Статті в журналах: "Wavelet transformation in oriented basis"

1

Теreschenko, Tetyana, Iuliia Yamnenko, Oleksandr Melnychenko, Maryna Panchenko, and Liudmyla Laikova. "Analysis of image compression methods based on wavelet transforms for maritime applications." Pomorstvo 35, no. 2 (December 22, 2021): 395–401. http://dx.doi.org/10.31217/p.35.2.21.

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The purpose of the article is to develop recommendations for choosing image compression method based on wavelet transformation, depending on image type, quality and compression requirements. Among the wavelet image compression methods, Embedded Zerotree Wavelet coder (EZW) and Set Partition In Hierarchical Trees (SPIHT) are considered, and the Haar wavelet and wavelet transformation in the oriented basis with the first, third, fifth and seventh decomposition levels is used as the base wavelet transform. These compression methods were compared with each other and with the standard JPEG method on the following parameters: mean square error, maximum error, peak to noise ratio, number of bits per pixel, compression ratio, and image size. The proposed methods can be successfully applied in the transmission of seabed relief images obtained from satellites or sea buoys.

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2

Shinde, Ashok Naganath, Sanjay L. Lalbalwar, and Anil B. Nandgaonkar. "Modified meta-heuristic-oriented compressed sensing reconstruction algorithm for bio-signals." International Journal of Wavelets, Multiresolution and Information Processing 17, no. 05 (September 2019): 1950031. http://dx.doi.org/10.1142/s0219691319500310.

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In signal processing, several applications necessitate the efficient reprocessing and representation of data. Compression is the standard approach that is used for effectively representing the signal. In modern era, many new techniques are developed for compression at the sensing level. Compressed sensing (CS) is a rising domain that is on the basis of disclosure, which is a little gathering of a sparse signal’s linear projections including adequate information for reconstruction. The sampling of the signal is permitted by the CS at a rate underneath the Nyquist sampling rate while relying on the sparsity of the signals. Additionally, the reconstruction of the original signal from some compressive measurements can be authentically exploited using the varied reconstruction algorithms of CS. This paper intends to exploit a new compressive sensing algorithm for reconstructing the signal in bio-medical data. For this purpose, the signal can be compressed by undergoing three stages: designing of stable measurement matrix, signal compression and signal reconstruction. In this, the compression stage includes a new working model that precedes three operations. They are signal transformation, evaluation of [Formula: see text] and normalization. In order to evaluate the theta ([Formula: see text]) value, this paper uses the Haar wavelet matrix function. Further, this paper ensures the betterment of the proposed work by influencing the optimization concept with the evaluation procedure. The vector coefficient of Haar wavelet function is optimally selected using a new optimization algorithm called Average Fitness-based Glowworm Swarm Optimization (AF-GSO) algorithm. Finally, the performance of the proposed model is compared over the traditional methods like Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Firefly (FF), Crow Search (CS) and Glowworm Swarm Optimization (GSO) algorithms.

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3

Hryciw, Roman D., Hyon-Sohk Ohm, and Jie Zhou. "Theoretical Basis for Optical Granulometry by Wavelet Transformation." Journal of Computing in Civil Engineering 29, no. 3 (May 2015): 04014050. http://dx.doi.org/10.1061/(asce)cp.1943-5487.0000345.

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4

Xie, Haoyu, and Riki Honda. "Arbitrarily Oriented Phase Randomization of Design Ground Motions by Continuous Wavelets." Infrastructures 6, no. 10 (October 11, 2021): 144. http://dx.doi.org/10.3390/infrastructures6100144.

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For dynamic analysis in seismic design, selection of input ground motions is of huge importance. In the presented scheme, complex Continuous Wavelet Transform (CWT) is utilized to simulate stochastic ground motions from historical records of earthquakes with phase disturbance arbitrarily localized in time-frequency domain. The complex arguments of wavelet coefficients are determined as phase spectrum and an innovative formulation is constructed to improve computational efficiency of inverse wavelet transform with a pair of random complex arguments introduced and make more candidate wavelets available in the article. The proposed methodology is evaluated by numerical simulations on a two-degree-of-freedom system including spectral analysis and dynamic analysis with Shannon wavelet basis and Gabor wavelet basis. The result shows that the presented scheme enables time-frequency range of disturbance in time-frequency domain arbitrarily oriented and complex Shannon wavelet basis is verified as the optimal candidate mother wavelet for the procedure in case of frequency information maintenance with phase perturbation.

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5

Wu, Guang Li, Zhen Sen Wu, Shen Miao Han, and Guang Ling Wu. "Coding Algorithms of Aurora Image Compression Based on Wavelet Transformation." Advanced Materials Research 433-440 (January 2012): 5324–28. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.5324.

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This paper introduced some significant applications of aurora images, listed the main factors of choosing wavelet basis in image compression coding and analyzed the influence of aurora image compression effect caused by different wavelet basis were experimentally. The results of two kinds of significant wavelet transform algorithms EZW and SPIHT were analyzed, compared and also experimentally improved.

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6

Romanchak, V. M. "Wavelet transformation on a finite interval." Informatics 17, no. 4 (January 3, 2021): 22–35. http://dx.doi.org/10.37661/10.37661/1816-0301-2020-17-4-22-35.

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Integral transformations on a finite interval with a singular basis wavelet are considered. Using a sequence of such transformations, the problem of nonparametric approximation of a function is solved. Traditionally, it is assumed that the validity condition must be met for a basic wavelet (the average value of the wavelet must be zero). The paper develops the previously proposed method of singular wavelets when the tolerance condition is not met. In this case Delta-shaped functions that participate in Parzen – Rosenblatt and Nadaray – Watson estimations can be used as a basic wavelet. The set of wavelet transformations for a function defined on a numeric axis, defined locally, and on a finite interval were previously investigated. However, the study of the convergence of the decomposition on a finite interval was carried out only in one particular case. It was due to technical difficulties when trying to solve this problem directly. In the paper the idea of evaluating the periodic continuation of a function defined initially on a finite interval is implemented. It allowed to formulate sufficient convergence conditions for the expansion of the function in a series. An example of approximation of a function defined on a finite interval using the sum of discrete wavelet transformations is given.

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7

Romanchak, V. M. "Wavelet transformation on a finite interval." Informatics 17, no. 4 (January 3, 2021): 22–35. http://dx.doi.org/10.37661/10.37661/1816-0301-2020-17-4-22-35.

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Integral transformations on a finite interval with a singular basis wavelet are considered. Using a sequence of such transformations, the problem of nonparametric approximation of a function is solved. Traditionally, it is assumed that the validity condition must be met for a basic wavelet (the average value of the wavelet must be zero). The paper develops the previously proposed method of singular wavelets when the tolerance condition is not met. In this case Delta-shaped functions that participate in Parzen – Rosenblatt and Nadaray – Watson estimations can be used as a basic wavelet. The set of wavelet transformations for a function defined on a numeric axis, defined locally, and on a finite interval were previously investigated. However, the study of the convergence of the decomposition on a finite interval was carried out only in one particular case. It was due to technical difficulties when trying to solve this problem directly. In the paper the idea of evaluating the periodic continuation of a function defined initially on a finite interval is implemented. It allowed to formulate sufficient convergence conditions for the expansion of the function in a series. An example of approximation of a function defined on a finite interval using the sum of discrete wavelet transformations is given.

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8

Cai, Zhi Yuan, and Yi Xu. "An Arc Fault Current Interrupter Based on Wavelet Transformation." Applied Mechanics and Materials 313-314 (March 2013): 1262–65. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.1262.

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In real life , arc fault circuit interrupter plays a very important role to prevent the arc fault from fire about protecting the circuit.This article mainly introduces the types of arc,and the main purpose of designing this new type interrupter.The paper tells that it knows about the basic principle of wavelet transformation and use the wavelet tested data to be analyzed.The paper uses the window moving method to summarizes how to judge the basis of arc fault.Some kinds of loads are suitable and some are not.The paper also designs arc detection flow chart.It applies for effective basis for further.

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9

Yamnenko, Yuliia Serhiivna, Vitalii Viktorovych Levchenko, and Kateryna Serhiivna Niemchinova. "Method of Digital Video Processing Based on Wavelet-Transform in Oriented Basis." Microsystems, Electronics and Acoustics 23, no. 3 (June 30, 2018): 42–48. http://dx.doi.org/10.20535/2523-4455.2018.23.3.135399.

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10

Kuznetsov, K. M., I. V. Obolenskii, and A. A. Bulychev. "Potential field transformation on the basis of a continuous wavelet transform." Moscow University Geology Bulletin 71, no. 1 (January 2016): 112–20. http://dx.doi.org/10.3103/s0145875215060034.

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11

Cui, De Long, and Jing Long Zuo. "Retrieval Oriented Robust Audio Hashing." Advanced Materials Research 121-122 (June 2010): 854–59. http://dx.doi.org/10.4028/www.scientific.net/amr.121-122.854.

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Aiming at content-based audio retrieval (CBAR) applications, a robust audio hashing scheme is proposed. First the audio is divided to frame by fixed length and then low-frequent and high-frequent components are obtained by three-level lifting-based wavelet transformation in every frame. Secondly the audio frame is approximately represented as a product of a base matrix and an encoding matrix, or coefficient matrix, using non-negative matrix factorization (NMF). Finally the sum of each column in the coefficient matrix is calculated, which is then quantized to produce one bit of the hash sequence. Experiment results show that the proposed scheme is robust against Mp3 compression, Real compression, filtering, amplitude compression, equalization, echo, etc. It is insensitive to small local change, and therefore is suitable for distinguishing different audios.

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12

Li, Hua, Ling Ling Li, Shan Shan Huang, and Feng Qiang Li. "The Fault Line Selection Method of Small Current Grounding System Based on Wavelet Transformation." Advanced Materials Research 354-355 (October 2011): 149–52. http://dx.doi.org/10.4028/www.scientific.net/amr.354-355.149.

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In order to make full use of small current grounding system transient information and to improve the accuracy of fault line selection, a method based on wavelet transformation was proposed. On the basis of wavelets transformation theory and its characteristics, a proper wavelet function was chosen up to take wavelet transform to collected fault data, and then to get the fault line according to the modulus maxima theory. The MATLAB simulation results show the effectiveness of the proposed techniques on improving the accuracy of fault line selection.

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13

Indradewi, I. Gusti Ayu Agung Diatri, Ni Wayan Sumartini Saraswati, and NI Wayan Wardani. "COVID-19 Chest X-Ray Detection Performance Through Variations of Wavelets Basis Function." MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer 21, no. 1 (November 26, 2021): 31–42. http://dx.doi.org/10.30812/matrik.v21i1.1089.

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Our previous work regarding the X-Ray detection of COVID-19 using Haar wavelet feature extraction and the Support Vector Machines (SVM) classification machine has shown that the combination of the two methods can detect COVID-19 well but then the question arises whether the Haar wavelet is the best wavelet method. So that in this study we conducted experiments on several wavelet methods such as biorthogonal, coiflet, Daubechies, haar, and symlets for chest X-Ray feature extraction with the same dataset. The results of the feature extraction are then classified using SVM and measure the quality of the classification model with parameters of accuracy, error rate, recall, specification, and precision. The results showed that the Daubechies wavelet gave the best performance for all classification quality parameters. The Daubechies wavelet transformation gave 95.47% accuracy, 4.53% error rate, 98.75% recall, 92.19% specificity, and 93.45% precision.

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14

Кулькова and Varvara Kulkova. "TRANSFORMATION OF INTERNAL STABILITY SOCIALLY ORIENTED NON-PROFIT ORGANIZATIONS." Central Russian Journal of Social Sciences 10, no. 5 (October 20, 2015): 197–204. http://dx.doi.org/10.12737/14349.

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The article presents the results of the study of the components of the inner stability of NPOs in the case of daily practice in 2011-2014, three non-profit organizations of the Republic of Tatarstan (RT), various forms included in the register of NPOs. On the basis of monitoring of sites of NPOs, study of primary documents, expert survey the analysis of the components of internal sustainability of NPOs was conducted: management, internal image, staff, finance, services, and marketing. It is revealed: in the given time period there is no substantial transformation of internal sustainability of NPOs; non-profit organizations of various forms of type differentiation demonstrate sustainability; project management structure of the organization and the "quality" of the internal image and human capital in the NPO work to achieve internal stability of institutions. Reserves to increase the internal stability of NPOs are indicated: expansion of services on the basis of marketing technologies.

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15

Xiang, Xin Jian, and Zhang Lin. "Arc-Fault Detection Method Research Based on Wavelet Transformation." Advanced Materials Research 646 (January 2013): 240–44. http://dx.doi.org/10.4028/www.scientific.net/amr.646.240.

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The arc-fault is the main reason that cause electric fires. The technology of arc-fault circuit interrupters (AFCI) is the new circuit protection technology and it could avoid arc-fault causing fire effectively. The appearance of arc-fault can not be predicted. The traditional time domain or frequency domain analysis method for arc-fault signal processing is not ideal because it’s inaccurate and not in time. This paper bases on characteristics of arc-fault signals and analyzes the series connection arc-fault signal by Daubechies wavelet transform in 4 orders. As a result, it can provide the characteristics of arc-fault and detect arc-fault effectively and timely. This method is confirmed reliability by the simulation result and provides the theoretical basis of the development of AFCI.

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16

Akimov, Pavel A., and Marina L. Mozgaleva. "Correct Wavelet-Based Multilevel Numerical Method of Local Solution of Boundary Problems of Structural Analysis." Applied Mechanics and Materials 166-169 (May 2012): 3155–58. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.3155.

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The distinctive paper is devoted to correct wavelet-based multilevel numerical method of local solution of boundary problems of structural analysis. Operational and variational formulations of the problem (particularly with the use of wavelet basis) are presented. Computer-oriented algorithms of fast direct and inverse discrete Haar transforms are described. Due to special algorithms of averaging within multigrid approach, reduction of the problem is provided.

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17

Cheng, Liwei, Duanling Li, Xiang Li, and Shuyue Yu. "The Optimal Wavelet Basis Function Selection in Feature Extraction of Motor Imagery Electroencephalogram Based on Wavelet Packet Transformation." IEEE Access 7 (2019): 174465–81. http://dx.doi.org/10.1109/access.2019.2953972.

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18

Tang, Ning, Jin Cai, and Yuan Li. "An Enhanced Resolution Three-Dimensional Transformation Method Based on Discrete Wavelet Transform." Applied Mechanics and Materials 159 (March 2012): 41–45. http://dx.doi.org/10.4028/www.scientific.net/amm.159.41.

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With the development of interactive multimedia technologies, image and video compression algorithms necessitated a number of better performance and functionality. Wavelet transform based embedded image coding method is the basis of JPEG2000. Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. JPEG2000 algorithm has been developed based on the discrete wavelet transform (DWT) techniques, which have shown how the results achieved in different areas in information technology can be applied to enhance the performance.

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19

Winaya, I. Gede, and Ahmad Ashari. "Transformasi Skema Basis Data Relasional Menjadi Model Data Berorientasi Dokumen pada MongoDB." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 10, no. 1 (January 31, 2016): 47. http://dx.doi.org/10.22146/ijccs.11188.

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MongoDB is a database that uses document-oriented data storage models. In fact, to migrate from a relational database to NoSQL databases such as MongoDB is not an easy matter especially if the data are extremely complex. Based on the documentation that has been done by several global companies related to the use of MongoDB, it can be concluded that the process of migration from RDBMS to MongoDB require quite a long time. One process that takes quite a lot is transformation of relational database schema into a document-oriented data model on MongoDB. This research discusses the development transformation system of relational database schema to the document oriented data model in MongoDB. The process of transformation is done by utilizing the structure and relationships between tables in the scheme as the main parameters of the modeling algorithm. In the process of the modeling documents, it necessary to adjustments the specifications of MongoDB document that formed document model can be implemented in MongoDB. Document models are formed from transformation process can be a single document, embedded document, referenced document or combination of these. Document models are formed depending on the type, rules, and the value of the relationships cardinality between tables in the relational database schema.

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20

Isah, Abdulnasir, and Chang Phang. "Genocchi Wavelet-like Operational Matrix and its Application for Solving Non-linear Fractional Differential Equations." Open Physics 14, no. 1 (January 1, 2016): 463–72. http://dx.doi.org/10.1515/phys-2016-0050.

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AbstractIn this work, we propose a new operational method based on a Genocchi wavelet-like basis to obtain the numerical solutions of non-linear fractional order differential equations (NFDEs). To the best of our knowledge this is the first time a Genocchi wavelet-like basis is presented. The Genocchi wavelet-like operational matrix of a fractional derivative is derived through waveletpolynomial transformation. These operational matrices are used together with the collocation method to turn the NFDEs into a system of non-linear algebraic equations. Error estimates are shown and some illustrative examples are given in order to demonstrate the accuracy and simplicity of the proposed technique.

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21

Li, Xiaoguang, Guoli Feng, and Shengyue Hao. "Market-Oriented Transformation and Development of Local Government Financing Platforms in China: Exploratory Research Based on Multiple Cases." Systems 10, no. 3 (May 14, 2022): 65. http://dx.doi.org/10.3390/systems10030065.

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In recent years, the disorderly development of local government debt financing and local government financing platforms (GFP) in China has brought huge government debt risks. In order to control the debt increment caused by illegal financing of the GFP, the state has issued a series of documents. Under the new economic form, how to determine the position, choose the road, and plan the path of market-oriented development for high-quality economic development is critical to the GFP. This paper is committed to solving the key points and transformation paths of market-oriented transformation of the GFP. (1) On the basis of literature research, it analyzes the necessity, feasibility, and current transformation difficulties of market-oriented transformation of the GFP. (2) It defines the concept of the GFP and the concept of market-oriented transformation of the GFP. (3) It collates and analyzes the real cases of market-oriented transformation of four local government (county-level and above) financing platforms, studies the key points of transformation, and systematically summarizes the path of market-oriented transformation from three aspects: the goal, work plan, and implementation scheme of transformation and development. (4) Based on the idea of finding problems, diagnosing problems, optimizing, and improving, we put forward optimization strategy suggestions.

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22

Nazarkevych, Mariia, Natalia Kryvinska, and Yaroslav Voznyi. "Applying Ateb–Gabor Filters to Biometric Imaging Problems." Symmetry 13, no. 4 (April 19, 2021): 717. http://dx.doi.org/10.3390/sym13040717.

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This article presents a new method of image filtering based on a new kind of image processing transformation, particularly the wavelet-Ateb–Gabor transformation, that is a wider basis for Gabor functions. Ateb functions are symmetric functions. The developed type of filtering makes it possible to perform image transformation and to obtain better biometric image recognition results than traditional filters allow. These results are possible due to the construction of various forms and sizes of the curves of the developed functions. Further, the wavelet transformation of Gabor filtering is investigated, and the time spent by the system on the operation is substantiated. The filtration is based on the images taken from NIST Special Database 302, that is publicly available. The reliability of the proposed method of wavelet-Ateb–Gabor filtering is proved by calculating and comparing the values of peak signal-to-noise ratio (PSNR) and mean square error (MSE) between two biometric images, one of which is filtered by the developed filtration method, and the other by the Gabor filter. The time characteristics of this filtering process are studied as well.

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23

Al-Fahoum, A. S., and I. Howitt. "Combined wavelet transformation and radial basis neural networks for classifying life-threatening cardiac arrhythmias." Medical & Biological Engineering & Computing 37, no. 5 (September 1999): 566–73. http://dx.doi.org/10.1007/bf02513350.

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Xu, Yong. "Function Basis for Mechatronic System Design." Advanced Materials Research 284-286 (July 2011): 1401–7. http://dx.doi.org/10.4028/www.scientific.net/amr.284-286.1401.

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A new function-oriented theoretical basis for mechatronic system design is presented in the paper, with a technology-independent functional description of such aspects in a mechatronic system as 1) relations and distinctions among purpose function, transformation function and state transition and 2) structure of information processing. All discussions are summarized in a set of principles, which consequently form the basis for devising design models and methods for mechatronic systems.

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25

Xiao, Hai Ping, Lan Lan Chen, Yi Qiang Chen, and Zhong Qun Guo. "Research and Application of Grey Predictive Model Based on Wavelet Analysis." Applied Mechanics and Materials 170-173 (May 2012): 2912–16. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.2912.

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It is the scientific basis of instructing the project to produce and operate that the deformation is monitored, and the analysis and prediction in constructing and operating of project is one of the important jobs. In order to analyze and predict the deformation of the project more timely and accurately, the paper analyzed and established the feasibility of wavelet-grey predicting model on the basis of the grey system theory in modeling limitations and the characteristics of wavelet transformation. With the comparison of predictive datas in two kinds of models, the results show, the predictive datas of the wavelet-grey model are more accurately than grey model’s, and has achieved good results in prediction of the engineering, is a feasible method.

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26

Tereshchenko, T., T. Khyzhniak, L. Laikova, and A. Parkhomenko. "RESEARCH OF AUTOCORRELATION FUNCTION USING THE TRANSFORMATION IN ORIENTED BASIS IN ELECTRICAL CIRCUITS." Tekhnichna Elektrodynamika 2016, no. 4 (June 14, 2016): 29–31. http://dx.doi.org/10.15407/techned2016.04.029.

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27

Lomаtenkov, D. A., and J. V. Gnezdova. "The innovation transformation of telecom industry." Voprosy regionalnoj ekonomiki 38, no. 1 (March 30, 2019): 75–79. http://dx.doi.org/10.21499/2078-4023-2019-38-1-75-79.

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In article is considered investments into development of telecom industry on the basis of digital technologies, contrary to popular belief which optional should be long-term. At the same time adaptation of organizational model and development of the corporate culture oriented to innovations – one of the most important conditions of success. At the same time the Russian telecommunication sector is at an early stage of development in all directions of digital conversions.

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Fritz-Popovski, Gerhard. "Two-dimensional indirect Fourier transformation for evaluation of small-angle scattering data of oriented samples." Journal of Applied Crystallography 46, no. 5 (September 18, 2013): 1447–54. http://dx.doi.org/10.1107/s002188981302150x.

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An extension of the indirect Fourier transformation method for two-dimensional small-angle scattering patterns is presented. This allows for a model-free investigation of real-space functions of oriented structures. The real-space function is built from two-dimensional basis functions. The Fourier transformed basis functions are approximated to the scattering pattern. The solution to this problem in reciprocal space can be used to compute the corresponding real-space functions. These real-space functions contain information on size, shape, internal structure and orientation of the structures studied. Information on structures that are oriented in different distinct directions can be partly separated. The applicability of the technique is demonstrated on simulated data of oriented cuboids and on two experimental data sets based on the nanostructure of spruce normal wood.

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Liu, Feng Qin, and Peng Miao. "Analogical Basis Decomposition for Randomized Sampling Signal Reconstruction." Applied Mechanics and Materials 58-60 (June 2011): 1517–22. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1517.

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Signal restoration from randomly sampling is needed in many different application environments, like time efficiency and low-power device or hardware failure. In this paper, we use the Analogical Basis Decomposition (ABD) theory to restore the signal by randomized sampling data in frequency domain. Based on the ABD theory, once standard basis are defined in the signal domain, the corresponding analogical basis can be obtained by randomized sampling each base in the frequency domain. Randomly sampled signal can be represented as sum of weighted analogical basis. We developed a fast matching pursuit technique to estimate the weights of analogical basis and then restore the signal. Actually, ABD theory can be used for signal restoration in other transformation domain (like wavelet transformation). Finally, we apply the ABD theory to reconstruct 2-D MR image based on partial sampling data ink-space.

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30

Zhang, Yu Jun, Mei Xiang, and Ying Tian. "An Efficient Ear Recognition Method from Two-Dimensional Images." Advanced Materials Research 1049-1050 (October 2014): 1531–35. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1531.

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An efficient ear recognition method by weighted wavelet transformation and Bi-Directional principal component analysis was proposed. First, each ear image was decomposed into four sub-images by wavelet transformation ,the four sub-images were low frequency image , vertical detail image ,horizontal detail image and high frequency image .Then the low frequency image was decomposed into four sub-images, the four-images were weighted by different coefficients, then ,the four sub-images were reconstructed into a image .On this basis ,the feature was extraction by the BDPCA method ,and then we use the k-Nearest Neighbor Classification to recognition .Experimental results show that the method have high recognition rate and shorted training time.

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Chakraborty, Avijit, and David Okaya. "Frequency‐time decomposition of seismic data using wavelet‐based methods." GEOPHYSICS 60, no. 6 (November 1995): 1906–16. http://dx.doi.org/10.1190/1.1443922.

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Анотація:

Spectral analysis is an important signal processing tool for seismic data. The transformation of a seismogram into the frequency domain is the basis for a significant number of processing algorithms and interpretive methods. However, for seismograms whose frequency content vary with time, a simple 1-D (Fourier) frequency transformation is not sufficient. Improved spectral decomposition in frequency‐time (FT) space is provided by the sliding window (short time) Fourier transform, although this method suffers from the time‐ frequency resolution limitation. Recently developed transforms based on the new mathematical field of wavelet analysis bypass this resolution limitation and offer superior spectral decomposition. The continuous wavelet transform with its scale‐translation plane is conceptually best understood when contrasted to a short time Fourier transform. The discrete wavelet transform and matching pursuit algorithm are alternative wavelet transforms that map a seismogram into FT space. Decomposition into FT space of synthetic and calibrated explosive‐source seismic data suggest that the matching pursuit algorithm provides excellent spectral localization, and reflections, direct and surface waves, and artifact energy are clearly identifiable. Wavelet‐based transformations offer new opportunities for improved processing algorithms and spectral interpretation methods.

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Демененко, Inna Demenenko, Данакин, Nikolay Danakin, Шавырина, and Irina Shavyrina. "Client-oriented organizational culture as a vector of transformation of Higher school." Central Russian Journal of Social Sciences 11, no. 4 (August 29, 2016): 12–17. http://dx.doi.org/10.12737/21313.

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In the article the role of organizational culture as a customer-oriented trajectory of management at university is considered. The authors analyze the main clients of the educational environment on the basis of which the model of customer-oriented organizational culture of the university is proposed, reflecting the structural platform of organizational culture, the integration of internal and external customers in the socio-cultural environment of the university, as well as sequential communications and transformations of external customers in the internal customers.

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Chen, Guobin, та Nanying Luo. "Network Actual Traffic Prediction Algorithm Based on α-stable Distribution and Wavelet Transformation". Cybernetics and Information Technologies 14, № 4 (31 січня 2015): 45–55. http://dx.doi.org/10.1515/cait-2014-0004.

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Abstract In order to improve the prediction precision of wireless sensor network traffic, a new prediction algorithm (State Prediction algorithm based on α-stable distribution α, SP-α) is proposed, combined with α-stable distribution and wavelet transformation. The algorithm proposed first defines the characteristics of α-stable distribution and then gives the judge basis that obeys α-stable distribution. At the same time, it reduces the prediction error of the actual traffic by fusion of the prediction results of α-stable distribution with wavelet transformation. Finally, the paper thoroughly researches the key factors impacting on the new algorithm through simulations in OPNET and MATLAB. Compared with the performance of FARIMA model, the simulation results proved that SP-α algorithm has better adaptability.

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Sakrutina, E. A. "To a Question of Predicting Model Stability on the Basis of Multiple Scale Wavelet Transformation." Proceedings of the Southwest State University 23, no. 2 (July 9, 2019): 109–23. http://dx.doi.org/10.21869/2223-1560-2019-23-2-109-123.

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Purpose of research. The article is devoted to the development of production predicting models and their stability conditions.Methods: Predicting models are actively used in modern control systems, in information support intellectual systems of decision-making. They have a huge role in any activity connected with signals' processing including anomalies detection of various technological processes and assessment of risk potential of critical information infrastructure objects. They can also be used in monitoring systems of security threats. Special class among predicting models is represented by the models based on experiences of proceeding processes (for example, regularities taken from the data which are saved up as a result of an object work).Results. Virtual "instant" model of an object belonging to this class is described in the article. It is presented taking into account multiple and large-scale decomposition of entrance influences vectors and the forecast of an object output. The described model gives the forecast without possible future conditions of an expected background. The approach based on the wavelet-analysis which is characterized by a unique opportunity of detailed frequency analysis in time is developed for stability study of virtual "instant" model. Stability conditions of the predicting model are received on the basis of this approach. This model has allocation conditions for approximating and detailing components for four types of ratios between memory depth on input and output.Conclusion: Predicting model of oil processing in which memory depth on an input is more than memory depth on output is described in the article. It is shown that the accuracy of virtual "instant" model forecast is higher than linear predicting model has at rare data of laboratory analysis. One of stability conditions depending on decomposition depth is shown for the constructed model. On the basis of received results analysis it is possible to draw a conclusion on applicability of received stability conditions for risk potential assessment of process development forecast implementation in monitoring systems of security threats.

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Golovnin, Oleg, and Anastasia Stolbova. "Wavelet Analysis as a Tool for Studying the Road Traffic Characteristics in the Context of Intelligent Transport Systems with Incomplete Data." SPIIRAS Proceedings 18, no. 2 (April 12, 2019): 326–53. http://dx.doi.org/10.15622/sp.18.2.326-353.

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A frequent problem of traffic flow characteristics acquisition is data loss, which leads to uneven time series analysis. An effective approach to uneven data analysis is the spectral analysis, which requires obtaining process with a constant sampling interval, for example, by restoring missing data, which leads to the appearance of dating error. Thus, the main purpose of this study is to develop a method and software for wavelet analysis of traffic flow characteristics without restoring the missing data. To analyze and interpret non-stationary uneven time series obtained from traffic monitoring systems, we propose the wavelet transformation method with adjustment of the sampling intervals, which results in a time-frequency domain with a constant sampling interval. Wavelet analysis is applied to the macroscopic traffic flow characteristics. We developed the software for traffic flow wavelet analysis on the "ITSGIS" intelligent transport geo-information framework using the attribute-oriented approach. Wavelet analysis of traffic flows characteristics using Morlet wavelets was accomplished for data analysis of the city of Aarhus, Denmark. Wavelet spectra and scalograms were constructed and analyzed, general dependencies in the frequency distribution of extremes, and differences in spectral power were revealed. The developed software is being experimentally tested in solving practical problems of municipalities and road agencies in Russia.

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36

Lin, Jian-Fu, Junfang Wang, Li-Xin Wang, and Siu-seong Law. "Structural Damage Diagnosis-Oriented Impulse Response Function Estimation under Seismic Excitations." Sensors 19, no. 24 (December 9, 2019): 5413. http://dx.doi.org/10.3390/s19245413.

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Impulse response function (IRF) is an ideal structural damage index for the identification of structural damage associated with changes in modal properties. However, IRFs from multiple excitations applied at different degrees-of-freedoms jointly contribute to the dynamic response, and their estimation is often underdetermined. Although some efforts have been devoted to the estimation of IRF for a structure under single excitation, the case under multiple excitations has not been fully investigated yet. The estimation of IRF under multiple excitations is generally an ill-conditioned inverse problem such that an incorrect or non-feasible solution is common, preventing its application to damage detection. This work explores this problem by introducing dimensionality reduction transformation matrices relating two sets of IRFs of a structure with discussions on the performance of the non-unique transformation matrices. Then, the extraction of IRF via wavelet-based and Tikhonov regularization-based methods are compared. Finally, a numerical study with a truss structure is conducted to validate the estimation of the IRFs and to demonstrate their applicability for damage detection under seismic excitations. Both the damage locations and severity are accurately identified, indicating the proposed methodology can enable the IRFs estimation under multiple excitations for successful damage detection.

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37

Nahar, A. K. "A Compression Original Image Based On The DDWT Technique And Enhancement SNR." International Journal of Engineering Technology and Sciences 5, no. 3 (December 27, 2018): 73–89. http://dx.doi.org/10.15282/ijets.v5i3.1132.

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Generally, Discrete wavelet transform (DWT) are good perform a when little to no simple mathematical operations in the wavelet basis, in many applications, wavelet transforms can be severely truncated compressed and retain useful information Image compression. Though, DWT and the divided wavelet transform, still suffering from Poor directionality Lack of phase information, and Shift- sensitivity, which is a major drawback in most the communications systems. The Double-Density Discrete Wavelet Transform (DDDWT) achieves great results compared to previous conventional methods less complexity. Credited with this good result, so due to a simplified account that deal with two-dimensional and three-dimensional images by the way and transformation matrices as if through a matrix multiplication between the picture and the conversion of number DDWT. Moreover, the form of repeated goal is achieved with the optimization process for the appropriate application.

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Komorska, Iwona. "Diagnostic-Oriented Vibroacoustic Model of the Reciprocating Engine." Solid State Phenomena 180 (November 2011): 214–21. http://dx.doi.org/10.4028/www.scientific.net/ssp.180.214.

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The method of modelling the signal of vibrations of the internal combustion engine based on the discrete wavelet transform (DWT), is presented in the paper. This method is suitable for the representation of transient processes, which occur in the vibroacoustic signal (VA) generated by the engine. The model is identified on the basis of the vibration signal recorded during the car driving at a constant speed. The base model and its measures are created for the new engine and the control measurements, performed either at the determined time periods or car mileage, are compared to them. This base model must be actualised after each engine overhaul and as its wear and tear progresses, due to changes of the vibration characteristics. On account of a random character of vibration responses the envelope of the modelled signal is utilised for diagnostic purposes. The model based diagnostic method was verified in the paper on the example of the engine exhaust valve defect.

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Voronin, Dmitry, Pavel Kuznetsov, and Vladislav Evstigneev. "Urban sustainable development using qualimetry procedures of digital transformation." E3S Web of Conferences 291 (2021): 04008. http://dx.doi.org/10.1051/e3sconf/202129104008.

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The use of information technologies to improve the efficiency of organizing the functioning of urban processes and the provision of innovative services forms the basis of the concept of smart sustainable city. Society mistakenly identify the digital transformation of the urban environment with the unsystematic, redundant introduction of technical innovations into the citizens’ life. This is because the changes made to the habitual processes of citizens' life often do not pass the mandatory check for their balance in terms of compliance with principles of sustainable development. The article proposes a new conceptual approach for assessing the effectiveness of the implemented solutions related to the implementation of the paradigm that ensures the transition from technology-oriented to human-oriented concept of “Sustainable Smart Cities”. The main idea is to consider the transformation of the urban environment through the prism of changes in the functional state of its objects.

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Владимир Викторович, Тарновский, Полянин Андрей Витальевич, and Кулакова Людмила Ивановна. "FEATURES OF ORGANIZATIONAL BEHAVIOR IN SOCIALLY ORIENTED ENTREPRENEURIAL STRUCTURES." STATE AND MUNICIPAL MANAGEMENT SCHOLAR NOTES 4, no. 4 (December 2021): 54–59. http://dx.doi.org/10.22394/2079-1690-2021-1-4-54-59.

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The authors have formed a scheme of group organizational behavior in a socially oriented entrepreneurial structure, in which all components are closely interconnected, and they must be considered in a single complex of elements and parameters that give an idea of the behavior of all employees of the organization. Several groups formed in a socially oriented entrepreneurial structure together with group and intergroup communication interaction, functioning relationships of individual participants and whole groups form the group structure of organizational behavior. The authors carried out the transformation of the basic elements on the basis of the "Edgar Shein pyramid" for the formation of organizational culture in an organization carrying out entrepreneurial activity. The forms and types of communication interaction in a socially oriented entrepreneurial structure are structured. The author's matrix of management paradigms in economic and social systems has been formed, which clearly demonstrates that, depending on the transformation of attitudes towards a person in personnel policy and the transition from the economic plane to the socio-economic one, the tools for working with employees will change, and accordingly the landscape of organizational culture will change, which will lead to a transformation in organizational behavior and modifications of communication interactions.

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41

Zhang, Hua, Shu Yan Zhang, Li Jia Wang, and Guo Zhen Wang. "Edge Detection Using the Multi-Oriented Local Energy." Applied Mechanics and Materials 568-570 (June 2014): 638–42. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.638.

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To detect the edge of object, an efficient scheme based on the Multi-Oriented Local Energy (MOLE) is presented. The MOLE is constructed by Multi-oriented Gaussian second differential and its Hilbert transformation. The Multi-oriented Gaussian second differential is obtained by using a linear combination of basis filters with arbitrary orientations. To overcome the affection of illumination, Phase Congruency is employed by normalizing the directional energies. At last, our method is compared with other common methods. The experimental results reveal that this method can extract more continuous edge and obtain more details.

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42

Dastan, Aysegul, and Roland N. Horne. "Robust Well-Test Interpretation by Using Nonlinear Regression With Parameter and Data Transformations." SPE Journal 16, no. 03 (March 29, 2011): 698–712. http://dx.doi.org/10.2118/132467-pa.

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Summary Nonlinear regression is a well-established technique in well-test interpretation. However, this widely used technique is vulnerable to issues commonly observed in real data sets—specifically, sensitivity to noise, parameter uncertainty, and dependence on starting guess. In this paper, we show significant improvements in nonlinear regression by using transformations on the parameter space and the data space. Our techniques improve the accuracy of parameter estimation substantially. The techniques also provide faster convergence, reduced sensitivity to starting guesses, automatic noise reduction, and data compression. In the first part of the paper, we show, for the first time, that Cartesian parameter transformations are necessary for correct statistical representation of physical systems (e.g., the reservoir). Using true Cartesian parameters enables nonlinear regression to search for the optimal solution homogeneously on the entire parameter space, which results in faster convergence and increases the probability of convergence for a random starting guess. Nonlinear regression using Cartesian parameters also reveals inherent ambiguities in a data set, which may be left concealed when using existing techniques, leading to incorrect conclusions. We proposed suitable Cartesian transform pairs for common reservoir parameters and used a Monte Carlo technique to verify that the transform pairs generate Cartesian parameters. The second part of the paper discusses nonlinear regression using the wavelet transformation of the data set. The wavelet transformation is a process that can compress and denoise data automatically. We showed that only a few wavelet coefficients are sufficient for an improved performance and direct control of nonlinear regression. By using regression on a reduced wavelet basis rather than the original pressure data points, we achieved improved performance in terms of likelihood of convergence and narrower confidence intervals. The wavelet components in the reduced basis isolate the key contributors to the response and, hence, use only the relevant elements in the pressure-transient signal. We investigated four different wavelet strategies, which differ in the method of choosing a reduced wavelet basis. Combinations of the techniques discussed in this paper were used to analyze 20 data sets to find the technique or combination of techniques that works best with a particular data set. Using the appropriate combination of our techniques provides very robust and novel interpretation techniques, which will allow for reliable estimation of reservoir parameters using nonlinear regression.

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43

Genin, B. L., and Y. V. Zontov. "Digital Transformation of the Patent Information Services." Intellectual property law 1 (March 25, 2021): 14–18. http://dx.doi.org/10.18572/2072-4322-2021-1-14-18.

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Relevance. At present, there are significant changes in the modern systems of official publication of patent offices. The paper discusses the concept of digital transformation in relation to official publication systems and the construction of a client-oriented Agency. The new publication requirements include requirements for effective search for information about inventions and utility models, requirements for providing information about changes in legal status, requirements for providing analytical information, and requirements for citation information. Methodology: the research is based on complex and systematic analysis, general scientific methods of cognition-analysis and synthesis, dialectical method, systematization and classification, process and system approaches, as well as the method of comparison. Results. New goals of the publication system and requirements for Electronic publication systems as information service systems are formulated. It is proposed to create and develop new electronic publishing systems based on the use of customer-oriented digital platforms of the service architecture. The main point of contention is that the improvement of electronic publishing systems of patent offices and their transformation into information service systems, with its huge public benefit, can become a negative factor for commercial enterprises that provide search and information services on a paid basis.

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Guryleva, Anastasiya V., Alexei M. Khorokhorov, and Vitaly S. Kobozev. "Methods Of Increasing Spectral Resolution Of Imaging Spectrometers Built On The Basis Of Multi–channel Radiation Detectors." Volume 28, Number 6, 2020, no. 03-2020 (December 2020): 95–104. http://dx.doi.org/10.33383/2019-098.

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The article proposes the methods of object shooting by means of a spectrometer based on a multi-channel radiation detector and further processing of its results allowing spectral resolution of such spectrometers significantly to increase with the same original spatial resolution. The mathematical model of the shooting process is provided. It is determined that restoration of spectral radiance of objects based on the shooting data using the proposed method is a mathematically incorrect inverse task. The Greville method, the method of wavelet transformation, the Tikhonov regularisation method, and the Godunov method were considered as methods for its solution. The results of computational modelling of the considered methods are shown and it is found that restoration of spectral radiance of objects based on the shooting data using the considered methods is possible and relative error of restoration is at a fraction of per cent scale. It is determined that the wavelet transformation method is an optimal method of solution of the incorrect spectral radiance restoration task. It is also shown that the proposed method of imaging spectrometry is applicable both when using matrix radiation detectors with increased number of narrow-band filters and when using widely spread standard three-channel matrix RGB detectors of radiation.

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45

Peng, Kai. "The Application of Sets of Orthogonal Function to Signal Analyses." Applied Mechanics and Materials 380-384 (August 2013): 3613–17. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3613.

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Generally speaking, the method of signal analysis is built on the basis that signal decomposition is an orthogonal component. There are different selection ways for the sets of orthogonal functions after transformation and the transformation of orthogonal functions does not affect expressed functions themselves. Aiming at different requirements for application, different sets of orthogonal functions need to be used. This thesis not only studies classical and modern sets of orthogonal functions Fourier and wavelet sequence but also proposes prospects for the new application of the sets of orthogonal functions.

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Lara, Juan De, Esther Guerra, and Jörg Kienzle. "Facet-oriented Modelling." ACM Transactions on Software Engineering and Methodology 30, no. 3 (May 2021): 1–59. http://dx.doi.org/10.1145/3428076.

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Models are the central assets in model-driven engineering (MDE), as they are actively used in all phases of software development. Models are built using metamodel-based languages, and so objects in models are typed by a metamodel class. This typing is static, established at creation time, and cannot be changed later. Therefore, objects in MDE are closed and fixed with respect to the class they conform to, the fields they have, and the well-formedness constraints they must comply with. This hampers many MDE activities, like the reuse of model-related artefacts such as transformations, the opportunistic or dynamic combination of metamodels, or the dynamic reconfiguration of models. To alleviate this rigidity, we propose making model objects open so that they can acquire or drop so-called facets . These contribute with a type, fields and constraints to the objects holding them. Facets are defined by regular metamodels, hence being a lightweight extension of standard metamodelling. Facet metamodels may declare usage interfaces , as well as laws that govern the assignment of facets to objects (or classes). This article describes our proposal, reporting on a theory, analysis techniques, and an implementation. The benefits of the approach are validated on the basis of five case studies dealing with annotation models, transformation reuse, multi-view modelling, multi-level modelling, and language product lines.

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47

Li, Wenlong, and Haibin Qu. "Wavelet-based classification and influence matrix analysis method for the fast discrimination of Chinese herbal medicines according to the geographical origins with near infrared spectroscopy." Journal of Innovative Optical Health Sciences 07, no. 04 (July 2014): 1350061. http://dx.doi.org/10.1142/s1793545813500612.

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A discriminant analysis technique using wavelet transformation (WT) and influence matrix analysis (CAIMAN) method is proposed for the near infrared (NIR) spectroscopy classification. In the proposed methodology, NIR spectra are decomposed by WT for data compression and a forward feature selection is further employed to extract the relevant information from the wavelet coefficients, reducing both classification errors and model complexity. A discriminant-CAIMAN (D-CAIMAN) method is utilized to build the classification model in wavelet domain on the basis of reduced wavelet coefficients of spectral variables. NIR spectra data set of 265 salviae miltiorrhizae radix samples from 9 different geographical origins is used as an example to test the classification performance of the algorithm. For a comparison, k-nearest neighbor (KNN), linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) methods are also employed. D-CAIMAN with wavelet-based feature selection (WD-CAIMAN) method shows the best performance, achieving the total classification rate of 100% in both cross-validation set and prediction set. It is worth noting that the WD-CAIMAN classifier also shows improved sensitivity, selectivity and model interpretability in the classifications.

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48

Wang, Gui Cheng, Jun Jian Yu, Jian Chen, and Wei Song. "Analysis of Vibration Signals Caused by Unbalance of the HSK Shank." Materials Science Forum 723 (June 2012): 269–74. http://dx.doi.org/10.4028/www.scientific.net/msf.723.269.

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Unbalance vibration is introduced. The reasons of HSK shank unbalance and the features of vibration signal are analyzed. The method of signal essing is described. Finally, transformation and reconstruction of the vibration signal are studied by wavelet theory. HSK shank’s vibration is more accurately extracted. This way can be a good basis for scientific research and the development of the HSK integrated measurement system.

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49

Dyeyeva, Nataliya, and Mykola Ziniuk. "THEORETICAL BASIS OF CAPITALIZATION MANAGEMENT OF THE ENTERPRISE." Economics: time realities 3, no. 49 (June 23, 2020): 79–86. http://dx.doi.org/10.15276/etr.03.2020.10.

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Even today we can predict that the main consequence of the new technological wave will be that the cost of labor will cease to be decisive in the formation of production costs. This means that the low-skilled labor force that makes up developing countries and some sectors of the Ukrainian economy will cease to be significant. And the main factor will be the technological potential. Ukrainian higher education institutions also see great prospects in the further development of digitalization. Digital business transformation is a smarter result. The combination of digital technologies with the organizational and human changes needed to build a digital information-oriented culture allows organizations, including corporate entities, to significantly increase business efficiency

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50

Li, Deng-ao, Jie Zhou, Jumin Zhao, and Xinyan Liu. "J Wave Autodetection Using Analytic Time-Frequency Flexible Wavelet Transformation Applied on ECG Signals." Mathematical Problems in Engineering 2018 (May 31, 2018): 1–11. http://dx.doi.org/10.1155/2018/6791405.

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As a new important index of the electrocardiogram (ECG) of ventricular bipolar play, J wave plays an increasingly significant role in the clinical diagnosis. The existence of J wave hints at potential crisis of fatal disease and even death. Nowadays, however, it can hardly meet the clinical needs where the diagnosis of J wave variation only depends on experience of clinicians. Therefore, a new technique which is capable of detecting J wave using analytic time-frequency flexible wavelet transformation (ATFFWT) is proposed in this paper. We have used ATFFWT to decompose the processed ECG signals into the desired subbands. Further, Fuzzy Entropy (FE) is computed from each subband to capture more hidden and meaningful information. Feature scoring method is applied to select optimal feature set. Finally, the extracted features are fed to Least Squares-Support Vector Machine (LS-SVM) classifier. The 10-fold cross validation is used to obtain reliable and stable performance and to avoid the overfitting of the model. Our proposed algorithm has achieved accuracy of 97.61% for Morlet Wavelet (MW) kernel in comparison to 97.56% for Radial Basis Function (RBF) kernel. The developed effective algorithm can be used to design an expert system to aid clinicians in their regular diagnosis.

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