple Lie groups determine the representations.
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