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Journal articles on the topic 'Matrix of evaluation'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Sastre, Jorge, and Javier Ibáñez. "Efficient Evaluation of Matrix Polynomials beyond the Paterson–Stockmeyer Method." Mathematics 9, no. 14 (July 7, 2021): 1600. http://dx.doi.org/10.3390/math9141600.

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Recently, two general methods for evaluating matrix polynomials requiring one matrix product less than the Paterson–Stockmeyer method were proposed, where the cost of evaluating a matrix polynomial is given asymptotically by the total number of matrix product evaluations. An analysis of the stability of those methods was given and the methods have been applied to Taylor-based implementations for computing the exponential, the cosine and the hyperbolic tangent matrix functions. Moreover, a particular example for the evaluation of the matrix exponential Taylor approximation of degree 15 requiring four matrix products was given, whereas the maximum polynomial degree available using Paterson–Stockmeyer method with four matrix products is 9. Based on this example, a new family of methods for evaluating matrix polynomials more efficiently than the Paterson–Stockmeyer method was proposed, having the potential to achieve a much higher efficiency, i.e., requiring less matrix products for evaluating a matrix polynomial of certain degree, or increasing the available degree for the same cost. However, the difficulty of these family of methods lies in the calculation of the coefficients involved for the evaluation of general matrix polynomials and approximations. In this paper, we provide a general matrix polynomial evaluation method for evaluating matrix polynomials requiring two matrix products less than the Paterson-Stockmeyer method for degrees higher than 30. Moreover, we provide general methods for evaluating matrix polynomial approximations of degrees 15 and 21 with four and five matrix product evaluations, respectively, whereas the maximum available degrees for the same cost with the Paterson–Stockmeyer method are 9 and 12, respectively. Finally, practical examples for evaluating Taylor approximations of the matrix cosine and the matrix logarithm accurately and efficiently with these new methods are given.

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2

Iche, Ghanshyam Ramesh. "Formulation and Evaluation of Aceclofenac Matrix Tablet." International Journal of Scientific Research 3, no. 1 (June 1, 2012): 410–12. http://dx.doi.org/10.15373/22778179/jan2014/142.

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3

Capps, III, Charles J., and Michael D. Glissmeyer. "Extending The Competitive Profile Matrix Using Internal Factor Evaluation And External Factor Evaluation Matrix Concepts." Journal of Applied Business Research (JABR) 28, no. 5 (August 21, 2012): 1059. http://dx.doi.org/10.19030/jabr.v28i5.7245.

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Internal Factor Evaluation and External Factor Evaluation matrices allow an organization to visualize their strengths, weaknesses, opportunities, and threats while a Competitive Profile Matrix utilizes critical success factors to allow an organization to compare itself to other competitors. The authors wondered if substituting basic internal strengths and weaknesses categories, and external opportunities and threats classifications for the conventional CSFs in a forced ranking method could extend the Competitive Profile Matrix to allow additional strategic understanding. The goal of extending the Competitive Profile Matrix using the forced ranking of important organizational factors when evaluating an organizations relative competitive position against major competitors was successfully realized. An External Competitive Profile Matrix (ECPM) and an Internal Competitive Profile Matrix (ICPM) better draw awareness to internal and external categories that need an organizations attention.

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4

Sahu, Mithlesh, Mithun Bhowmick, and Jagdish Rathi. "Design and evaluation of Matrix Transdermal therapeutic system of Repaglinide." International Journal of Research and Development in Pharmacy & Life Sciences 06, no. 04 (July 2017): 2697–705. http://dx.doi.org/10.21276/ijrdpl.2278-0238.2017.6(4).2697-2705.

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5

Sastre, J. "Efficient evaluation of matrix polynomials." Linear Algebra and its Applications 539 (February 2018): 229–50. http://dx.doi.org/10.1016/j.laa.2017.11.010.

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6

Campbell, E., J. Pierce, S. Endicott, and S. Shapiro. "Evaluation of Extracellular Matrix Turnover." Chest 99, no. 3 (March 1991): 49S. http://dx.doi.org/10.1378/chest.99.3_supplement.49s.

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7

Wituła, Roman, Damian Słota, Jarosław Matlak, Agata Chmielowska, and Michał Różański. "Matrix methods in evaluation of integrals." Journal of Applied Mathematics and Computational Mechanics 19, no. 1 (March 2020): 103–12. http://dx.doi.org/10.17512/jamcm.2020.1.09.

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8

Nguyen, Canh Hao, and Tu Bao Ho. "An efficient kernel matrix evaluation measure." Pattern Recognition 41, no. 11 (November 2008): 3366–72. http://dx.doi.org/10.1016/j.patcog.2008.04.005.

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9

Urbanowicz, Krzysztof, Peter Richmond, and Janusz A. Hołyst. "Risk evaluation with enhanced covariance matrix." Physica A: Statistical Mechanics and its Applications 384, no. 2 (October 2007): 468–74. http://dx.doi.org/10.1016/j.physa.2007.05.034.

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10

Pack, Russell T., and John S. Dahler. "Asymptotic evaluation of WKB matrix elements." International Journal of Quantum Chemistry 3, S3A (June 18, 2009): 329. http://dx.doi.org/10.1002/qua.560030736.

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11

Tadi, M., and Wei Cai. "Inverse matrix evaluation for linear systems." Inverse Problems 17, no. 2 (February 13, 2001): 247–60. http://dx.doi.org/10.1088/0266-5611/17/2/305.

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12

MURPHY, GILLIAN, VERA KNAUPER, SUSAN COWELL, ROSALIND HEMBRY, HEATHER STANTON, GEORGINA BUTLER, JOSE FREIJE, ALBERTO M. PENDAS, and CARLOS LOPEZ-OTIN. "Evaluation of Some Newer Matrix Metalloproteinases." Annals of the New York Academy of Sciences 878, no. 1 INHIBITION OF (June 1999): 25–39. http://dx.doi.org/10.1111/j.1749-6632.1999.tb07672.x.

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13

Jia, Feng, Gerrit Schultz, Frederik Testud, Anna Masako Welz, Hans Weber, Sebastian Littin, Huijun Yu, Jürgen Hennig, and Maxim Zaitsev. "Performance evaluation of matrix gradient coils." Magnetic Resonance Materials in Physics, Biology and Medicine 29, no. 1 (December 14, 2015): 59–73. http://dx.doi.org/10.1007/s10334-015-0519-y.

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14

Ran, Chen, Ji Kunhua, Wang Yun, Lu Jian, Xie Haining, and Zhuang Liming. "Management Evaluation of Distribution Network Based on Fuzzy Evaluation Matrix." Journal of Physics: Conference Series 1345 (November 2019): 022038. http://dx.doi.org/10.1088/1742-6596/1345/2/022038.

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15

Hassan, Somaia Awad, A. M. Hemeida, and Mountasser M. M. Mahmoud. "Performance Evaluation of Matrix-Matrix Multiplications Using Intel's Advanced Vector Extensions (AVX)." Microprocessors and Microsystems 47 (November 2016): 369–74. http://dx.doi.org/10.1016/j.micpro.2016.10.002.

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16

Fabera, K. T., S. H. Advani, J. K. Lee, and J. T. Jinn. "Frictional Stress Evaluation along the Fiber-Matrix Interface in Ceramic Matrix Composites." Journal of the American Ceramic Society 69, no. 9 (September 1986): C—208—C—209. http://dx.doi.org/10.1111/j.1151-2916.1986.tb07480.x.

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17

Shen, Fujin, Sixing Yang, Yi Yao, Kaiyu Qian, Yun Wei, and Linglong Wang. "Biocompatibility evaluation of vessel extracellular matrix as a matrix for urethral reconstruction." Journal of Wuhan University of Technology-Mater. Sci. Ed. 22, no. 3 (September 2007): 436–38. http://dx.doi.org/10.1007/s11595-006-3436-0.

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18

Befani, Barbara. "Quality of quality: A diagnostic approach to qualitative evaluation." Evaluation 26, no. 3 (February 25, 2020): 333–49. http://dx.doi.org/10.1177/1356389019898223.

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This article discusses the integration of a diagnostic lens in qualitative or mixed methods evaluations, arguing that this will improve quality: in particular, it will improve transparency, credibility and reliability of evaluation findings.We start by unpacking the notion of evaluation quality and pointing out the typical weaknesses of qualitative methods. We then introduce the basic notions of diagnostic approaches and how they relate to theory-based evaluation, process tracing, and Bayesian updating, arguing for the merits of taking a formal Bayesian approach, founded on the confusion matrix, which amongst else reduces confirmation bias and conservatism. This article draws parallels between the process tracing tests and elements of the confusion matrix.

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19

Zhang, Jiachao, Shin-ichiro Mori, and Shinji Tomita. "Evaluation of Three Quads Using Matrix Transpose." Journal of Information Processing 26 (2018): 301–5. http://dx.doi.org/10.2197/ipsjjip.26.301.

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20

Jose, Jobin, V. Jayapraksah, and Prashant Nayak. "Formulation and Evaluation of Rizatriptan Matrix Tablet." Research Journal of Pharmacy and Technology 9, no. 2 (2016): 115. http://dx.doi.org/10.5958/0974-360x.2016.00018.4.

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21

Henrion, Didier, and Michael Šebek. "Numerical Methods For Polynomial Matrix Rank Evaluation ⋆." IFAC Proceedings Volumes 31, no. 18 (July 1998): 369–74. http://dx.doi.org/10.1016/s1474-6670(17)42019-2.

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22

Roy, S. C. D., and S. Minocha. "On the evaluation of a matrix polynomial." IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 39, no. 7 (July 1992): 567–70. http://dx.doi.org/10.1109/81.257297.

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23

Tan, Jie, Yikai Wang, Zishu He, and Guohao Sun. "ASCRL evaluation with parametrically constrained covariance matrix." Electronics Letters 54, no. 11 (May 2018): 718–20. http://dx.doi.org/10.1049/el.2018.0423.

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24

Langr, Daniel, and Pavel Tvrdik. "Evaluation Criteria for Sparse Matrix Storage Formats." IEEE Transactions on Parallel and Distributed Systems 27, no. 2 (February 1, 2016): 428–40. http://dx.doi.org/10.1109/tpds.2015.2401575.

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25

Alatan, L., M. I. Aksun, K. Mahadevan, and M. T. Birand. "Analytical evaluation of the MoM matrix elements." IEEE Transactions on Microwave Theory and Techniques 44, no. 4 (April 1996): 519–25. http://dx.doi.org/10.1109/22.491019.

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26

Ren, Dongfeng, Shuxun Hou, Huadong Wang, Dianzhong Luo, and Lihai Zhang. "Evaluation of RGD Modification on Collagen Matrix." Artificial Cells, Blood Substitutes, and Biotechnology 34, no. 3 (January 2006): 293–303. http://dx.doi.org/10.1080/10731190600683829.

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27

Palma, Carla, Vanessa Morgado, and Ricardo J. N. Bettencourt da Silva. "Top-down evaluation of matrix effects uncertainty." Talanta 192 (January 2019): 278–87. http://dx.doi.org/10.1016/j.talanta.2018.09.039.

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28

Etchegoyen, A., M. C. Etchegoyen, and E. G. Vergini. "Evaluation of Hamiltonian two-body matrix elements." Computer Physics Communications 55, no. 2 (September 1989): 227–31. http://dx.doi.org/10.1016/0010-4655(89)90079-9.

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29

Tuzun, Robert E., and Don Secrest. "Numerical evaluation of Kratzer oscillator matrix elements." Computer Physics Communications 70, no. 2 (June 1992): 362–70. http://dx.doi.org/10.1016/0010-4655(92)90199-9.

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30

Rej, R. "Proficiency testing, matrix effects, and method evaluation." Clinical Chemistry 40, no. 3 (March 1, 1994): 345–46. http://dx.doi.org/10.1093/clinchem/40.3.345.

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31

FRANK, P., D. MANGAT, N. ADKINSON, R. HAMILTON, H. HOMBURGER, D. OWNBY, H. ZEITZ, and I. HRUSOVSKY. "766 Clinical evaluation of abbott matrix Aero." Journal of Allergy and Clinical Immunology 87, no. 1 (January 1991): 331. http://dx.doi.org/10.1016/0091-6749(91)92048-6.

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32

Prouvost, Laurent P., and Michael J. Economides. "Real-time evaluation of matrix acidizing treatments." Journal of Petroleum Science and Engineering 1, no. 2 (December 1987): 145–54. http://dx.doi.org/10.1016/0920-4105(87)90005-2.

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33

Sharma, V. K., Sanjay Sharma, R. B. Mahajan, and H. P. Garg. "Evaluation of a matrix solar air heater." Energy Conversion and Management 30, no. 1 (January 1990): 1–8. http://dx.doi.org/10.1016/0196-8904(90)90050-9.

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34

Novati, P., M. Redivo-Zaglia, and M. R. Russo. "Preconditioning linear systems via matrix function evaluation." Applied Numerical Mathematics 62, no. 12 (December 2012): 1804–18. http://dx.doi.org/10.1016/j.apnum.2012.07.001.

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35

Cherubino, Mario, Igor Pellegatta, Federico Tamborini, Michele Cerati, Fausto Sessa, and Luigi Valdatta. "Evaluation of lymphangiogenesis in acellular dermal matrix." Indian Journal of Plastic Surgery 47, no. 03 (September 2014): 318–24. http://dx.doi.org/10.4103/0970-0358.146578.

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ABSTRACT Introduction: Much attention has been directed towards understanding the phenomena of angiogenesis and lymphangiogenesis in wound healing. Thanks to the manifold dermal substitute available nowadays, wound treatment has improved greatly. Many studies have been published about angiogenesis and cell invasion in INTEGRA®. On the other hand, the development of the lymphatic network in acellular dermal matrix (ADM) is a more obscure matter. In this article, we aim to characterize the different phases of host cell invasion in ADM. Special attention was given to lymphangiogenic aspects. Materials and Methods: Among 57 rats selected to analyse the role of ADM in lymphangiogenesis, we created four groups. We performed an excision procedure on both thighs of these rats: On the left one we did not perform any action except repairing the borders of the wound; while on the right one we used INTEGRA® implant. The excision biopsy was performed at four different times: First group after 7 days, second after 14 days, third after 21 days and fourth after 28 days. For our microscopic evaluation, we used the classical staining technique of haematoxylin and eosin and a semi-quantitative method in order to evaluate cellularity counts. To assess angiogenesis and lymphangiogenesis development we employed PROX-1 Ab and CD31/PECAM for immunohistochemical analysis. Results: We found remarkable wound contraction in defects that healed by secondary intention while minor wound contraction was observed in defects treated with ADM. At day 7, optical microscopy revealed a more plentiful cellularity in the granulation tissue compared with the dermal regeneration matrix. The immunohistochemical process highlighted vascular and lymphatic cells in both groups. After 14 days a high grade of fibrosis was noticeable in the non-treated group. At day 21, both lymphatic and vascular endothelial cells were better developed in the group with a dermal matrix application. At day 28, lymphatic endothelial cells had organized themselves, engineering the pseudocylindrical structure better disposed in the ADM group than in the control group, and the lymphatic cells were detectable inside the vessels’ lumen in this group. Conclusion: This study has made it possible to demonstrate the absolute importance of an ADM in proper wound healing and has shown better definition of both the qualitative and quantitative aspects of lymphangiogenesis compared to the second intention healing. A major grade of organization of the extracellular matrix and a minor grade of fibrosclerosis in ADM allowed a well-structured morphologic and functional development of the endothelial and lymphatic vascular structures. This study hopes to represent a clinical basis for a wider use of ADM in lesions where lymphatic complications are common.

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36

Seng, Wong Meng. "E-Government Evaluation." International Journal of Electronic Government Research 9, no. 1 (January 2013): 82–96. http://dx.doi.org/10.4018/jegr.2013010105.

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Governments are in the process of transformation from old to new public management, and now E-Government, where online services are delivered to customers using information and communication technologies. Governments that evaluate customer satisfaction using Likert scales often face the challenge of translating findings into strategic actions. This paper introduces a novel ROI vs. ROR matrix analysis, a strategic action tool, to assess customer satisfaction in using E-Filing service in Malaysia. This paper will explore the concept of Customer Relationship Management (CRM) in E-Government, especially the business benefits realisations, tangible in the form of return on investment (ROI, e.g., cost savings) and intangible in the form of return on relationship (ROR, e.g., provide prompt services and helpful responses to customer requests). The development of the ROI vs. ROR matrix is discussed and followed by a demonstration of the usefulness of this matrix to classify customer experiences into four satisfaction quadrants. The research findings are then translated into strategic actions. This research allows the government service provider to identify strategic focus areas that need attention and allocation of resources. Since the main objective of CRM in E-Government is to improve customer satisfaction, the introduction of this ROI vs ROR matrix is timely to help government service provider to learn about their needs and motivations in using E-Government services.

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37

Ju, Zhi Lan, Yong Wei Zhu, and Fu Bao Zhang. "The Fuzzy Comprehensive Evaluation of the Self-Conditioning of Hydrophilic Fixed-Abrasive Pad." Advanced Engineering Forum 29 (August 2018): 26–33. http://dx.doi.org/10.4028/www.scientific.net/aef.29.26.

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The self-conditioning of hydrophilic fixed abrasive lapping based on the principle of two-body (pad-wafer) abrasion has great importance on the MRR (material removal rate) of wafer. The physical and mechanical properties of pad were taken as set of available alternatives. Fuzzy comprehensive evaluation principle was applied to establish a model for the self-conditioning of FAP. The swelling ratio, the slurry abrasive ratio and pendulum hardness were selected to be the set of alternatives for self-conditioning evaluations in this paper .The five types of matrix formations of fixed-abrasive pad were prepared, and the matrix were ranked in order of comprehensive evaluation index. The results show that the fuzzy evaluation is rational. The tests of MRR verified the self-conditioning of FAP. The machining of pad can be evaluated in advance of lapping processes. Moreover, the self-conditioning evaluation will be important reference for determination of FAP during choosing the matrix formations.

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38

Hou, Qiang, and Xue Zhou. "Cross-Efficiency Evaluation Method with Compete-Cooperate Matrix." Mathematical Problems in Engineering 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/710264.

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Cross-efficiency evaluation method is an effective and widespread adopted data envelopment analysis (DEA) method with self-assessment and peer-assessment to evaluate and rank decision making units (DMUs). Extant aggressive, benevolent, and neutral cross-efficiency methods are used to evaluate DMUs with competitive, cooperative, and nontendentious relationships, respectively. In this paper, a symmetric (nonsymmetric) compete-cooperate matrix is introduced into aggressive and benevolent cross-efficiency methods and compete-cooperate cross-efficiency method is proposed to evaluate DMUs with diverse (relative) relationships. Deviation maximization method is applied to determine the final weights of cross-evaluation to enhance the differentiation ability of cross-efficiency evaluation method. Numerical demonstration is provided to illustrate the reasonability and practicability of the proposed method.

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39

Wu, Yong Liang, Bao Quan Mao, Li Xu, Dong Ming Dai, and Yan Chao Liu. "The Evaluation of Module Division Programme Based on Information Entropy." Advanced Materials Research 479-481 (February 2012): 1592–95. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.1592.

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Firstly, analysis product’s customer demand correlation, function correlation, geometric correlation, structure the corresponding correlation matrix, distribute the respective weighting factor, and then establish an integrated correlation matrix. Application of fuzzy clustering, the establishment of cluster map, the program has been divided into different modules. Based on information entropy theory, select product’s design and manufacturing complexity, cost, maintenance as the optimization objective, establish mathematical evaluation model of module division. Evaluating a number of options get from the fuzzy clustering method, which gain the most reasonable module division program. Finally, taking the seat frame of the Remote Control Weapon Station(RCWS) for example, verify the validity and reasonableness of the evaluation method.

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40

Du, Shao Wen, and Shan Shan Li. "Laboratory Evaluation of Warm Stone Matrix Asphalt Mixture." Advanced Materials Research 243-249 (May 2011): 4178–81. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.4178.

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Two kinds of warm additives, Sasobit and Evotherm DAT, were used to develop warm stone mastic asphalt (SMA) mixture. The test results showed that compaction temperature of SMA can be decreased by 30-40°C when using Sasobit or Evotherm DAT. Then, to compare the mechanical performance properties of SMA and warm SMAs, mechanical properties of pavement mixture, including Marshall stability, retained Marshall stability, tensile strength ratio, Cantabro loss, rutting dynamic stability and low temperature flexural strength, were tested in laboratory. The results indicated that Sasobit can decrease obviously the moisture resistance ability and low temperature cracking resistance ability of SMA. Therefore, the pavement performance properties of Sasobit warm SMA are inferior to those of Evotherm DAT warm SMA, which has the nearly same performance properties as hot SMA.

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41

TSUTSUMI, Yoshihito, Masahiro TAKEI, Yoshifuru SAITO, Mitsuaki OCHI, Hui LI, and Kiyoshi HORII. "Evaluation of Particle Density Using State Transition Matrix." Journal of the Visualization Society of Japan 22, no. 1Supplement (2002): 217–18. http://dx.doi.org/10.3154/jvs.22.1supplement_217.

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42

Navaneetha, K., T. Saritha, B. Venkateswara Reddy, N. Jabili, and B. Soujanya. "FORMULATION AND EVALUATION OF KETOPROFEN TRILAYERED MATRIX TABLET." International Research Journal of Pharmacy 7, no. 12 (January 9, 2017): 124–31. http://dx.doi.org/10.7897/2230-8407.0712158.

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43

Delvere, Ieva, Marija Iltina, Maxat Shanbayev, Aray Abildayeva, Svetlana Kuzhamberdieva, and Dagnija Blumberga. "Evaluation of Polymer Matrix Composite Waste Recycling Methods." Environmental and Climate Technologies 23, no. 1 (January 1, 2019): 168–87. http://dx.doi.org/10.2478/rtuect-2019-0012.

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Abstract Polymer-based matrix composite materials are in high demand in many different fields: aeronautics, pressure vessel manufacturing, wind turbine blade manufacturing, and others. Due to the great mechanical properties of fiber reinforced plastics, it is a desirable material for various applications, but at the same time its heterogenic structure makes the composite waste hard to recycle. This paper focuses on different fiber reinforced plastics (FRP) waste recycling methods and their comparison by carrying out literature review and using multi-criteria decision making analysis (MCDA). Four polymer matrix composite waste recycling methods are compared to calculate which one has the best sustainability performance based on the chosen criteria. Analytical Hierarchy Process and TOPSIS are applied for criteria weighing and method comparison. Sensitivity analysis is used to evaluate the obtained results. It is concluded that more studies concerning different FRP waste recycling method sustainability performance need to be done, to derive more data, that would make MCDA more reliable and also other FRP waste recycling methods could be compared. Another conclusion is that different methods have different strengths which makes it hard to compare them. While FRP waste recycling is getting more broadly used, there still is a lot of work to establish wide spread effective system of FRP waste recycling that is both economically viable and gives the best results concerning recycled material quality.

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44

Roth, Michael, Moritz Wolf, and Udo Lindemann. "Integrated Matrix-based Fault Tree Generation and Evaluation." Procedia Computer Science 44 (2015): 599–608. http://dx.doi.org/10.1016/j.procs.2015.03.027.

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45

Lyhagen, Johan. "A matrix evaluation of the moving-average representation." Economics Letters 55, no. 2 (August 1997): 179–83. http://dx.doi.org/10.1016/s0165-1765(97)00069-4.

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46

Palley, Igor, and Anthony J. Signorelli. "New Method for Evaluation of Fiber/Matrix Adhesion." Journal of Adhesion 25, no. 3 (May 1988): 161–67. http://dx.doi.org/10.1080/00218468808071259.

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47

Hu, Jurong, Ning Cao, Hao Lu, and Fei Wang. "Evaluation of Covariance Matrix in Distributed MIMO Radar." Intelligent Automation & Soft Computing 18, no. 7 (January 2012): 953–65. http://dx.doi.org/10.1080/10798587.2012.10643301.

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48

Soliman, Mostafa I., and Elsayed A. Elsayed. "Simple super-matrix processor: Implementation and performance evaluation." Journal of Parallel and Distributed Computing 83 (September 2015): 96–118. http://dx.doi.org/10.1016/j.jpdc.2015.06.001.

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49

Clonis, Yannis D. "Matrix evaluation for preparative high-performance affinity chromatography." Journal of Chromatography A 407 (January 1987): 179–87. http://dx.doi.org/10.1016/s0021-9673(01)92615-9.

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50

Chen, Liming, and Shin Hasegawa. "Color pixel arrangement evaluation for matrix display devices." Journal of the Institute of Television Engineers of Japan 44, no. 1 (1990): 77–80. http://dx.doi.org/10.3169/itej1978.44.77.

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