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Ding, Ing Jr, Chih Ta Yen, and Che Wei Chang. "Classification of Chinese Popular Songs Using a Fusion Scheme of GMM Model Estimate and Formant Feature Analysis." Applied Mechanics and Materials 479-480 (December 2013): 1006–9. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.1006.
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In this paper, a fusion scheme that combines Gaussian mixture model (GMM) calculations and formant feature analysis, called GMM-Formant, is proposed for classification of Chinese popular songs. Generally, automatic classification of popular music could be performed by two main categories of techniques, model-based and feature-based approaches. In model-based classification techniques, GMM is widely used for its simplicity. In feature-based music recognition, the formant parameter is an important acoustic feature for evaluation. The proposed GMM-Formant method takes use of linear interpolation for combining GMM likelihood estimates and formant evaluation results appropriately. GMM-Formant will effectively adjust the likelihood score, which is derived from GMM calculations, by referring to certain degree of formant feature evaluation outcomes. By considering both model-based and feature-based techniques for song classification, GMM-Formant provides a more reliable recognition classification result and therefore will maintain a satisfactory performance in recognition accuracy. Experimental results obtained from a musical data set of numerous Chinese popular songs show the superiority of the proposed GMM-Formant. Keywords: Song classification; Gaussian mixture model; Formant feature; GMM-Formant.
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Alharbi, Bayan, and Hanan S. Alshanbari. "Face-voice based multimodal biometric authentication system via FaceNet and GMM." PeerJ Computer Science 9 (July 11, 2023): e1468. http://dx.doi.org/10.7717/peerj-cs.1468.
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Information security has become an inseparable aspect of the field of information technology as a result of advancements in the industry. Authentication is crucial when it comes to dealing with security. A user must be identified using biometrics based on certain physiological and behavioral markers. To validate or establish the identification of an individual requesting their services, a variety of systems require trustworthy personal recognition schemes. The goal of such systems is to ensure that the offered services are only accessible by authorized users and not by others. This case study provides enhanced accuracy for multimodal biometric authentication based on voice and face hence, reducing the equal error rate. The proposed scheme utilizes the Gaussian mixture model for voice recognition, FaceNet model for face recognition and score level fusion to determine the identity of the user. The results reveal that the proposed scheme has the lowest equal error rate in comparison to the previous work.
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Gupta, Monika, Smriti Srivastava, Gopal Chaudhary, Manju Khari, and Javier Parra Fuente. "Voltage Regulation using Probabilistic and Fuzzy Controlled Dynamic Voltage Restorer for Oil and Gas Industry." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, Supp02 (December 2020): 49–64. http://dx.doi.org/10.1142/s0218488520400139.
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In a power distribution system, faults occurring can cause voltage sag that can affect critical loads connected in the power network which can cause serious effects in the oil and gas industry. The objective of this paper is to design and implement an efficient and economical dynamic voltage restorer (DVR) to compensate for voltage sag conditions in the oil and gas industry. Due to the complexity and sensitivity of loads, a short voltage sag duration can still cause severe power quality problems to the entire system. Dynamic Voltage Restorer (DVR) is a static series compensating type custom power device. The overall efficiency of the DVR largely relies on the effectiveness of the control strategy governing the switching of the inverters. It can be said that the heart of the DVR control strategy is the derivation of reference currents. This paper deals with the extraction of reference current values using a controller based on a combination of probabilistic and fuzzy set theory. The basis of the proposed controller is that Gaussian Mixture Model (GMM) which is a probabilistic approach can be translated to an additive fuzzy interface system i.e. Generalized Fuzzy Model (GFM). The proposed controller (GMM-GFM) initially optimizes the membership functions using GMM and the final output is calculated using GFM in a single iteration i.e. with no recursions. In the control scheme two control loops are used: a feed-forward loop that uses the Proportional and Integral (PI) controller and the feedback loop uses GMM-GFM based controller. The controller is implemented and respective simulations are performed in the MATLAB SIMULINK environment for three-phase, three-wire distribution system with various issues. A comparative analysis is then done amongst all the three controllers which are based on the T-S, ML, and GMM-GFM modes respectively. The simulation results of this comparison rank the DVR with the GMM-GFM controller first, followed by the fuzzy logic Mamdani model and then with the fuzzy logic T-S model.
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Mamyrbayev, O., A. Akhmediyarova, A. Kydyrbekova, N. O. Mekebayev, and B. Zhumazhanov. "BIOMETRIC HUMAN AUTHENTICATION SYSTEM THROUGH SPEECH USING DEEP NEURAL NETWORKS (DNN)." BULLETIN 5, no. 387 (October 15, 2020): 6–15. http://dx.doi.org/10.32014/2020.2518-1467.137.
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Biometrics offers more security and convenience than traditional methods of identification. Recently, DNN has become a means of a more reliable and efficient authentication scheme. In this work, we compare two modern teaching methods: these two methods are methods based on the Gaussian mixture model (GMM) (denoted by the GMM i-vector) and methods based on deep neural networks (DNN) (denoted as the i-vector DNN). The results show that the DNN system with an i-vector is superior to the GMM system with an i-vector for various durations (from full length to 5s). DNNs have proven to be the most effective features for text-independent speaker verification in recent studies. In this paper, a new scheme is proposed that allows using DNN when checking text using hints in a simple and effective way. Experiments show that the proposed scheme reduces EER by 24.32% compared with the modern method and is evaluated for its reliability using noisy data, as well as data collected in real conditions. In addition, it is shown that the use of DNN instead of GMM for universal background modeling leads to a decrease in EER by 15.7%.
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Chaddad, Ahmad. "Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models." International Journal of Biomedical Imaging 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/868031.
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This paper presents a novel method for Glioblastoma (GBM) feature extraction based on Gaussian mixture model (GMM) features using MRI. We addressed the task of the new features to identify GBM using T1 and T2 weighted images (T1-WI, T2-WI) and Fluid-Attenuated Inversion Recovery (FLAIR) MR images. A pathologic area was detected using multithresholding segmentation with morphological operations of MR images. Multiclassifier techniques were considered to evaluate the performance of the feature based scheme in terms of its capability to discriminate GBM and normal tissue. GMM features demonstrated the best performance by the comparative study using principal component analysis (PCA) and wavelet based features. For the T1-WI, the accuracy performance was 97.05% (AUC = 92.73%) with 0.00% missed detection and 2.95% false alarm. In the T2-WI, the same accuracy (97.05%, AUC = 91.70%) value was achieved with 2.95% missed detection and 0.00% false alarm. In FLAIR mode the accuracy decreased to 94.11% (AUC = 95.85%) with 0.00% missed detection and 5.89% false alarm. These experimental results are promising to enhance the characteristics of heterogeneity and hence early treatment of GBM.
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Chen, Rong, Yuzhu Bai, Yong Zhao, Zhijun Chen, and Tao Sheng. "Safe Proximity Operation to Rotating Non-Cooperative Spacecraft with Complex Shape Using Gaussian Mixture Model-Based Fixed-Time Control." Applied Sciences 10, no. 17 (August 29, 2020): 5986. http://dx.doi.org/10.3390/app10175986.
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This paper studies the safety control problem for rotating spacecraft proximity maneuver in presence of complex shaped obstacles. First, considering the attitude change of the target spacecraft, a dynamic model of close-range relative motion in a body-fixed coordinate system is derived using a novel approach. Then, the Gaussian mixture model (GMM) is utilized to reconstruct the complex shape of the spacecraft, and a novel GMM-based artificial potential function (APF) is proposed to represent the collision avoidance requirement. By combining GMM-based APF with fixed-time stability methodology, a fixed-time control (FTC) is designed for close-range proximity operation to a rotating spacecraft having a complex shape. The presented GMM-FTC scheme can guarantee the convergence of relative state errors, and ensure that no collision occurs. Finally, simulation results are provided to illustrate the feasibility of the proposed control approach.
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Zergat, Kawthar Yasmine, and Abderrahmane Amrouche. "New scheme based on GMM-PCA-SVM modelling for automatic speaker recognition." International Journal of Speech Technology 17, no. 4 (May 14, 2014): 373–81. http://dx.doi.org/10.1007/s10772-014-9235-7.
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Chen, Guang Hua, and Gui Zhi Sheng. "Detection of Moving Objects Based on Mixture Gaussian Model." Advanced Materials Research 1039 (October 2014): 274–79. http://dx.doi.org/10.4028/www.scientific.net/amr.1039.274.
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The paper proposes an improved adaptive Gaussian mixture model (GMM) approach with online EM algorithms for updating, which solves the video segmentation problems carried by busy environment and illumination change. Different learning rates are set for foreground district and background district respectively, which improves the convergence speed of background model. A shadow removal scheme is also introduced for extracting complete moving objects. It is based on brightness distortion and chromaticity distortion in RGB color space. Morphological filtering and connected components analysis algorithm are also introduced to process the result of background subtraction. The experiment results show that the improved GMM has good accuracy and high adaptability in video segmentation. It can extract a complete and clear moving object when it is incorporated with shadow removal.
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KIM, Y., S. JEONG, and D. KIM. "A GMM-Based Target Classification Scheme for a Node in Wireless Sensor Networks." IEICE Transactions on Communications E91-B, no. 11 (November 1, 2008): 3544–51. http://dx.doi.org/10.1093/ietcom/e91-b.11.3544.
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Chen, Joy Iong-Zong, and P. Hengjinda. "Based on machine learning scheme to develop a smart robot embedded with GMM-UBM." Journal of Intelligent & Fuzzy Systems 40, no. 4 (April 12, 2021): 7925–37. http://dx.doi.org/10.3233/jifs-189615.
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Smart Robot embedded with GMM-UBM (Gaussian mixture model- universal background model) based on the machine learning scheme is presented in the article. Authors have designed a smart robot for the farmer and which is designed controlled by the concept of machine learning. On the other hand, the techniques of machine learning are applied to develop a smart robot for helping farmers recognize the environment conditions, e.g. weather, and disease protection in rice or plant. The smart robot is implemented to detect and to recognize the environment conditions around a fixed area. The sensing way through vision devices, such as camera, look like a human’s eye to distinguish various types of target. The QR code is deployed to simulate working conditions allows the robot to separate conditions and act according to conditions precisely. Besides, the smart robot is embedded with GMM-UBM algorithm for promoting the accuracy of recognition from the deployment of machine learning. The smart robot, mainly combines with AI (Artificial intelligence) techniques, consists of the following equipments: 1) a control movement subsystem, 2) a sensor control subsystem, and 3) an analysis subsystem. The researcher has determined the condition of the message options via QR code. In addition, the contents of the QR code tag will be processed a text message and saved to a memory device, once the reading is finished. The data analysis subsystem then reads the text and recommends the robot to move according to the specified conditions. The results from QR code data allow the smart robot to accurately collect many kinds of prefer data (e.g., climate data) in the farm at the specified location.
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Xie, Qunyi, and Hongqing Zhu. "Image Retrieval Based on Multiview Constrained Nonnegative Matrix Factorization and Gaussian Mixture Model Spectral Clustering Method." Mathematical Problems in Engineering 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/3271924.
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Content-based image retrieval has recently become an important research topic and has been widely used for managing images from repertories. In this article, we address an efficient technique, called MNGS, which integrates multiview constrained nonnegative matrix factorization (NMF) and Gaussian mixture model- (GMM-) based spectral clustering for image retrieval. In the proposed methodology, the multiview NMF scheme provides competitive sparse representations of underlying images through decomposition of a similarity-preserving matrix that is formed by fusing multiple features from different visual aspects. In particular, the proposed method merges manifold constraints into the standard NMF objective function to impose an orthogonality constraint on the basis matrix and satisfy the structure preservation requirement of the coefficient matrix. To manipulate the clustering method on sparse representations, this paper has developed a GMM-based spectral clustering method in which the Gaussian components are regrouped in spectral space, which significantly improves the retrieval effectiveness. In this way, image retrieval of the whole database translates to a nearest-neighbour search in the cluster containing the query image. Simultaneously, this study investigates the proof of convergence of the objective function and the analysis of the computational complexity. Experimental results on three standard image datasets reveal the advantages that can be achieved with the proposed retrieval scheme.
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Ding, Ing-Jr, and Zong-Gui Wu. "Combinations of eigenspace and GMM with Kinect sensor-extracted action gesture features for person identity recognition." Engineering Computations 33, no. 8 (November 7, 2016): 2489–503. http://dx.doi.org/10.1108/ec-02-2016-0076.
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Purpose The Kinect sensor released by Microsoft is well-known for its effectiveness on human gesture recognition. Gesture recognition by Kinect has been proved to be an efficient command operation and provides an additional human-computer interface in addition to the traditional speech recognition. For Kinect gesture recognition in the application of gesture command operations, recognition of the active user making the gesture command to Kinect will be an extremely crucial problem. The purpose of this paper is to propose a recognition method for recognizing the person identity of an active user using combined eigenspace and Gaussian mixture model (GMM) with Kinect-extracted action gesture features. Design/methodology/approach Several Kinect-derived gesture features will be explored for determining the effective pattern features in the active user recognition task. In this work, a separate Kinect-derived feature design for eigenspace recognition and GMM classification is presented for achieving the optimal performance of each individual classifier. In addition to Kinect-extracted feature designs for active user recognition, this study will further develop a combined recognition method, called combined eigenspace-GMM, which properly hybridizes the decision information of both the eigenspace and the GMM for making a more reliable user recognition result. Findings Active user recognition using an effective combination of eigenspace and GMM with well-developed active gesture features in Kinect-based active user recognition will have an outstanding performance on the recognition accuracy. The presented Kinect-based user recognition system using the presented approach will further have the competitive benefits of recognition on both gesture commands and providing users of gesture commands. Originality/value A hybridized scheme of eigenspace and GMM performs better than eigenspace-alone or GMM-alone on recognition accuracy of active user recognition; a separate Kinect-derived feature design for eigenspace recognition and GMM classification is presented for achieving the optimal performance of the individual classifier; combined eigenspace-GMM active user recognition belonging to model-based active user recognition design has a fine extension on increasing the recognition rate by adjusting recognition models.
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Kim, Seongjai. "3‐D eikonal solvers: First‐arrival traveltimes." GEOPHYSICS 67, no. 4 (July 2002): 1225–31. http://dx.doi.org/10.1190/1.1500384.
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The article is concerned with the development and comparison of three different algorithms for the computation of first‐arrival traveltimes: the fast marching method (FMM), the group marching method (GMM), and a second‐order finite‐difference eikonal solver. GMM is introduced as a variant of FMM. It proceeds the solution by advancing a selected group of grid points at a time, rather than sorting the solution in the narrow band to march forward a single grid point. The second‐order eikonal solver studied in the article is an expanding‐box, essentially nonoscillatory scheme for which the stability is enforced by the introduction of a down ‘n’ out marching and a post‐sweeping iteration. Techniques such as the maximum angle condition, the average normal velocity, and cache‐based implementation are introduced for the algorithms to improve the numerical accuracy and efficiency. The algorithms are implemented for solving the eikonal equation in 3‐D isotropic media, and their performances are compared. GMM is numerically verified to be faster than FMM. However, the second‐order algorithm turns out to be superior to these first‐order level‐set methods in both accuracy and efficiency; the incorporation of average normal velocity improves accuracy dramatically for the second‐order scheme.
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Xu, Hangyong, Meihua Bi, Feifan Hu, Zhirui Hu, Xuyang Teng, and Weisheng Hu. "A GMM-based non-uniform quantization scheme for improving low-resolution IMDD-UFMC system performance." Optical Fiber Technology 71 (July 2022): 102943. http://dx.doi.org/10.1016/j.yofte.2022.102943.
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Liu, Di, Min Zhu, Dong Li, Xiaofang Fang, and Yanbo Wu. "Energy-Efficient Time Synchronization based on Nonlinear Clock Skew Tracking for Underwater Acoustic Networks." Sensors 21, no. 15 (July 23, 2021): 5018. http://dx.doi.org/10.3390/s21155018.
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Time synchronization plays an important role in the scheduling and position technologies of sensor nodes in underwater acoustic networks (UANs). The time synchronization (TS) algorithms face challenges such as high requirements of energy efficiency, the estimation accuracy of the time-varying clock skew and the suppression of the impulsive noise. To achieve accurate time synchronization for UANs, an energy-efficient TS method based on nonlinear clock skew tracking (NCST) is proposed. First, based on the sea trial temperature data and the crystal oscillators’ temperature–frequency characteristics, a nonlinear model is established to characterize the dynamic of clock skews. Second, a single-way communication scheme based on a receiver-only (RO) paradigm is used in the NCST-TS to save limited energy. Meanwhile, impulsive noises are considered during the communication process and the Gaussian mixture model (GMM) is employed to fit receiving timestamp errors caused by non-Gaussian noise. To combat the nonlinear and non-Gaussian problem, the particle filter (PF)-based algorithm is used to track the time-varying clock state and an accurate posterior probability density function under the GMM error model is also given in PF. The simulation results show that under the GMM error model, the accumulative Root Mean Square Errors (RMSE) of NCST-TS can be reduced from 10−4 s to 10−5 s compared with existing protocols. It also outperforms the other TS algorithms in the aspect of energy efficiency.
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Wang, Xu. "The Design of University Coordination Utility Management and Online Repair Platform Based on Multivariate Statistical Analysis with Random Matrix." Mathematical Problems in Engineering 2022 (August 11, 2022): 1–11. http://dx.doi.org/10.1155/2022/5477390.
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In this paper, the random matrix of multivariate statistical analysis is used to conduct in-depth research and analysis of the university coordination utility management and online repair platform. Considering that the chunking of variables based on mechanistic knowledge is not easy to achieve, firstly, the maximum correlation and minimum redundancy algorithm is used to portray the correlation more accurately between process variables and remove the redundancy between variables to provide the optimal variable input for the base model. The multivariate mean control chart was used to calculate the offset between the data of each test group of the contact network and the overall mean and standard values of the contact network parameters under different correlations among the contact network parameters. Based on the daily work research and process document sampling of the university coordination utilities management department, the requirement analysis and design of the target system were completed, and a university coordination utility management system based on BS architecture was developed. Student information is lost, data statistics are wrong, etc., so that the business work of other departments of the school cannot be carried out smoothly. The whole platform can be divided into several submodules according to the functions: super administrator module, administrator module, staff module, and user module, and the detailed design scheme of each module is described in detail. At the same time, the logistic regression model is trained using the collected data sets, and the training scheme of the model is designed. The mathematical model of logistic regression and the related algorithm are used to decide whether to purchase maintenance equipment at this stage and the quantity of purchase. Finally, a new monitoring index is proposed to monitor the process status. MNPE-GMM not only maintains most of the local structural information of the window dataset in the feature subspace but also reduces the computational complexity of GMM in the fault detection process. The MNPE-GMM method can effectively improve the fault detection rate of multimodal intermittent processes by introducing new statistics.
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Magaraja, Anousouya Devi, Ezhilarasie Rajapackiyam, Vaitheki Kanagaraj, Suresh Joseph Kanagaraj, Ketan Kotecha, Subramaniyaswamy Vairavasundaram, Mayuri Mehta, and Vasile Palade. "A Hybrid Linear Iterative Clustering and Bayes Classification-Based GrabCut Segmentation Scheme for Dynamic Detection of Cervical Cancer." Applied Sciences 12, no. 20 (October 18, 2022): 10522. http://dx.doi.org/10.3390/app122010522.
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Cervical cancer earlier detection remains indispensable for enhancing the survival rate probability among women patients worldwide. The early detection of cervical cancer is done relatively by using the Pap Smear cell Test. This method of detection is challenged by the degradation phenomenon within the image segmentation task that arises when the superpixel count is minimized. This paper introduces a Hybrid Linear Iterative Clustering and Bayes classification-based GrabCut Segmentation Technique (HLC-BC-GCST) for the dynamic detection of Cervical cancer. In this proposed HLC-BC-GCST approach, the Linear Iterative Clustering process is employed to cluster the potential features of the preprocessed image, which is then combined with GrabCut to prevent the issues that arise when the number of superpixels is minimized. In addition, the proposed HLC-BC-GCST scheme benefits of the advantages of the Gaussian mixture model (GMM) on the extracted features from the iterative clustering method, based on which the mapping is performed to describe the energy function. Then, Bayes classification is used for reconstructing the graph cut model from the extracted energy function derived from the GMM model-based Linear Iterative Clustering features for better computation and implementation. Finally, the boundary optimization method is utilized to considerably minimize the roughness of cervical cells, which contains the cytoplasm and nuclei regions, using the GrabCut algorithm to facilitate improved segmentation accuracy. The results of the proposed HLC-BC-GCST scheme are 6% better than the results obtained by other standard detection approaches of cervical cancer using graph cuts.
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Zhou, Hao, Yun Gao, Guo Wu Yuan, and Xue Jie Zhang. "A Fast Convergent Adaptive-K Mixture-Of-Gaussian Model for Video Object Segmentation." Advanced Materials Research 694-697 (May 2013): 1919–24. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1919.
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It is a key step to extract moving objects from background for computer vision applications. GMM based methods are the most commonly used technique for background subtraction in video sequence. However, how to establish efficient and precision background model with fast convergence rate is a Research-Worthy problem. In this paper, an effective scheme is proposed to accelerate the convergence rate of Adaptive-K Gaussian Mixture Model (AKGMM). The AKGMM algorithm alters the dimension of the parameter space at each pixel based on the changing frequency of pixel value. The number of GMM reflects the complexity of pattern at the pixel. An improved learning method is proposed for Gaussian Mixture Model. An adaptive learning rate is calculated for each Gaussian at every frame for speeding up the convergence without compromising model stability. Experimental results demonstrated that the proposed method gets a faster convergence while maintaining good robustness against complex environment compared to a conventional method.
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Freifeld, Oren, Hayit Greenspan, and Jacob Goldberger. "Multiple Sclerosis Lesion Detection Using Constrained GMM and Curve Evolution." International Journal of Biomedical Imaging 2009 (2009): 1–13. http://dx.doi.org/10.1155/2009/715124.
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This paper focuses on the detection and segmentation of Multiple Sclerosis (MS) lesions in magnetic resonance (MRI) brain images. To capture the complex tissue spatial layout, a probabilistic model termed Constrained Gaussian Mixture Model (CGMM) is proposed based on a mixture of multiple spatially oriented Gaussians per tissue. The intensity of a tissue is considered a global parameter and is constrained, by a parameter-tying scheme, to be the same value for the entire set of Gaussians that are related to the same tissue. MS lesions are identified as outlier Gaussian components and are grouped to form a new class in addition to the healthy tissue classes. A probability-based curve evolution technique is used to refine the delineation of lesion boundaries. The proposed CGMM-CE algorithm is used to segment 3D MRI brain images with an arbitrary number of channels. The CGMM-CE algorithm is automated and does not require an atlas for initialization or parameter learning. Experimental results on both standard brain MRI simulation data and real data indicate that the proposed method outperforms previously suggested approaches, especially for highly noisy data.
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Ding, Ing-Jr, Chih-Ta Yen, and Zih-Jheng Lin. "FUZZY LOGIC-BASED INTELLIGENT CONTROL FOR SVM SPEAKER VERIFICATION WITH THE SUPPORT OF GMM PRIOR INFORMATION." Transactions of the Canadian Society for Mechanical Engineering 37, no. 3 (September 2013): 467–76. http://dx.doi.org/10.1139/tcsme-2013-0036.
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In this paper, a fuzzy logic-based intelligent control (FLIC) scheme for support vector machine (SVM) speaker verification, called FLICSVM, is developed. The proposed FLICSVM method enhances SVM training by considering the property of training utterances for establishing the SVM model and therefore could further ensure the robustness of the SVM classifier on speaker verification. In FLICSVM, when establishing the SVM model in the training procedure, the popular fuzzy control methodology is employed to tune certain specific SVM parameter according to the prior information of SVM training utterances that is derived from Gaussian mixture model (GMM) calculations. Experimental results demonstrated that proposed FLICSVM is apparently superior to conventional SVM in the recognition accuracy.
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Wang, Xin Hua, Shou Qiang Hu, Qian Yi Ya, Shu Wen Sun, and Xiu Xia Cao. "Research on Control Power and Self-Sensing Technology for GMM Self-Sensing Actuator." Applied Mechanics and Materials 34-35 (October 2010): 1314–18. http://dx.doi.org/10.4028/www.scientific.net/amm.34-35.1314.
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Structure and principle of a new kind of diphase opposition giant magnetostrictive self-sensing actuator (SSA for short) is introduced, for which a kind of double outputs high-precision NC stable voltage power is designed. With the method of combining with the hardware design and the software setting, the controllability and reliability of the actuator are greatly improved. And the whole design becomes more reasonable, which saves the cost and improves the practicability. In addition, based on the micro controller unit (MCU) with high-speed control, the scheme design of the real-time separation circuit for dynamic balance signal can effectively identify out and pick up the self-sensing signal which changes from foreign pressure feed back. Then the SSA real-time, dynamic and accurately control is realized. The experiment results show that the voltage power can high-speed and accurately output both output voltages with high current, and that the self-sensing signal decoupling circuit can isolate the self-sensing signals without distortion
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Pourghassem, Hossein. "A novel material detection algorithm based on 2D GMM-based power density function and image detail addition scheme in dual energy X-ray images." Journal of X-Ray Science and Technology 20, no. 2 (2012): 213–28. http://dx.doi.org/10.3233/xst-2012-0330.
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Li, Qiuling, Xiao Chen, Bingbing Wang, Jing Liu, Guofeng Zhang, and Bin Feng. "Shot Boundary Detection Based on Global Features and the Target Features." Symmetry 15, no. 3 (February 21, 2023): 565. http://dx.doi.org/10.3390/sym15030565.
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Video processing plays an important role in the intelligent monitoring and management system of agricultural information. Video shot boundary detection is the basic symmetry step underlying video processing techniques. According to the current shot boundary detection algorithm, the feature changes between gradual transition frames are difficult to detect, and the misdetection situation is caused by ignoring the attention of the target feature during the feature extraction. A novel symmetry multi-step comparative scheme of shot boundary detection algorithm based on global features and target features is proposed. First, the RGB color histogram features of the video frame are extracted. Second, foreground object detection for the video frames is performed using the Gaussian Mixture Model (GMM), and the scale-invariant features transformation (SIFT) of the foreground targets is extracted. Finally, global features and target features fusion through weights, calculating the difference between adjacent frames across multiple steps, generate a pattern distance map. The pattern distance map of the gradual transition and the cut detection is different; we can judge the gradual transition and the cut detection according to the pattern distance map. Experiments show that the proposed symmetry method improves by about 2% in recall and accuracy compared to other algorithms.
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Lin, Fandel, and Hsun-Ping Hsieh. "A Joint Passenger Flow Inference and Path Recommender System for Deploying New Routes and Stations of Mass Transit Transportation." ACM Transactions on Knowledge Discovery from Data 16, no. 1 (July 3, 2021): 1–36. http://dx.doi.org/10.1145/3451393.
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In this work, a novel decision assistant system for urban transportation, called Route Scheme Assistant (RSA), is proposed to address two crucial issues that few former researches have focused on: route-based passenger flow (PF) inference and multivariant high-PF route recommendation. First, RSA can estimate the PF of arbitrary user-designated routes effectively by utilizing Deep Neural Network (DNN) for regression based on geographical information and spatial-temporal urban informatics. Second, our proposed Bidirectional Prioritized Spanning Tree (BDPST) intelligently combines the parallel computing concept and Gaussian mixture model (GMM) for route recommendation under users’ constraints running in a timely manner. We did experiments on bus-ticket data of Tainan and Chicago and the experimental results show that the PF inference model outperforms baseline and comparative methods from 41% to 57%. Moreover, the proposed BDPST algorithm's performance is not far away from the optimal PF and outperforms other comparative methods from 39% to 71% in large-scale route recommendations.
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Li, Yang, Zhuang Li, Yanping Wang, Guangda Xie, Yun Lin, Wenjie Shen, and Wen Jiang. "Improving the Performance of RODNet for MMW Radar Target Detection in Dense Pedestrian Scene." Mathematics 11, no. 2 (January 10, 2023): 361. http://dx.doi.org/10.3390/math11020361.
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In the field of autonomous driving, millimeter-wave (MMW) radar is often used as a supplement sensor of other types of sensors, such as optics, in severe weather conditions to provide target-detection services for autonomous driving. RODNet (A Real-Time Radar Object-Detection Network) is one of the most widely used MMW radar range–azimuth (RA) image sequence target-detection algorithms based on Convolutional Neural Networks (CNNs). However, RODNet adopts an object-location similarity (OLS) detection method that is independent of the number of targets to obtain the final target detections from the predicted confidence map. Therefore, it gives a poor performance on missed detection ratio in dense pedestrian scenes. Based on the analysis of the predicted confidence map distribution characteristics, we propose a new generative model-based target-location detection algorithm to improve the performance of RODNet in dense pedestrian scenes. The confidence value and space distribution predicted by RODNet are analyzed in this paper. It shows that the space distribution is more robust than the value distribution for clustering. This is useful in selecting a clustering method to estimate the clustering centers of multiple targets in close range under the effects of distributed target and radar measurement variance and multipath scattering. Another key idea of this algorithm is the derivation of a Gaussian Mixture Model with target number (GMM-TN) for generating the likelihood probability distributions of different target number assumptions. Furthermore, a minimum Kullback–Leibler (KL) divergence target number estimation scheme is proposed combined with K-means clustering and a GMM-TN model. Through the CRUW dataset, the target-detection experiment on a dense pedestrian scene is carried out, and the confidence distribution under typical hidden variable conditions is analyzed. The effectiveness of the improved algorithm is verified: the Average Precision (AP) is improved by 29% and the Average Recall (AR) is improved by 36%.
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Beaklini, Pedro P. B., Allan V. C. Quadros, Marcio G. B. de Avellar, Maria L. L. Dantas, and André L. F. Cançado. "AGN dichotomy beyond radio loudness: a Gaussian mixture model analysis." Monthly Notices of the Royal Astronomical Society 497, no. 2 (July 15, 2020): 1463–74. http://dx.doi.org/10.1093/mnras/staa2072.
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ABSTRACT Since the discovery of quasi-stellar objects (QSOs), also known as quasars, they have been traditionally subdivided as radio-loud and radio-quiet sources. Whether such division is a misleading effect from a highly heterogeneous single population of objects, or real has yet to be answered. Such dichotomy has been evidenced by observations of the flux ratio between the optical and radio emissions (usually B band and 5 GHz). Evidence of two populations in quasars and samples of a wide diversity of active galactic nuclei (AGNs) has been accumulated over the years. Other quantities beyond radio loudness also seem to show the signature of the existence of two different populations of AGNs. To verify the existence of a dichotomy through different parameters, we employed a soft clustering scheme, based on the Gaussian mixture model (GMM), to classify these objects simultaneously using the following parameters: black hole mass, colour, and R loudness index, as well as the usual radio and B-band luminosity. To investigate whether different kinds of AGNs manifest any population dichotomy, we applied GMM to four independent catalogues composed of both optical and radio information. Our results indicate the persistence of a dichotomy in all data sets, although the discriminating power differs for different choices of parameters. Although the radio loudness parameter alone does not seem to be enough to display the dichotomy, the evidence of two populations of AGNs could persist even if we consider other parameters. Our research suggests that the dichotomy is not a misleading effect but real.
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Xiong, Chenyao, Qingsong Li, Dingjie Wang, and Jie Wu. "Using Multi-Antenna Trajectory Constraint to Analyze BeiDou Carrier-Phase Observation Error of Dynamic Receivers." Sensors 21, no. 20 (October 19, 2021): 6930. http://dx.doi.org/10.3390/s21206930.
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Appropriate cycle-slip and measurement-error models are essential for BeiDou carrier-phase-based integrity risk calculation. To establish the receiver’s measurement-error model, an accurate position reference of the GNSS antenna is fundamental for calculating the measurement error. However, it is still a challenge to acquire position references for dynamic BeiDou receivers, resulting in improper GNSS measurement-error models and unreliable integrity monitoring. This paper proposes an improved precise relative positioning scheme by adopting multi-antenna trajectory constraints for dynamic BeiDou receivers. The dynamic experiments show an obvious decline of 78.7%, at most, in the positioning failure rate of the proposed method, as compared with the traditional method. The position solutions obtained from the proposed approach are used as the reference to analyze the cycle-slip and measurement-error characteristics of the dynamic receiver. The field test results indicate that the cycle-slip rate decreases with the increase of signal-to-noise ratio (SNR), and cycle slipping obeys a positively skewed distribution that could be fitted by the Gaussian mixture model (GMM). On the other hand, the standard deviation of the carrier-phase measurement error is inversely proportional to SNR, and its distribution is characteristically fat-tailed, which could be fitted by the bi-normal model.
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Liu, Hongqiang, Zhongliang Zhou, and Chunguang Lu. "Maneuvering Detection Using Multiple Parallel CUSUM Detector." Mathematical Problems in Engineering 2018 (2018): 1–17. http://dx.doi.org/10.1155/2018/5062184.
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The switching model tracking algorithm based on hard decisions is an important method to solve the maneuvering target tracking problem. The use of Doppler velocity not only helps shorten the delay time of maneuvering detection but also provides information about the target motion model. A novel target maneuvering detection method named Multiple Parallel Cumulative Sum (M-CUSUM) for target multiple maneuvering models is proposed in this paper based on Doppler velocity. The main scheme of the proposed approach consists of the following: firstly, the problem framework of multiple model maneuvering detection is put forward; secondly, the statistic of acceleration is obtained through modeling the mapping relationship between Doppler velocity and the normal/tangential acceleration according to the geometry and kinematics; thirdly, the joint empirical distribution of the normal/tangential acceleration is obtained by the statistical experiment method and then the approximate joint probability distribution function of the normal/tangential acceleration is acquired by use of Gaussian Mixture Model (GMM) with Expectation Maximization (EM) algorithm; fourthly, it is taken as the prior information of target maneuvering which is introduced to the likelihood ratio of prediction measurement residual by the marginalization method; finally, the standard Cumulative Sum (CUSUM) detector is extended as Multiple Parallel CUSUM detector. Simulation results show that M-CUSUM detector has a smaller maneuver onset detection delay time compared with similar detectors and has the ability of pattern recognition of target maneuvers.
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Levy, G., M. Coon, G. Nguyen, and D. Sulsky. "Physically-based data assimilation." Geoscientific Model Development 3, no. 2 (November 29, 2010): 669–77. http://dx.doi.org/10.5194/gmd-3-669-2010.
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Abstract. Ideally, a validation and assimilation scheme should maintain the physical principles embodied in the model and be able to evaluate and assimilate lower dimensional features (e.g., discontinuities) contained within a bulk simulation, even when these features are not directly observed or represented by model variables. We present such a scheme and suggest its potential to resolve or alleviate some outstanding problems that stem from making and applying required, yet often non-physical, assumptions and procedures in common operational data assimilation. As proof of concept, we use a sea-ice model with remotely sensed observations of leads in a one-step assimilation cycle. Using the new scheme in a sixteen day simulation experiment introduces model skill (against persistence) several days earlier than in the control run, improves the overall model skill and delays its drop off at later stages of the simulation. The potential and requirements to extend this scheme to different applications, and to both empirical and statistical multivariate and full cycle data assimilation schemes, are discussed.
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Guimberteau, M., A. Ducharne, P. Ciais, J. P. Boisier, S. Peng, M. De Weirdt, and H. Verbeeck. "Testing conceptual and physically based soil hydrology schemes against observations for the Amazon Basin." Geoscientific Model Development 7, no. 3 (June 6, 2014): 1115–36. http://dx.doi.org/10.5194/gmd-7-1115-2014.
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Abstract. This study analyzes the performance of the two soil hydrology schemes of the land surface model ORCHIDEE in estimating Amazonian hydrology and phenology for five major sub-basins (Xingu, Tapajós, Madeira, Solimões and Negro), during the 29-year period 1980–2008. A simple 2-layer scheme with a bucket topped by an evaporative layer is compared to an 11-layer diffusion scheme. The soil schemes are coupled with a river routing module and a process model of plant physiology, phenology and carbon dynamics. The simulated water budget and vegetation functioning components are compared with several data sets at sub-basin scale. The use of the 11-layer soil diffusion scheme does not significantly change the Amazonian water budget simulation when compared to the 2-layer soil scheme (+3.1 and −3.0% in evapotranspiration and river discharge, respectively). However, the higher water-holding capacity of the soil and the physically based representation of runoff and drainage in the 11-layer soil diffusion scheme result in more dynamic soil water storage variation and improved simulation of the total terrestrial water storage when compared to GRACE satellite estimates. The greater soil water storage within the 11-layer scheme also results in increased dry-season evapotranspiration (+0.5 mm d−1, +17%) and improves river discharge simulation in the southeastern sub-basins such as the Xingu. Evapotranspiration over this sub-basin is sustained during the whole dry season with the 11-layer soil diffusion scheme, whereas the 2-layer scheme limits it after only 2 dry months. Lower plant drought stress simulated by the 11-layer soil diffusion scheme leads to better simulation of the seasonal cycle of photosynthesis (GPP) when compared to a GPP data-driven model based on eddy covariance and satellite greenness measurements. A dry-season length between 4 and 7 months over the entire Amazon Basin is found to be critical in distinguishing differences in hydrological feedbacks between the soil and the vegetation cover simulated by the two soil schemes. On average, the multilayer soil diffusion scheme provides little improvement in simulated hydrology over the wet tropical Amazonian sub-basins, but a more significant improvement is found over the drier sub-basins. The use of a multilayer soil diffusion scheme might become critical for assessments of future hydrological changes, especially in southern regions of the Amazon Basin where longer dry seasons and more severe droughts are expected in the next century.
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Teh, Je Sen, and Azman Samsudin. "A Chaos-Based Authenticated Cipher with Associated Data." Security and Communication Networks 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/9040518.
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In recent years, there has been a rising interest in authenticated encryption with associated data (AEAD) which combines encryption and authentication into a unified scheme. AEAD schemes provide authentication for a message that is divided into two parts: associated data which is not encrypted and the plaintext which is encrypted. However, there is a lack of chaos-based AEAD schemes in recent literature. This paper introduces a new 128-bit chaos-based AEAD scheme based on the single-key Even-Mansour and Type-II generalized Feistel structure. The proposed scheme provides both privacy and authentication in a single-pass using only one 128-bit secret key. The chaotic tent map is used to generate whitening keys for the Even-Mansour construction, round keys, and random s-boxes for the Feistel round function. In addition, the proposed AEAD scheme can be implemented with true random number generators to map a message to multiple possible ciphertexts in a nondeterministic manner. Security and statistical evaluation indicate that the proposed scheme is highly secure for both the ciphertext and the authentication tag. Furthermore, it has multiple advantages over AES-GCM which is the current standard for authenticated encryption.
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Theodoritsi, Georgia N., Giancarlo Ciarelli, and Spyros N. Pandis. "Simulation of the evolution of biomass burning organic aerosol with different volatility basis set schemes in PMCAMx-SRv1.0." Geoscientific Model Development 14, no. 4 (April 21, 2021): 2041–55. http://dx.doi.org/10.5194/gmd-14-2041-2021.
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Abstract. A source-resolved three-dimensional chemical transport model, PMCAMx-SR (Particulate Matter Comprehensive Air-quality Model with extensions – Source Resolved), was applied in the continental US to investigate the contribution of the various components (primary and secondary) of biomass burning organic aerosol (bbOA) to organic aerosol levels. Two different schemes based on the volatility basis set were used for the simulation of the bbOA during different seasons. The first is the default scheme of PMCAMx-SR, and the second is a recently developed scheme based on laboratory experiments of the bbOA evolution. The simulations with the alternative bbOA scheme predict much higher total bbOA concentrations when compared with the base case ones. This is mainly due to the high emissions of intermediate-volatility organic compounds (IVOCs) assumed in the alternative scheme. The oxidation of these compounds is predicted to be a significant source of secondary organic aerosol. The impact of the other parameters that differ in the two schemes is low to negligible. The monthly average maximum predicted concentrations of the alternative bbOA scheme were approximately an order of magnitude higher than those of the default scheme during all seasons. The performance of the two schemes was evaluated against observed total organic aerosol concentrations from several measurement sites across the US. The results were different for the different seasons examined. The default scheme performed better during July and September, while the alternative scheme performed a little better during April. These results illustrate the uncertainty of the corresponding predictions and the need to quantify the emissions and reactions of IVOCs from specific biomass sources and to better constrain the total (primary and secondary) bbOA levels.
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Yin, Jinfang, Xudong Liang, Hong Wang, and Haile Xue. "Representation of the autoconversion from cloud to rain using a weighted ensemble approach: a case study using WRF v4.1.3." Geoscientific Model Development 15, no. 2 (January 27, 2022): 771–86. http://dx.doi.org/10.5194/gmd-15-771-2022.
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Abstract. Cloud and precipitation processes remain among the largest sources of uncertainties in weather and climate modelling, and considerable attention has been paid to improving the representation of the cloud and precipitation processes in numerical models in the last several decades. In this study, we develop a weighted ensemble (named EN) scheme by employing several widely used autoconversion (ATC) schemes to represent the ATC from cloud water to rainwater. One unique feature of the EN approach is that the ATC rate is a weighted mean value based on the calculations from several ATC schemes within a microphysics scheme with a negligible increase in computation cost. The EN scheme is compared with the several commonly used ATC schemes by performing real case simulations. In terms of accumulated rainfall and extreme hourly rainfall rate, the EN scheme provides better simulations than by using the single Berry–Reinhardt scheme, which was originally used in the Thompson scheme. It is worth emphasizing, in the present study, that we only pay attention to the ATC process from cloud water into rainwater with the purpose of improving the modelling of the extreme rainfall events over southern China. Actually, any (source and sink) term in a cloud microphysics scheme can be treated with the same approach. The ensemble method proposed herein appears to have important implications for developing cloud microphysics schemes in numerical models, especially for the models with variable grid resolution, which would be expected to improve the representation of cloud microphysical processes in the weather and climate models.
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He, Yanfeng, Hossain Mohammed Syedul Hoque, and Kengo Sudo. "Introducing new lightning schemes into the CHASER (MIROC) chemistry–climate model." Geoscientific Model Development 15, no. 14 (July 21, 2022): 5627–50. http://dx.doi.org/10.5194/gmd-15-5627-2022.
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Abstract. The formation of nitrogen oxides (NOx) associated with lightning activities (hereinafter designated as LNOx) is a major source of NOx. In fact, it is regarded as the dominant NOx source in the middle to upper troposphere. Therefore, improving the prediction accuracy of lightning and LNOx in chemical climate models is crucially important. This study implemented three new lightning schemes with the CHASER (MIROC) global chemical transport and climate model. The first lightning scheme is based on upward cloud ice flux (ICEFLUX scheme). The second one (the original ECMWF scheme), also adopted in the European Centre for Medium-Range Weather Forecasts (ECMWF) forecasting system, calculates lightning flash rates as a function of QR (a quantity intended to represent the charging rate of collisions between graupel and other types of hydrometeors inside the charge separation region), convective available potential energy (CAPE), and convective cloud-base height. For the original ECMWF scheme, by tuning the equations and adjustment factors for land and ocean, a new lightning scheme called the ECMWF-McCAUL scheme was also tested in CHASER. The ECMWF-McCAUL scheme calculates lightning flash rates as a function of CAPE and column precipitating ice. In the original version of CHASER (MIROC), lightning is initially parameterized with the widely used cloud-top height scheme (CTH scheme). Model evaluations with lightning observations conducted using the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) indicate that both the ICEFLUX and ECMWF schemes simulate the spatial distribution of lightning more accurately on a global scale than the CTH scheme does. The ECMWF-McCAUL scheme showed the highest prediction accuracy for the global distribution of lightning. Evaluation by atmospheric tomography (ATom) aircraft observations (NO) and tropospheric monitoring instrument (TROPOMI) satellite observations (NO2) shows that the newly implemented lightning schemes partially facilitated the reduction of model biases (NO and NO2), typically within the regions where LNOx is the major source of NOx, when compared to using the CTH scheme. Although the newly implemented lightning schemes have a minor effect on the tropospheric mean oxidation capacity compared to the CTH scheme, they led to marked changes in oxidation capacity in different regions of the troposphere. Historical trend analyses of flash and surface temperatures predicted using CHASER (2001–2020) show that lightning schemes predicted increasing trends of lightning or no significant trends, except for one case of the ICEFLUX scheme, which predicted a decreasing trend of lightning. The global lightning rates of increase during 2001–2020 predicted by the CTH scheme were 17.69 % ∘C−1 and 2.50 % ∘C−1, respectively, with and without meteorological nudging. The un-nudged runs also included the short-term surface warming but without the application of meteorological nudging. Furthermore, the ECMWF schemes predicted a larger increasing trend of lightning flash rates under the short-term surface warming by a factor of 4 (ECMWF-McCAUL scheme) and 5 (original ECMWF scheme) compared to the CTH scheme without nudging. In conclusion, the three new lightning schemes improved global lightning prediction in the CHASER model. However, further research is needed to assess the reproducibility of trends of lightning over longer periods.
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Kang, Daiwen, Kenneth E. Pickering, Dale J. Allen, Kristen M. Foley, David C. Wong, Rohit Mathur, and Shawn J. Roselle. "Simulating lightning NO production in CMAQv5.2: evolution of scientific updates." Geoscientific Model Development 12, no. 7 (July 18, 2019): 3071–83. http://dx.doi.org/10.5194/gmd-12-3071-2019.
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Abstract. This work describes the lightning nitric oxide (LNO) production schemes in the Community Multiscale Air Quality (CMAQ) model. We first document the existing LNO production scheme and vertical distribution algorithm. We then describe updates that were made to the scheme originally based on monthly National Lightning Detection Network (mNLDN) observations. The updated scheme uses hourly NLDN (hNLDN) observations. These NLDN-based schemes are good for retrospective model applications when historical lightning data are available. For applications when observed data are not available (i.e., air quality forecasts and climate studies that assume similar climate conditions), we have developed a scheme that is based on linear and log-linear parameters derived from regression of multiyear historical NLDN (pNLDN) observations and meteorological model simulations. Preliminary assessment for total column LNO production reveals that the mNLDN scheme overestimates LNO by over 40 % during summer months compared with the updated hNLDN scheme that reflects the observed lightning activity more faithfully in time and space. The pNLDN performance varies with year, but it generally produced LNO columns that are comparable to hNLDN and mNLDN, and in most cases it outperformed mNLDN. Thus, when no observed lightning data are available, pNLDN can provide reasonable estimates of LNO emissions over time and space for this important natural NO source that influences air quality regulations.
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Hong, S., X. Yu, S. K. Park, Y. S. Choi, and B. Myoung. "Assessing optimal set of implemented physical parameterization schemes in a multi-physics land surface model using genetic algorithm." Geoscientific Model Development 7, no. 5 (October 29, 2014): 2517–29. http://dx.doi.org/10.5194/gmd-7-2517-2014.
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Abstract. Optimization of land surface models has been challenging due to the model complexity and uncertainty. In this study, we performed scheme-based model optimizations by designing a framework for coupling "the micro-genetic algorithm" (micro-GA) and "the Noah land surface model with multiple physics options" (Noah-MP). Micro-GA controls the scheme selections among eight different land surface parameterization categories, each containing 2–4 schemes, in Noah-MP in order to extract the optimal scheme combination that achieves the best skill score. This coupling framework was successfully applied to the optimizations of evapotranspiration and runoff simulations in terms of surface water balance over the Han River basin in Korea, showing outstanding speeds in searching for the optimal scheme combination. Taking advantage of the natural selection mechanism in micro-GA, we explored the model sensitivity to scheme selections and the scheme interrelationship during the micro-GA evolution process. This information is helpful for better understanding physical parameterizations and hence it is expected to be effectively used for further optimizations with uncertain parameters in a specific set of schemes.
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Shiu, Chein-Jung, Yi-Chi Wang, Huang-Hsiung Hsu, Wei-Ting Chen, Hua-Lu Pan, Ruiyu Sun, Yi-Hsuan Chen, and Cheng-An Chen. "GTS v1.0: a macrophysics scheme for climate models based on a probability density function." Geoscientific Model Development 14, no. 1 (January 12, 2021): 177–204. http://dx.doi.org/10.5194/gmd-14-177-2021.
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Abstract. Cloud macrophysics schemes are unique parameterizations for general circulation models. We propose an approach based on a probability density function (PDF) that utilizes cloud condensates and saturation ratios to replace the assumption of critical relative humidity (RH). We test this approach, called the Global Forecast System (GFS) – Taiwan Earth System Model (TaiESM) – Sundqvist (GTS) scheme, using the macrophysics scheme within the Community Atmosphere Model version 5.3 (CAM5.3) framework. Via single-column model results, the new approach simulates the cloud fraction (CF)–RH distributions closer to those of the observations when compared to those of the default CAM5.3 scheme. We also validate the impact of the GTS scheme on global climate simulations with satellite observations. The simulated CF is comparable to CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. Comparisons of the vertical distributions of CF and cloud water content (CWC), as functions of large-scale dynamic and thermodynamic parameters, with the CloudSat/CALIPSO data suggest that the GTS scheme can closely simulate observations. This is particularly noticeable for thermodynamic parameters, such as RH, upper-tropospheric temperature, and total precipitable water, implying that our scheme can simulate variation in CF associated with RH more reliably than the default scheme. Changes in CF and CWC would affect climatic fields and large-scale circulation via cloud–radiation interaction. Both climatological means and annual cycles of many of the GTS-simulated variables are improved compared with the default scheme, particularly with respect to water vapor and RH fields. Different PDF shapes in the GTS scheme also significantly affect global simulations.
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Arabas, S., A. Jaruga, H. Pawlowska, and W. W. Grabowski. "libcloudph++ 1.0: a single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++." Geoscientific Model Development 8, no. 6 (June 9, 2015): 1677–707. http://dx.doi.org/10.5194/gmd-8-1677-2015.
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Abstract. This paper introduces a library of algorithms for representing cloud microphysics in numerical models. The library is written in C++, hence the name libcloudph++. In the current release, the library covers three warm-rain schemes: the single- and double-moment bulk schemes, and the particle-based scheme with Monte Carlo coalescence. The three schemes are intended for modelling frameworks of different dimensionalities and complexities ranging from parcel models to multi-dimensional cloud-resolving (e.g. large-eddy) simulations. A two-dimensional (2-D) prescribed-flow framework is used in the paper to illustrate the library features. The libcloudph++ and all its mandatory dependencies are free and open-source software. The Boost.units library is used for zero-overhead dimensional analysis of the code at compile time. The particle-based scheme is implemented using the Thrust library that allows one to leverage the power of graphics processing units (GPU), retaining the possibility of compiling the unchanged code for execution on single or multiple standard processors (CPUs). The paper includes a complete description of the programming interface (API) of the library and a performance analysis including comparison of GPU and CPU set-ups.
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Saito, Fuyuki, Takashi Obase, and Ayako Abe-Ouchi. "Implementation of the RCIP scheme and its performance for 1-D age computations in ice-sheet models." Geoscientific Model Development 13, no. 11 (November 28, 2020): 5875–96. http://dx.doi.org/10.5194/gmd-13-5875-2020.
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Abstract. Ice-sheet age computations are formulated using an Eulerian advection equation, and there are many schemes that can be used to solve them numerically. Typically, these differ in numerical characteristics such as stability, accuracy, and diffusivity. Furthermore, although various methods have been presented for ice-sheet age computations, the constrained interpolation profile method and its variants have not been examined in this context. The present study introduces one of its variants, a rational function-based constrained interpolation profile (RCIP) scheme, to one-dimensional ice age computation and demonstrates its performance levels via comparisons with those obtained from first- and second-order upwind schemes. Our results show that the RCIP scheme preserves the pattern of input surface mass balance histories in terms of the vertical profile of internal annual layer thickness better than the other schemes.
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Islam, Saif Ul, and Soobae Kim. "Design of an Optimal Adoptive Fault Ride through Scheme for Overcurrent Protection of Grid-Forming Inverter-Based Resources under Symmetrical Faults." Sustainability 15, no. 8 (April 15, 2023): 6705. http://dx.doi.org/10.3390/su15086705.
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As the integration of inverter-based resources (IBRs) is rapidly increasing in regard to the existing power system, switching from grid-following (GFL) to grid-forming (GFM) inverter control is the solution to maintain grid resilience. However, additional overcurrent protection, especially during fault transition, is required due to limited overcurrent capability and the high magnitude of spikes during fault recovery in IBRs, specifically in the GFM control mode. Furthermore, the power system stability should not be compromised by the employment of additional fault ride through (FRT) schemes. This article presents the design and implementation of an adoptive fault ride through (FRT) scheme for grid-forming inverters under symmetrical fault conditions. The proposed adoptive FRT scheme is comprised of two cascaded power electronic-based circuits, i.e., fault current ride through and a spikes reactor. This adoptive FRT scheme optimizes the fault variables during the fault time and suppresses the fault clearing spikes, without affecting system stability. A three-bus inverter-based grid-forming model is used in MATLAB/Simulink for the implementation of the proposed scheme. Further, a conventionally used FRT scheme, which includes fault current reactors, is simulated in the same test environment for justification of the proposed adoptive scheme. The adoptive FRT scheme is simulated for both time domain and frequency domain to analyze the response of harmonic distortion with the suppression of the fault current. Moreover, the proposed scheme is also simulated under the GFL mode of IBRs to justify the reliability of the scheme. The overall simulation results and performance evaluation indices authenticate the optimal, fault tolerant, harmonic, and spike-free behavior of the proposed scheme at both the AC and DC side of the grid-forming inverters.
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Sørensen, B., E. Kaas, and U. S. Korsholm. "A mass-conserving and multi-tracer efficient transport scheme in the online integrated Enviro-HIRLAM model." Geoscientific Model Development 6, no. 4 (July 22, 2013): 1029–42. http://dx.doi.org/10.5194/gmd-6-1029-2013.
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Abstract. In this paper a new advection scheme for the online coupled chemical–weather prediction model Enviro-HIRLAM is presented. The new scheme is based on the locally mass-conserving semi-Lagrangian method (LMCSL), where the original two-dimensional scheme has been extended to a fully three-dimensional version. This means that the three-dimensional semi-implicit semi-Lagrangian scheme which is currently used in Enviro-HIRLAM is largely unchanged. The HIRLAM model is a computationally efficient hydrostatic operational short-term numerical weather prediction model, which is used as the base for the online integrated Enviro-HIRLAM. The new scheme is shown to be efficient, mass conserving, and shape preserving, while only requiring minor alterations to the original code. It still retains the stability at long time steps, which the semi-Lagrangian schemes are known for, while handling the emissions of chemical species accurately. Several mass-conserving filters have been tested to assess the optimal balance of accuracy vs. efficiency.
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Niyogi, Dev, Kiran Alapaty, Sethu Raman, and Fei Chen. "Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications." Journal of Applied Meteorology and Climatology 48, no. 2 (February 1, 2009): 349–68. http://dx.doi.org/10.1175/2008jamc1662.1.
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Abstract Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.
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Leriche, M., J. P. Pinty, C. Mari, and D. Gazen. "A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases." Geoscientific Model Development 6, no. 4 (August 22, 2013): 1275–98. http://dx.doi.org/10.5194/gmd-6-1275-2013.
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Abstract. A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous- and aqueous-phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas- and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel) of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to the retention efficiency of gases in the ice phase. The 2-D and 3-D simulations illustrate that the retention in ice of a moderately soluble gas such as formaldehyde substantially decreases its concentration in the upper troposphere. In these simulations, retention of highly soluble species in the ice phase significantly increased the wet deposition rates.
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Rößler, Thomas, Olaf Stein, Yi Heng, Paul Baumeister, and Lars Hoffmann. "Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses." Geoscientific Model Development 11, no. 2 (February 8, 2018): 575–92. http://dx.doi.org/10.5194/gmd-11-575-2018.
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Abstract. The accuracy of trajectory calculations performed by Lagrangian particle dispersion models (LPDMs) depends on various factors. The optimization of numerical integration schemes used to solve the trajectory equation helps to maximize the computational efficiency of large-scale LPDM simulations. We analyzed global truncation errors of six explicit integration schemes of the Runge–Kutta family, which we implemented in the Massive-Parallel Trajectory Calculations (MPTRAC) advection module. The simulations were driven by wind fields from operational analysis and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) at T1279L137 spatial resolution and 3 h temporal sampling. We defined separate test cases for 15 distinct regions of the atmosphere, covering the polar regions, the midlatitudes, and the tropics in the free troposphere, in the upper troposphere and lower stratosphere (UT/LS) region, and in the middle stratosphere. In total, more than 5000 different transport simulations were performed, covering the months of January, April, July, and October for the years 2014 and 2015. We quantified the accuracy of the trajectories by calculating transport deviations with respect to reference simulations using a fourth-order Runge–Kutta integration scheme with a sufficiently fine time step. Transport deviations were assessed with respect to error limits based on turbulent diffusion. Independent of the numerical scheme, the global truncation errors vary significantly between the different regions. Horizontal transport deviations in the stratosphere are typically an order of magnitude smaller compared with the free troposphere. We found that the truncation errors of the six numerical schemes fall into three distinct groups, which mostly depend on the numerical order of the scheme. Schemes of the same order differ little in accuracy, but some methods need less computational time, which gives them an advantage in efficiency. The selection of the integration scheme and the appropriate time step should possibly take into account the typical altitude ranges as well as the total length of the simulations to achieve the most efficient simulations. However, trying to summarize, we recommend the third-order Runge–Kutta method with a time step of 170 s or the midpoint scheme with a time step of 100 s for efficient simulations of up to 10 days of simulation time for the specific ECMWF high-resolution data set considered in this study. Purely stratospheric simulations can use significantly larger time steps of 800 and 1100 s for the midpoint scheme and the third-order Runge–Kutta method, respectively.
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Gutjahr, Oliver, Nils Brüggemann, Helmuth Haak, Johann H. Jungclaus, Dian A. Putrasahan, Katja Lohmann, and Jin-Song von Storch. "Comparison of ocean vertical mixing schemes in the Max Planck Institute Earth System Model (MPI-ESM1.2)." Geoscientific Model Development 14, no. 5 (May 3, 2021): 2317–49. http://dx.doi.org/10.5194/gmd-14-2317-2021.
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Abstract. For the first time, we compare the effects of four different ocean vertical mixing schemes on the mean state of the ocean and atmosphere in the Max Planck Institute Earth System Model (MPI-ESM1.2). These four schemes are namely the default Pacanowski and Philander (1981) (PP) scheme, the K-profile parameterization (KPP) from the Community Vertical Mixing (CVMix) library, a recently implemented scheme based on turbulent kinetic energy (TKE), and a recently developed prognostic scheme for internal wave dissipation, energy, and mixing (IDEMIX) to replace the often assumed constant background diffusivity in the ocean interior. In this study, the IDEMIX scheme is combined with the TKE scheme (collectively called the TKE+IDEMIX scheme) to provide an energetically more consistent framework for mixing, as it does not rely on the unwanted effect of creating spurious energy for mixing. Energetic consistency can have implications on the climate. Therefore, we focus on the effects of TKE+IDEMIX on the climate mean state and compare them with the first three schemes that are commonly used in other models but are not energetically consistent. We find warmer sea surface temperatures (SSTs) in the North Atlantic and Nordic Seas using KPP or TKE(+IDEMIX), which is related to 10 % higher overflows that cause a stronger and deeper upper cell of the Atlantic meridional overturning circulation (AMOC) and thereby an enhanced northward heat transport and higher inflow of warm and saline water from the Indian Ocean into the South Atlantic. Saltier subpolar North Atlantic and Nordic Seas lead to increased deep convection and thus to the increased overflows. Due to the warmer SSTs, the extratropics of the Northern Hemisphere become warmer with TKE(+IDEMIX), weakening the meridional gradient and thus the jet stream. With KPP, the tropics and the Southern Hemisphere also become warmer without weakening the jet stream. Using an energetically more consistent scheme (TKE+IDEMIX) produces a more heterogeneous and realistic pattern of vertical eddy diffusivity, with lower diffusivities in deep and flat-bottom basins and elevated turbulence over rough topography. IDEMIX improves in particular the diffusivity in the Arctic Ocean and reduces the warm bias in the Atlantic Water layer. We conclude that although shortcomings due to model resolution determine the global-scale bias pattern, the choice of the vertical mixing scheme may play an important role for regional biases.
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Séférian, Roland, Sunghye Baek, Olivier Boucher, Jean-Louis Dufresne, Bertrand Decharme, David Saint-Martin, and Romain Roehrig. "An interactive ocean surface albedo scheme (OSAv1.0): formulation and evaluation in ARPEGE-Climat (V6.1) and LMDZ (V5A)." Geoscientific Model Development 11, no. 1 (January 23, 2018): 321–38. http://dx.doi.org/10.5194/gmd-11-321-2018.
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Abstract. Ocean surface represents roughly 70 % of the Earth's surface, playing a large role in the partitioning of the energy flow within the climate system. The ocean surface albedo (OSA) is an important parameter in this partitioning because it governs the amount of energy penetrating into the ocean or reflected towards space. The old OSA schemes in the ARPEGE-Climat and LMDZ models only resolve the latitudinal dependence in an ad hoc way without an accurate representation of the solar zenith angle dependence. Here, we propose a new interactive OSA scheme suited for Earth system models, which enables coupling between Earth system model components like surface ocean waves and marine biogeochemistry. This scheme resolves spectrally the various contributions of the surface for direct and diffuse solar radiation. The implementation of this scheme in two Earth system models leads to substantial improvements in simulated OSA. At the local scale, models using the interactive OSA scheme better replicate the day-to-day distribution of OSA derived from ground-based observations in contrast to old schemes. At global scale, the improved representation of OSA for diffuse radiation reduces model biases by up to 80 % over the tropical oceans, reducing annual-mean model–data error in surface upwelling shortwave radiation by up to 7 W m−2 over this domain. The spatial correlation coefficient between modeled and observed OSA at monthly resolution has been increased from 0.1 to 0.8. Despite its complexity, this interactive OSA scheme is computationally efficient for enabling precise OSA calculation without penalizing the elapsed model time.
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Stegehuis, A. I., R. Vautard, P. Ciais, A. J. Teuling, D. G. Miralles, and M. Wild. "An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves." Geoscientific Model Development 8, no. 7 (July 29, 2015): 2285–98. http://dx.doi.org/10.5194/gmd-8-2285-2015.
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Abstract. Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface scheme, with the goal of detecting the most sensitive physics and identifying those that appear most suitable for simulating the heat wave events of 2003 in western Europe and 2010 in Russia. In total, 55 out of 216 simulations combining different atmospheric physical schemes have a temperature bias smaller than 1 °C during the heat wave episodes, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heat waves, and shortwave radiation is slightly overestimated. Convection is found to be the most sensitive atmospheric physical process impacting simulated heat wave temperature across four different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme configurations, which may be used in the future to perform heat wave analysis and to investigate the impact of climate change during summer in Europe.
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Chao, Winston C. "Catastrophe-Concept-Based Cumulus Parameterization: Correction of Systematic Errors in the Precipitation Diurnal Cycle over Land in a GCM." Journal of the Atmospheric Sciences 70, no. 11 (October 31, 2013): 3599–614. http://dx.doi.org/10.1175/jas-d-13-022.1.
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Abstract The onset of cumulus convection in a grid column is a catastrophe, also known as a subcritical instability. Accordingly, in designing a cumulus parameterization scheme the onset of cumulus convection requires that a parameter crosses a critical value and the termination of cumulus convection requires that the same or a different parameter crosses a different critical value. Once begun, cumulus convection continues to exist, regardless of whether the onset criterion is still met, until the termination criterion is met. Also, the intensity of cumulus precipitation is related to how far the state is from the termination, not the onset, criterion. The cumulus parameterization schemes currently in use in GCMs, however, treat the onset of cumulus convection as a supercritical instability; namely, convection is turned on when a parameter exceeds a critical value and is turned off when the same parameter falls below the same critical value. Also, the intensity of cumulus precipitation is related to how far this critical value has been exceeded. Among the adverse consequences of the supercritical-instability-concept-based cumulus parameterization schemes are that over relatively flat land the precipitation peak occurs around noon—4–6 h too soon—and that the amplitude of the precipitation diurnal cycle is too weak. Based on the above-mentioned concept, a new cumulus parameterization scheme was designed by taking advantage of the existing infrastructure of the relaxed Arakawa–Schubert scheme (RAS), but replacing RAS's guiding principle with the catastrophe concept. Test results using NASA's Goddard Earth Observing System GCM, version 5 (GEOS-5), show dramatic improvement in the phase and amplitude of the precipitation diurnal cycle over relatively flat land.
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Liu, Yaling, Mohamad Hejazi, Hongyi Li, Xuesong Zhang, and Guoyong Leng. "A hydrological emulator for global applications – HE v1.0.0." Geoscientific Model Development 11, no. 3 (March 23, 2018): 1077–92. http://dx.doi.org/10.5194/gmd-11-1077-2018.
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Abstract. While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.
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Seidel, Sarah, Valentin Garbe, Alexander Schmid, and Johannes Heitmann. "(Invited, Digital Presentation) High-κ Gate Oxide Integration and Ohmic Contact Development for AlGaN/GaN MISHEMTs." ECS Meeting Abstracts MA2022-01, no. 19 (July 7, 2022): 1050. http://dx.doi.org/10.1149/ma2022-01191050mtgabs.
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GaN based devices are one of the main candidates for current power electronics and RF applications [1,2]. For optimizing device performance, a detailed understanding of the defects contained in the material and the passivation capability of dielectric layers, i.e., the interfacial defect states formed, is mandatory. Here, we will focus on the surface defect passivation and gate leakage current reduction by introducing thin dielectric films as gate insulator in a so-called MISHEMT (metal insulator semiconductor high electron mobility transistors) device using different materials. The impact of a fully amorphous dielectric (Al2O3), which was kept amorphous by the integration of a low thermal budget ohmic contact [3], was compared to an epitaxial dielectric film (GdScO3) [4]. Due to the band alignment and the high dielectric constant of GdScO3, the spillover effect as it was seen for Al2O3 [5] has been suppressed and a reduction of threshold voltage shift due to the additional capacitance by the dielectric layer has been achieved. In addition, AlTiOx films were investigated as gate dielectrics [6]. To avoid further deterioration of the dielectric layer by the ohmic contact formation anneal, a gate last integration scheme was carried out using Ti based gold free ohmic source and drain contacts [7]. By varying the Al content, the band alignment between the underlying GaN capping layer to the thin film dielectric was controlled. By this means and additional charge engineering in the dielectric layer, a gate leakage reduction with limited threshold voltage increase has been realized. All dielectric layers have been electrically characterized in detail. Interface trap densities were measured by photo-assisted capacitance voltage measurements and an in-depth comparison of the dielectric layers and their impact on the device performance will be given. [1] Yole Developpement, RF GaN Market: Applications, Players, Technology and Substrates 2019, Market & Technology Report, (2019) [2] T. Kimoto, Jpn. J. Appl. Phys. 54, 40103 (2015). [3] Schmid, A.; Schröter, Ch.; Otto, R.; Schuster, M.; Klemm, V.; Rafaja, D.; Heitmann, J., Appl. Phys. Lett. 106, 053509 (2015) [4] Seidel, S., Schmid, A., Miersch, C., Schubert, J., Heitmann, J. Appl. Phys. Lett., 118(5), 052902 (2021) [5] P. Lagger, P. Steinschifter, M. Reiner, M. Stadtmüller, G. Denifl, A. Naumann, J. Müller, L. Wilde, J. Sundqvist, D. Pogany, C. Ostermaier, Appl. Phys. Lett. 105, 033412 (2014) [6] N Siebdrath, S. Seidel, A. Schmid, J. Heitmann, Mikro-Nano-Integration; 8th GMM-Workshop, 2020, pp. 1-3. [7] Garbe, V.; Schmid, A.; Seidel, S.; Abendroth, B; Stöcker, H.; Doering P.; Meyer, D.C.; Heitmann, J., Phys. Stat. Sol. (B), 2100312 (2021)