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Artykuły w czasopismach na temat „BEMD”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Mohammed, Arrazaki Othman El Ouahabi Mohamed Zohry Adel Babbah. "Enhancing BEMD decomposition using adaptive support size for CSRBF functions." Indonesian Journal of Electrical Engineering and Computer Science 38, no. 1 (2025): 172–81. https://doi.org/10.11591/ijeecs.v38.i1.pp172-181.

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Despite their widespread development, the Fourier transform and wavelet transform are still unsuitable for analyzing non-stationary and non-linear signals. To address this limitation, bidimensional empirical mode decomposition (BEMD) has emerged as a promising technique. BEMD effectively extracts structures at various scales and frequencies but faces significant computational complexity, primarily during the extremum interpolation phase. To mitigate this, different interpolation functions were presented and suggested, with BEMD using compactly supported radial basis functions (BEMD-CSRBF) show

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Arrazaki, Mohammed, Othman El Ouahabi, Mohamed Zohry, and Adel Babbah. "Enhancing BEMD decomposition using adaptive support size for CSRBF functions." Indonesian Journal of Electrical Engineering and Computer Science 38, no. 1 (2025): 172. https://doi.org/10.11591/ijeecs.v38.i1.pp172-181.

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<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>Despite their widespread development, the Fourier transform and wavelet transform are still unsuitable for analyzing non-stationary and non-linear signals. To address this limitation, bidimensional empirical mode decomposition (BEMD) has emerged as a promising technique. BEMD effectively extracts structures at various scales and frequencies but faces significant computational complexity, primarily during the extremum interpolation phase. To mitigate this, different interpolation functions we

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Seifert, Christina, Jordan Vokes, Aaron Roberts, John Gorczyca, and Kyle Judd. "Simultaneous Bilateral Extensor Mechanism Disruptions: More Than Double the Trouble?" Journal of Knee Surgery 33, no. 09 (2019): 899–902. http://dx.doi.org/10.1055/s-0039-1688779.

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AbstractSimultaneous bilateral extensor mechanism disruption (BEMD) is a rare condition, for which the relationship between comorbid conditions, complications, and clinical outcomes has not been well defined. We hypothesized that patients with BEMD would have more comorbidities, more repair failures, and worse clinical outcomes compared with patients with unilateral extensor mechanism disruption (UEMD). We performed a retrospective review of all adult patients seen at our institution for either a quadriceps or patellar tendon rupture between 2012 and 2017. Statistical analysis was conducted us

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Jones, Lee, Susan R. Bryan, and David P. Crabb. "Gradually Then Suddenly? Decline in Vision-Related Quality of Life as Glaucoma Worsens." Journal of Ophthalmology 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/1621640.

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Purpose. To evaluate the relationship between self-reported vision-related quality of life (VRQL) and visual field (VF) loss in people from glaucoma clinics. Methods. A postal survey using the National Eye Institute Visual Function Questionnaire (NEI VFQ-25) was administered to people with a range of VF loss identified from a UK hospital-based glaucoma service database. Trends were assessed in a composite score from NEI VFQ-25 against better-eye mean deviation (BEMD) using linear regression and a spline-fitting method that can highlight where a monotonic relationship may have different stages.

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BHUIYAN, SHARIF M. A., JESMIN F. KHAN, and REZA R. ADHAMI. "A NOVEL APPROACH OF EDGE DETECTION VIA A FAST AND ADAPTIVE BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION METHOD." Advances in Adaptive Data Analysis 02, no. 02 (2010): 171–92. http://dx.doi.org/10.1142/s1793536910000446.

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A novel approach of edge detection is proposed that utilizes a bidimensional empirical mode decomposition (BEMD) method as the primary tool. For this purpose, a recently developed fast and adaptive BEMD (FABEMD) is used to decompose the given image into several bidimensional intrinsic mode functions (BIMFs). In FABEMD, order statistics filters (OSFs) are employed to get the upper and lower envelopes in the decomposition process, instead of surface interpolation, which enables fast decomposition and well-characterized BIMFs. Binarization and morphological operations are applied to the first BIM

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BHUIYAN, SHARIF M. A., NII O. ATTOH-OKINE, KENNETH E. BARNER, ALBERT Y. AYENU-PRAH, and REZA R. ADHAMI. "BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION USING VARIOUS INTERPOLATION TECHNIQUES." Advances in Adaptive Data Analysis 01, no. 02 (2009): 309–38. http://dx.doi.org/10.1142/s1793536909000084.

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Scattered data interpolation is an essential part of bidimensional empirical mode decomposition (BEMD) of an image. In the decomposition process, local maxima and minima of the image are extracted at each iteration and then interpolated to form the upper and the lower envelopes, respectively. The number of two-dimensional intrinsic mode functions resulting from the decomposition and their properties are highly dependent on the method of interpolation. Though a few methods of interpolation have been tested and/or applied to the BEMD process, many others remain to be tested. This paper evaluates

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Li, Hongyi, Chaojie Wang, and Di Zhao. "An Improved EMD and Its Applications to Find the Basis Functions of EMI Signals." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/150127.

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A B-spline empirical mode decomposition (BEMD) method is proposed to improve the celebrated empirical mode decomposition (EMD) method. The improvement of BEMD on EMD mainly concentrates on the sifting process. First, instead of the curve that resulted from computing the average of upper and lower envelopes, the curve interpolated by the midpoints of local maximal and minimal points is used as the mean curve, which can reduce the cost of computation. Second, the cubic spline interpolation is replaced with cubic B-spline interpolation on account of the advantages of B-spline over polynomial spli

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Cheng, Cheng, Weipeng Li, Adrián Lozano-Durán, and Hong Liu. "Identity of attached eddies in turbulent channel flows with bidimensional empirical mode decomposition." Journal of Fluid Mechanics 870 (May 15, 2019): 1037–71. http://dx.doi.org/10.1017/jfm.2019.272.

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Bidimensional empirical mode decomposition (BEMD) is used to identify attached eddies in turbulent channel flows and quantify their relationship with the mean skin-friction drag generation. BEMD is an adaptive, non-intrusive, data-driven method for mode decomposition of multiscale signals especially suitable for non-stationary and nonlinear processes such as those encountered in turbulent flows. In the present study, we decompose the velocity fluctuations obtained by direct numerical simulation of channel flows into BEMD modes characterized by specific length scales. Unlike previous works (e.g

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Ribstein, C., D. Courteix, N. Rabiau, et al. "Secondary Bone Defect in Neuromuscular Diseases in Childhood: A Longitudinal “Muscle-Bone Unit” Analysis." Neuropediatrics 49, no. 06 (2018): 397–400. http://dx.doi.org/10.1055/s-0038-1666846.

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AbstractTo evaluate the potential bone defect in neuromuscular diseases, we conducted a longitudinal study including three groups of patients: 14 Duchenne muscular dystrophies (DMD) and 2 limb-girdle muscular dystrophies (LGMD); 3 Becker muscular dystrophies (BeMD) and 7 spinal muscular atrophies (SMA). Yearly osteodensitometries assessed body composition and bone mineral density (BMD) associated with bone markers and leptin. Along the 7-year study, 107 osteodensitometries showed that bone status evolved to osteopenia in most patients except BeMD. When analyzing the crude values, BMD improved

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An, Feng-Ping, Da-Chao Lin, Xian-Wei Zhou, and Zhihui Sun. "Enhancing Image Denoising Performance of Bidimensional Empirical Mode Decomposition by Improving the Edge Effect." International Journal of Antennas and Propagation 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/769478.

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Bidimensional empirical mode decomposition (BEMD) algorithm, with high adaptive ability, provides a suitable tool for the noisy image processing, and, however, the edge effect involved in its operation gives rise to a problem—how to obtain reliable decomposition results to effectively remove noises from the image. Accordingly, we propose an approach to deal with the edge effect caused by BEMD in the decomposition of an image signal and then to enhance its denoising performance. This approach includes two steps, in which the first one is an extrapolation operation through the regression model c

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Arrazaki, Mohammed, Abdelouahed Sabri, Mohamed Zohry, and Tarek Zougari. "Adaptive image watermarking using bidimensional empirical mode decomposition." Bulletin of Electrical Engineering and Informatics 12, no. 5 (2023): 2955–63. http://dx.doi.org/10.11591/eei.v12i5.4688.

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Digital watermarking is considered one of the technological means used to guarantee the security and authenticity of data transmitted over communication systems. A new method of image watermarking using the bidimensional empirical mode decomposition (BEMD) will be presented in this article, where the new idea is to use the BEMD of both the cover image and the watermark image. The embedding process consists of adding to each intrinsic modal function (IMF) of the cover image the corresponding IMF of the watermark image. The watermarked image contains three different watermarks and appropriate fr

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Ghazi, Fatima, Aziza Benkuider, Fouad Ayoub, and Khalil Ibrahimi. "Selection of the Discriming Feature Using the BEMD’s BIMF for Classification of Breast Cancer Mammography Image." BioMedInformatics 4, no. 2 (2024): 1202–24. http://dx.doi.org/10.3390/biomedinformatics4020066.

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Mammogram exam images are useful in identifying diseases, such as breast cancer, which is one of the deadliest cancers, affecting adult women around the world. Computational image analysis and machine learning techniques can help experts identify abnormalities in these images. In this work we present a new system to help diagnose and analyze breast mammogram images. To do this, the system a method the Selection of the Most Discriminant Attributes of the images preprocessed by BEMD “SMDA-BEMD”, this entails picking the most pertinent traits from the collection of variables that characterize the

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Huang, Chuanjin, Haijun Song, Wenping Lei, Zhanya Niu, and Yajun Meng. "Instantaneous Amplitude-Frequency Feature Extraction for Rotor Fault Based on BEMD and Hilbert Transform." Shock and Vibration 2019 (March 12, 2019): 1–19. http://dx.doi.org/10.1155/2019/1639139.

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The vibration signals propagating in different directions from rotating machines can contain a variety of characteristic information. A novel feature extraction method based on bivariate empirical mode decomposition (BEMD) for rotor is proposed to comprehensively extract the fault features. In this work, the number of signal projection directions is determined through simulation, and the energy end condition based on the energy threshold is increased using BEMD to enhance the decomposition quality. Mixed vibration signals are generated along two orthogonal directions. Then, the acquired vibrat

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Molla, Md Khademul Islam, Poly Rani Ghosh, and Keikichi Hirose. "Bivariate EMD-Based Data Adaptive Approach to the Analysis of Climate Variability." Discrete Dynamics in Nature and Society 2011 (2011): 1–21. http://dx.doi.org/10.1155/2011/935034.

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This paper presents a data adaptive approach for the analysis of climate variability using bivariate empirical mode decomposition (BEMD). The time series of climate factors: daily evaporation, maximum and minimum temperatures are taken into consideration in variability analysis. All climate data are collected from a specific area of Bihar in India. Fractional Gaussian noise (fGn) is used here as the reference signal. The climate signal and fGn (of same length) are combined to produce bivariate (complex) signal which is decomposed using BEMD into a finite number of sub-band signals named intrin

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Harikiran, Jonnadula Dr J. Harikiran. "Hyperspectral image classification using support vector machines." IAES International Journal of Artificial Intelligence (IJ-AI) 9, no. 4 (2020): 684. http://dx.doi.org/10.11591/ijai.v9.i4.pp684-690.

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In this paper, a novel approach for hyperspectral image classification technique is presented using principal component analysis (PCA), bidimensional empirical mode decomposition (BEMD) and support vector machines (SVM). In this process, using PCA feature extraction technique on Hyperspectral Dataset, the first principal component is extracted. This component is supplied as input to BEMD algorithm, which divides the component into four parts, the first three parts represents intrensic mode functions (IMF) and last part shows the residue. These BIMFs and residue image is further taken as input

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T., Subba Reddy, and Harikiran J. "Hyperspectral image classification using support vector machines." International Journal of Artificial Intelligence (IJ-AI) 9, no. 4 (2020): 684–90. https://doi.org/10.11591/ijai.v9.i4.pp684-690.

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In this paper, a novel approach for hyperspectral image classification technique is presented using principal component analysis (PCA), bidimensional empirical mode decomposition (BEMD) and support vector machines (SVM). In this process, using PCA feature extraction technique on Hyperspectral Dataset, the first principal component is extracted. This component is supplied as input to BEMD algorithm, which divides the component into four parts, the first three parts represents intrensic mode functions (IMF) and last part shows the residue. These BIMFs and residue image is further taken as input

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Agarwal, Shuchi, and Jaipal Singh. "Efficient BEMD Data Hiding Algorithm." International Journal of Computer Applications 160, no. 5 (2017): 24–29. http://dx.doi.org/10.5120/ijca2017913051.

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Miao, Xinying, and Yunlong Liu. "Target Recognition of SAR Images Based on Complex Bidimensional Empirical Mode Decomposition." Scientific Programming 2021 (January 12, 2021): 1–10. http://dx.doi.org/10.1155/2021/6642316.

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A target recognition method for synthetic aperture radar (SAR) image based on complex bidimensional empirical mode decomposition (C-BEMD) is proposed. C-BEMD is used to decompose the original SAR image to obtain multilevel complex bidimensional intrinsic mode functions (BIMF), which reflect the two-dimensional time-frequency characteristics of the target. In the classification stage, the decomposed multilevel BIMFs are represented using the multitask sparse representation. Finally, the target category of the test sample is determined according to the reconstruction errors related to different

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Morvidone, Marcela, Ivana Masci, Diana Rubio, Melisa Kurtz, Deborah Tasat, and Rosa Piotrkowski. "Particle Size and Morphological Evaluation of Airborne Urban Dust Particles by Scanning Electron Microscopy and Bidimensional Empirical Mode Analysis." WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT 20 (October 21, 2024): 504–13. http://dx.doi.org/10.37394/232015.2024.20.49.

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Airborne particles affect the health of the population. As particles decrease in size, they can penetrate deeper into the respiratory system, reaching the terminal bronchioles and alveoli. Particles as small as 0.1 µm in diameter may translocate into the bloodstream, potentially impacting various organs. Additionally, the smaller the particle size, the longer they remain suspended in the air, thereby increasing their deleterious damages. The aim of this work is to study the size distribution of airborne particles emitted from anthropogenic sources of air pollution, with a special emphasis on e

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Wu, Yunan, Jun Chang, Zhongye Ji, Yi Huang, Junya Wang, and Shangnan Zhao. "Optical Asymmetric Cryptosystem Based on Dynamic Foveated Imaging and Bidimensional Empirical Mode Decomposition." Photonics 11, no. 2 (2024): 105. http://dx.doi.org/10.3390/photonics11020105.

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In this paper, we propose an asymmetric cryptosystem based on dynamic foveated imaging and bidimensional empirical mode decomposition (BEMD). Firstly, a novel dynamic foveated imaging algorithm is developed to transform a plaintext image to a globally ambiguous and locally clear image. Then, the image is passed through a phase-truncated Fourier transform system to generate a white noise image. The resulting image is encoded using BEMD to produce an encrypted image. The proposed cryptosystem offers two distinct decryption methods, allowing the receiver to obtain a decrypted image from a specifi

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Sumanto, Sumanto, Agus Buono, Karlisa Priandana, Bib Paruhum Silalahi, and Elisabeth Sri Hendrastuti. "Texture Analysis of Citrus Leaf Images Using BEMD for Huanglongbing Disease Diagnosis." Jurnal Online Informatika 8, no. 1 (2023): 115–21. http://dx.doi.org/10.15575/join.v8i1.1075.

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Plant diseases significantly threaten agricultural productivity, necessitating accurate identification and classification of plant lesions for improved crop quality. Citrus plants, belonging to the Rutaceae family, are highly susceptible to diseases such as citrus canker, black spot, and the devastating Huanglongbing (HLB) disease. HLB, caused by gram-negative proteobacteria strains, severely impacts citrus orchards globally, resulting in economic losses. Early detection and classification of HLB-infected plants are crucial for effective disease management. Traditional approaches rely on exper

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PROF., AJIT KUMAR YADAV. "EARLY BREAST CANCER DETECTION BY USING IMAGE PROCESSING." IJIERT - International Journal of Innovations in Engineering Research and Technology ICITER- 16 PUNE (June 20, 2016): 147–51. https://doi.org/10.5281/zenodo.1463597.

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<strong><strong> </strong>In developed nations,the breast cancer rate is high. The mass segmentation methods in mammogram plays important role in Computer aided diagnosis (CAD) system . In this paper is supposed to do the breast cancer detection by using the Bidimensional Empirical Mode Decomposition (BEMD) method. Breast cancers are traditionally known to be one of the major causes of death among women. In this work,a novel segmentation approach by contour extraction was developed,based on two main phases:detection of (ROI) and region segmentation. Our approach consists of first finding

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Zeng, Yanan, Junsheng Lu, Xinyu Chang, et al. "A Method to Improve the Imaging Quality in Dual-Wavelength Digital Holographic Microscopy." Scanning 2018 (October 14, 2018): 1–6. http://dx.doi.org/10.1155/2018/4582590.

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A digital hologram-optimizing method was proposed to improve the imaging quality of dual-wavelength digital holographic microscopy (DDHM) by reducing the phase noise level. In our previous work, phase noise reduction was achieved by dual-wavelength digital image-plane holographic microscopy (DDIPHM). In the optimization method in this paper, the phase noise was further reduced by enhancing the real-image term and suppressing effects of the zero-order term in the frequency spectrum of a digital hologram. Practically, the carrier frequency of the real-image term has the correspondence with inter

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Priya, Ebenezer, Subramanian Srinivasan, and Swaminathan Ramakrishnan. "Retrospective Non-Uniform Illumination Correction Techniques in Images of Tuberculosis." Microscopy and Microanalysis 20, no. 5 (2014): 1382–91. http://dx.doi.org/10.1017/s1431927614012896.

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AbstractImage pre-processing is highly significant in automated analysis of microscopy images. In this work, non-uniform illumination correction has been attempted using the surface fitting method (SFM), multiple regression method (MRM), and bidirectional empirical mode decomposition (BEMD) in digital microscopy images of tuberculosis (TB). The sputum smear positive and negative images recorded under a standard image acquisition protocol were subjected to illumination correction techniques and evaluated by error and statistical measures. Results show that SFM performs more efficiently than MRM

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Chen, Xiaoying, Aiguo Song, Jianqing Li, Yimin Zhu, Xuejin Sun, and Hong Zeng. "Texture Feature Extraction Method for Ground Nephogram Based on Hilbert Spectrum of Bidimensional Empirical Mode Decomposition." Journal of Atmospheric and Oceanic Technology 31, no. 9 (2014): 1982–94. http://dx.doi.org/10.1175/jtech-d-13-00238.1.

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Abstract It is important to recognize the type of cloud for automatic observation by ground nephoscope. Although cloud shapes are protean, cloud textures are relatively stable and contain rich information. In this paper, a novel method is presented to extract the nephogram feature from the Hilbert spectrum of cloud images using bidimensional empirical mode decomposition (BEMD). Cloud images are first decomposed into several intrinsic mode functions (IMFs) of textural features through BEMD. The IMFs are converted from two- to one-dimensional format, and then the Hilbert–Huang transform is perfo

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JIAN, ZHENZHEN, BINBIN ZHAO, and YONGQING CHEN. "APPLICATION OF BI-DIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD) IN EXTRACTION OF PLATINUM AND PALLADIUM ANOMALIES FEATURES." Advances in Adaptive Data Analysis 04, no. 01n02 (2012): 1250010. http://dx.doi.org/10.1142/s1793536912500100.

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The bi-dimensional empirical mode decomposition (BEMD) is applied to analyze nonstationary Platinum (Pt) and Palladium (Pd) concentration data in the eastern Yunnan Province, the southwestern China. Two kinds of Pt and Pd anomalies are obtained. One is the regional Pt and Pd anomalies shown in the BIMF3 component; the other is the local Pt and Pd anomalies shown in the BIMF2 component. It has been illustrated by further study that the regional Pt and Pd anomalies associated with the Emeishan basalts formed in Permian are distributed along deep-seated faults such as the Xiaojiang fault and the

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Jung, Steffen, and Carl Heckmann. "Prozessunterstützung über den Standard hinaus." BWK ENERGIE. 72, no. 10-11 (2020): 35–38. http://dx.doi.org/10.37544/1618-193x-2020-10-11-35.

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Die Transparenzinitiative des Bundesverbandes der Energiemarktdienstleister (BEMD) „IT-Lösungen: Meter to Cash“ hat sich in ihrer Neuauflage 2020 einmal mehr mit aktuellen Entwicklungen im Markt für Abrechnungslösungen beschäftigt. Neben einer aktualisierten und vervollständigten Marktsicht auf den derzeitigen Anbietermarkt liefert die Initiative Informationen, wie die Anbieter auf aktuelle Trends reagieren.

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Liu, Qing, Huina Jin, Xiang Bai, and Jinliang Zhang. "Prediction and Analysis of the Price of Carbon Emission Rights in Shanghai: Under the Background of COVID-19 and the Russia–Ukraine Conflict." Mathematics 11, no. 14 (2023): 3126. http://dx.doi.org/10.3390/math11143126.

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In the spring of 2022, a new round of epidemic broke out in Shanghai, causing a shock to the Shanghai carbon trading market. Against this background, this paper studied the impact of the new epidemic on the price of Shanghai carbon emission rights and tried to explore the prediction model under the unexpected event. First, because a model based on point value data cannot capture the information hidden in inter-day price fluctuation, based on the interval price of Shanghai carbon emission rights (SHEA) and its influencing factors, an autoregressive conditional interval model with jumping and ex

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Li, Yang, Jing Zhang, Chengbin Fu, and Dalong Wang. "BEMD-based two-dimensional SAR autofocus algorithm." Geocarto International 30, no. 10 (2015): 1163–71. http://dx.doi.org/10.1080/10106049.2015.1034193.

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Ekawati, Gestin Mey. "PEMISAHAN ANOMALI GAYABERAT DAERAH LAMPUNG MENGGUNAKAN BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION (BEMD)." Jurnal Geofisika Eksplorasi 7, no. 3 (2021): 191–201. http://dx.doi.org/10.23960/jge.v7i3.153.

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Metode gayaberat adalah salah satu metode geofisika yang digunakan dalam eksplorasi mineral dan migas. Metode ini memanfaatkan percepatan gravitasi untuk memodelkan struktur densitas batuan di dalam bumi, mendeliniasi struktur maupun satuan geologi. Pada tahap pengolahan data gayaberat diperlukan beberapa koreksi untuk menghasilkan anomali Bouguer lengkap (CBA). Nilai CBA merupakan hasil resultan dari seluruh kontribusi massa di bawah permukaan dan di sekitar titik datum. Pemisahan anomali CBA menjadi regional dan residual menjadi tahap penting dalam interpretasi dan pemodelan gayaberat. Beber

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Fan, Peili. "Combined with Local Neighborhood Characteristics and Remote Sensing Image Fusion Method of C-BEMD." International Journal of Circuits, Systems and Signal Processing 15 (August 12, 2021): 936–44. http://dx.doi.org/10.46300/9106.2021.15.100.

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For the sake of ameliorate the high resolution recognition capacity building remote sensing images, a remote sensing image fusion method based on local neighborhood characteristics and C-BEMD is advanced. The building remote sensing image acquisition model and the building remote sensing image picture element edge feature detection model are designed. The wavelet multi-scale denoising method is used to suppress the fuzzy spread of picture element feature points between image residual units, extract the geometric feature points of image sequence, and process the building remote sensing image bl

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Lu, Yi, Chenyang Huang, Jia Wang, and Peng Shang. "An Improved Quantitative Analysis Method for Plant Cortical Microtubules." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/637183.

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The arrangement of plant cortical microtubules can reflect the physiological state of cells. However, little attention has been paid to the image quantitative analysis of plant cortical microtubules so far. In this paper, Bidimensional Empirical Mode Decomposition (BEMD) algorithm was applied in the image preprocessing of the original microtubule image. And then Intrinsic Mode Function 1 (IMF1) image obtained by decomposition was selected to do the texture analysis based on Grey-Level Cooccurrence Matrix (GLCM) algorithm. Meanwhile, in order to further verify its reliability, the proposed text

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Guo, Xiao-Ting, Xu-Jie Duan, and Hui-Hua Kong. "Multi-Source Image Fusion Based on BEMD and Region Sharpness Guidance Region Overlapping Algorithm." Applied Sciences 14, no. 17 (2024): 7764. http://dx.doi.org/10.3390/app14177764.

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Multi-focal image and multi-modal image fusion technology can fully take advantage of different sensors or different times, retaining the image feature information and improving the image quality. A multi-source image fusion algorithm based on bidimensional empirical mode decomposition (BEMD) and a region sharpness-guided region overlapping algorithm are studied in this article. Firstly, source images are decomposed into multi-layer bidimensional intrinsic mode functions (BIMFs) and residuals from high-frequency layer to low-frequency layer by BEMD. Gaussian bidimensional intrinsic mode functi

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Chen, Yong Qing, and Bin Bin Zhao. "Extraction of Gravity Anomalies Associated with Gold Mineralization: A Comparison of Singular Value Decomposition and Bi-Dimensional Empirical Mode Decomposition." Advanced Materials Research 455-456 (January 2012): 1567–77. http://dx.doi.org/10.4028/www.scientific.net/amr.455-456.1567.

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Two methods of both the singular value decomposition (SVD) and the Bi-dimensional empirical mode decomposition (BEMD) were applied in extraction of gravity anomalies associated with gold mineralization in Tongshi gold field, respectively in this paper. Conclusions drawn by the comparison study are as follows: (a) The ore-controlling factor in the Tongshi gold field illustrated in the images obtained from the original gravity data by the two methods is the same that the Tongshi intrusions with a negative circular gravity anomaly and the ring contact metasomatic mineralization zone around the To

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Xu, Guan Lei, Xiao Tong Wang, Xiao Gang Xu, Jiang Hu, and Bin Yu Li. "The Bi-Dimensional Bedrosian’s Principle for Image Decomposition." Applied Mechanics and Materials 602-605 (August 2014): 3854–58. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.3854.

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Based on the derived bi-dimensional Bedrosian’s principles and the original multicomponents, we provide the combined bi-dimensional Bedrosian’s principle so that the monocomponents in multicomponents can be separated in the case that the existent methods fail. The proposed method can solve the problems caused by the cross-angle and amplitude ratio and frequency ratio and so on between these components that BEMD fails to solve. Experiments support the proposed methods.

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Riahi, Ali, Omar Elharrouss, and Somaya Al-Maadeed. "BEMD-3DCNN-based method for COVID-19 detection." Computers in Biology and Medicine 142 (March 2022): 105188. http://dx.doi.org/10.1016/j.compbiomed.2021.105188.

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Wan, Jian, Yuan Peng Diao, Dong Mei Yan, Qiang Guo, and Zhen Shen Qu. "Application of Bidimensional Empirical Mode Decomposition to Medical Liquid Opacity Detection." Applied Mechanics and Materials 128-129 (October 2011): 530–33. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.530.

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A Robert operator edge detection algorithm based on Bidimensional Empirical Mode Decomposition (BEMD) to detect medical liquid opacity is proposed. This method can effectively resolve the problem that traditional Robert operator edge detection can be easily effected by noise, and it also has certain effects on restraining external environment influence. The simulation results show that, compare with traditional medical liquid opacity detection methods, the proposed method could achieve higher detection accuracy, and has a certain theory and application value.

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Tang, Hong-rong, Min-fen Shen, and Bin Li. "The Improvement of the BEMD Using Compactly Supported RBF." Journal of Electronics & Information Technology 30, no. 1 (2011): 149–53. http://dx.doi.org/10.3724/sp.j.1146.2006.00849.

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Xing, Siming, Zhilin Cheng, ChunYu Ji, Jiaying Chen, and Luyu Qi. "Remote Sensing Image Zero-Watermark Algorithm Based on Bemd." Journal of Physics: Conference Series 1865, no. 4 (2021): 042035. http://dx.doi.org/10.1088/1742-6596/1865/4/042035.

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He, Zhi, Qiang Wang, Yi Shen, Jing Jin, and Yan Wang. "Multivariate Gray Model-Based BEMD for Hyperspectral Image Classification." IEEE Transactions on Instrumentation and Measurement 62, no. 5 (2013): 889–904. http://dx.doi.org/10.1109/tim.2013.2246917.

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Guanlei, Xu, Wang Xiaotong, and Xu Xiaogang. "On analysis of bi-dimensional component decomposition via BEMD." Pattern Recognition 45, no. 4 (2012): 1617–26. http://dx.doi.org/10.1016/j.patcog.2011.11.004.

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Ding, Shifei, Peng Du, Xingyu Zhao, Qiangbo Zhu, and Yu Xue. "BEMD image fusion based on PCNN and compressed sensing." Soft Computing 23, no. 20 (2018): 10045–54. http://dx.doi.org/10.1007/s00500-018-3560-8.

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An, Feng-Ping, and Xian-Wei Zhou. "BEMD–SIFT feature extraction algorithm for image processing application." Multimedia Tools and Applications 76, no. 11 (2016): 13153–72. http://dx.doi.org/10.1007/s11042-016-3746-y.

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Wu, Deyang, Miaomiao Wang, Jing Zhao, et al. "Color Zero-Watermarking Algorithm for Medical Images Based on BEMD-Schur Decomposition and Color Visual Cryptography." Security and Communication Networks 2021 (December 20, 2021): 1–12. http://dx.doi.org/10.1155/2021/7081194.

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With the widespread use of medical images in telemedicine, personal information may be leaked. The traditional zero-watermarking technology has poor robustness under large-scale attacks. At the same time, most of the zero-watermarking information generated is a binary sequence with a single information structure. In order to effectively solve the poor robustness problem of traditional zero-watermarking under large-scale attacks, a color zero-watermarking algorithm for medical images based on bidimensional empirical mode decomposition (BEMD)-Schur decomposition and color visual cryptography is

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Kavitha, H., and M. V. Sudhamani. "Content-Based Image Retrieval Using Edge and Gradient Orientation Features of an Object in an Image From Database." Journal of Intelligent Systems 25, no. 3 (2016): 441–54. http://dx.doi.org/10.1515/jisys-2014-0088.

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AbstractIn this work, we present a combination of edge feature and distribution of the gradient orientation of an object technique for content-based image retrieval (CBIR). First, the bidimensional empirical mode decomposition (BEMD) technique is employed to get the edge features of an image. Later, the information about the gradient orientation is obtained by the histogram of oriented gradient (HOG) descriptor. These two features are extracted from the images and stored in the database for further usage. When the user submits the query image, the features are extracted in same way and compare

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Cui, Min, Yicheng Wu, Chenguang Wang, Xiaochen Liu, and Chong Shen. "Salt and Pepper Noise Removal for Image Using Adaptive Pulse-Coupled Neural Network Optimized by Grey Wolf Optimization and Bidimensional Empirical Mode Decomposition." Applied Sciences 8, no. 10 (2018): 1977. http://dx.doi.org/10.3390/app8101977.

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Aimed at the problem of poor noise reduction effect and parameter uncertainty of pulse-coupled neural network (PCNN), a hybrid image denoising method, using an adaptive PCNN that has been optimized by grey wolf optimization (GWO) and bidimensional empirical mode decomposition (BEMD), is presented. The BEMD is used to decompose the original image into multilayer image components. After a GWO is run to complete PCNN parameter optimization, an adaptive PCNN filter method is used to remediate the polluted noise points that correspond to the different image components, from which a reconstruction o

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Liu, Quanbo, Xiaoli Li, and Kang Wang. "Dynamic Modeling of Flue Gas Desulfurization Process via Bivariate EMD-Based Temporal Convolutional Network." Applied Sciences 13, no. 13 (2023): 7370. http://dx.doi.org/10.3390/app13137370.

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Sulfur dioxide (SO2) can cause detrimental impacts on the ecosystem. It is well known that coal-fired power plants play a dominant role in SO2 emissions, and consequently industrial flue gas desulfurization (IFGD) systems are widely used in coal-fired power plants. To remove SO2 effectively such that ultra-low emission standard can be satisfied, IFGD modeling has become urgently necessary. IFGD is a chemical process with long-term dependencies between time steps, and it typically exhibits strong non-linear behavior. Furthermore, the process is rendered non-stationary due to frequent changes in

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Hao, Wei, Jin Yu, Yanzhu Hu, and Song Wang. "An Improved BEMD Method for Denoising the Phase-OTDR Signal." Journal of Physics: Conference Series 1650 (October 2020): 022061. http://dx.doi.org/10.1088/1742-6596/1650/2/022061.

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Ren, Wenyi, Dan Wu, Guoan Yang, et al. "Defringing in interference imaging spectrometer based on BEMD and PCA." Optik 157 (March 2018): 1027–34. http://dx.doi.org/10.1016/j.ijleo.2017.11.156.

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Chuwdhury, Gulam Sarwar, Md Khaliluzzaman, and Md Rashed-Al Mahfuz. "Analyzing Wavelet and Bidimensional Empirical Mode Decomposition of MRI Segmentation using Fuzzy C-Means Clustering." Rajshahi University Journal of Science and Engineering 44 (November 19, 2016): 101–12. http://dx.doi.org/10.3329/rujse.v44i0.30395.

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Image segmentation is a vital step in medical image processing. Magnetic resonance imaging (MRI) is used for brain tissues extraction in white and gray matter. These tissues extraction help in image segmentation applications such as radiotherapy planning, clinical diagnosis, treatment planning. This paper presents utilization of fuzzy C-means (FCM) clustering by using wavelet and bidimensional empirical mode decomposition (BEMD) to improve the quality of noisy MR images. The signal to noise ratio (SNR) value is calculated from FCM clustering data to examine the best segmentation technique. The

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