Relevant bibliographies by topics / GMM based scheme

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'GMM based scheme'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "GMM based scheme"

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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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Dissertations / Theses on the topic "GMM based scheme"

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Mapoka, Trust Tshepo. "Location based authenticated multi-services group key management for cyber security in high speed broadband wireless multicast communications : multi-service group key management scheme with location based handover authentication for multi-handoffs participating in multi-group service subscriptions, its performance evaluation and security correctness in high speed broadband wireless multicast communications." Thesis, University of Bradford, 2015. http://hdl.handle.net/10454/14468.

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Secure information exchanges over cyberspace is on the increase due to the convergence of wireless and mobile access technologies in all businesses. Accordingly, with the proliferation of diverse multicast group service subscriptions that are possible to co-exist within a single broadband network, there is also huge demand by the mobile subscribers to ubiquitously access these services over high speed broadband using their portable devices. Likewise, the Network Providers (NPs) invest hugely in infrastructure deployment to disseminate these services efficiently and concomitantly. Therefore, cyber security in any business is obligatory to restrict access of disseminated services to only authorised personnel. This becomes a vital requirement for a successful commercialisation of exchanged group services. The standard way to achieve cyber security in a wireless mobile multicast communication environment is through confidentiality using Group Key Management (GKM).The existing GKM schemes for secure wireless multicast from literature only target single group service confidentiality; however, the adoption of multiple group service confidentiality in them involve inefficient management of keys that induce huge performance overheads unbearable for real time computing. Therefore, a novel authenticated GKM scheme for multiple multicast group subscriptions known as slot based multiple group key management (SMGKM) is proposed. In the SMGKM, the handovers move across diverse decentralised clusters of homogeneous or heterogeneous wireless access network technologies while participating in multiple group service subscriptions. Unlike the conventional art, the SMGKM advances its security by integrating location based authentication and GKM functions. Both functions are securely offloaded from the Domain Key Distributor (DKD) to the intermediate cluster controllers, Area Key Distributors (AKDs), in a distributed fashion, using the proposed location based authenticated membership list (SKDL). A significant upgrade of fast handoff performance with reduced performance overheads of the SMGKM scheme is achieved. The developed numerical analysis and the simulation results display significant resource economy in terms of reduced rekeying transmission, communication bandwidth and storage overheads while providing enhanced security. The performance of the SMGKM in a high speed environment is also evaluated and has demonstrated that SMGKM outperforms the previous work. Finally, the SMGKM correctness against various attacks is verified using BAN logic, the eminent tool for analysing the widely deployed security protocols. The security analysis demonstrates that SMGKM can counteract the security flaws and redundancies identified in the chosen related art.
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Karthik, Girija Ramesan. "Binaural Source Localization using subband reliability and interaural time difference patterns." Thesis, 2018. https://etd.iisc.ac.in/handle/2005/5189.

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Machine localization of sound sources is necessary for a wide range of appli- cations, including human-robot interaction, surveillance and hearing aids. Robot sound localization algorithms have been proposed using microphone arrays with varied number of microphones. Adding more microphones helps increase the localization performance as more spatial cues can be obtained based on the number and arrangement of the microphones. However, hu- mans have an incredible ability to accurately localize and attend to target sound sources even in adverse noise conditions. The perceptual organi- zation of sounds in complex auditory scenes is done using various cues that help us group/segregate sounds. Among these, two major spatial cues are the Interaural time difference (ITD) and Interaural level/intensity difference(ILD/IID). Popular algorithms, for binaural source localization, model the distributions of ITD and ILD in each frequency subband us- ing Gaussian Mixture Models (GMMs) and perform likelihood integration across the time-frequency plane to estimate the direction of arrival (DoA) of the sources. In this thesis, we use ITDs and show that the localization performance of a GMM based scheme varies across subbands. We pro- pose subband selection and subband weighting schemes in order to exploit the subband reliability for localization. Source localization results demon- strate that the proposed schemes perform better than uniformly weighing all subbands. In particular, the best set of weights closely correspond to the case of selecting only the most reliable subband. We also propose a new binaural localization technique in which templates, that capture the direction-speci c interaural time di erence patterns, are used to localize sources. These templates are obtained using histograms of ITDs in each subband. DoA is estimated using a template matching scheme, which is experimentally found to perform better than the GMM based scheme.
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Hong, Cheng-Ru, and 洪承孺. "The GMD Based Precoding Scheme Design and Implementation for Closed-loop MIMO-OFDM Systems." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/94494383904461462019.

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碩士
國立中興大學
電機工程學系所
100
Due to the prosperous development of VLSI and wireless communication technology, the solution of Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems has become one of key technologies of wireless communications in recent years. The closed-loop MIMO-OFDM architecture is enhanced by employing precoding techniques, the channel state information at transmitter (CSIT) can be obtained via feedback from the receiver. Therefore, the scheme not only effectively improves performance of bit error rate (BER), but also can greatly reduce the complexity of the signal detector. The precoding techniques can be accomplished by applying matrix factorization methods such as singular value decomposition (SVD), geometric mean decomposition (GMD), and uniform channel decomposition (UCD). In this thesis, we present unified work, which combines QRD for signal detection and GMD for precoding techniques, into a unified design. It supports a MIMO system with the number of antennas upto 4 × 4. Two remarkable merits of this chip are that, first, it supports matrix factorizations with a constant throughput, and second, it reduces the computational complexity at both the algorithm level and the hardware level. In the algorithm aspect, we proposed a novel GMD computing scheme based on a divide-and-conquer approach. It not only avoids the operational convergence issues of the conventional SVD, but also alleviates the permutation operations required by the traditional GMD schemes. In addition, it can simultaneously achieve computational complexity reduction and computing parallelism improvement. According to the results of algorithm mapping, we evaluate various parallel, pipelined architectures to derive our hardware design. We further employ the low complexity coordinate rotations digital computers (CORDICs) design to simplify the arithmetic units. Moreover, various chip designs and implementation skills are introduced to boost the operating frequency and to lower the computational complexity. Implementation results for a 4 × 4 QRD / GMD chip in TSMC 90-nanometer CMOS process indicate that this chip design has a chip area of 3.29 mm2 and can compute a 4 × 4 QRD or 4 × 4 GMD every 4 cycles at a clock frequency of 125 MHz. The total power consumptions are 87.5 mW and 148.4 mW respectively in each mode. This design can provide a throughput of 31.25M matrix decompositions per second.
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Book chapters on the topic "GMM based scheme"

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Choi, Yoo-Joo, Yeon-Ju Lee, Jungho Yoon, Byung-Gook Lee, and Young J. Kim. "A New Class of Non-stationary Interpolatory Subdivision Schemes Based on Exponential Polynomials." In Geometric Modeling and Processing - GMP 2006, 563–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11802914_41.

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Löwner, Marc-Oliver. "New GML-Based Application Schema for Landforms, Processes and Their Interaction." In Landform - Structure, Evolution, Process Control, 21–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-75761-0_2.

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Jackson, Davina, and Richard Simpson. "Digital City: An Urban Perspective on Digital Earth." In Manual of Digital Earth, 527–63. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9915-3_16.

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Abstract Digital Earth and many other satellite and semiconductor-enabled cartography advances imply the need for a globally useful schema for more scientific and eco-ethical management of cities. How should we plan an internationally cohesive and locally effective system for understanding and managing urban stocks and flows around our planet? The answer to this question depends on new systems for managing geodata to underpin increasingly automated systems for evidence-based decision making. The current concept of Digital Earth as a “self-aware nervous system” is being advanced by urban proto-projects that are supported or followed by globally applicable initiatives including Singapore’s new Geospatial Masterplan, the International Standards Organization’s City Standards, Denmark’s Open Public Life Data Protocol, and the City-GML data model. These recent ventures are progressing a movement that extends far beyond the 1990s concepts of “smart cities” enabled by wireless telecommunications. In the Digital Earth science paradigm, cities must simulate their key situations and scenarios and analyze Earth observation data obtained via satellite-enabled devices that remotely detect and interpret all the light and radio waves of the electromagnetic spectrum.
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Al-Bahadili, Hussein, and Arafat Abu Mallouh. "Dynamic Channel Allocation in Cellular Communication Networks." In Utilizing Information Technology Systems Across Disciplines, 165–89. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-616-7.ch012.

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This chapter presents a description and performance evaluation of an efficient Distributed Artificial Intelligence (DAI) Dynamic Channels Allocation (DCA) scheme. Therefore, it is referred to as DAI-DCA scheme. It can be used for channel allocation in high traffic cellular communication networks (CCNs), such as the global system for mobile communication (GSM). The scheme utilizes a well-known DAI algorithm, namely, the asynchronous weak-commitment (AWC) algorithm, in which a complete solution is established by extensive communication among a group of neighboring collaborative cells forming a pattern, where each cell in the pattern uses a unique set of channels. To minimize communication overhead among cells, a token-based mechanism was introduced. The scheme achieved excellent average allocation efficiencies of over 85% for a number of realistic operation scenarios.
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Al-Bahadili, Hussein, and Arafat Abu Mallouh. "A Distributed Dynamic Channel Allocation Scheme in Cellular Communication Networks." In Networking and Telecommunications, 1648–60. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-986-1.ch106.

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This article presents a description and performance evaluation of an efficient distributed dynamic channels allocation (DDCA) scheme, which can be used for channel allocation in cellular communication networks (CCNs), such as the global system for mobile communication (GSM). The scheme utilizes a well-known distributed artificial intelligence (DAI) algorithm, namely, the asynchronous weak-commitment (AWC) algorithm, in which a complete solution is established by extensive communication among a group of neighbouring collaborative cells forming a pattern, where each cell in the pattern uses a unique set of channels. To minimize communication overhead among cells, a token-based mechanism was introduced. The scheme achieved excellent average allocation efficiencies of over 85% for a number of simulations.
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Bandopadhyay, Mandakinee, and Subrata Chattopadhyay. "Wireless Medicine Searching System Using GSM Modem in Smart City." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 151–67. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2584-5.ch009.

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With the development of mobile communication technologies and the popularity of relating devices, GSM network-based intelligent systems have been used more and more widely. Most existing intelligent systems have built on mobile platforms, but those systems don't provide any facility that could save time and energy. But people suffer from lack of time and energy to buy essential needs like medicine, etc. and they like to communicate to the supplier to get confirmation instantly before leaving home or office to collect the same. So, in society, it needs to give alignment without going on field. This chapter copes this problem using wireless database searching scheme using GSM technology, which is very useful in smart cities, where cell phone is an essential part of living. The system receives information from outsiders and customers through GSM modem database searches of all the suppliers connected in a common server and sends the result through short messages independently to the customer showing the availability.
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Zhang, Hui, Xin Pan, Haiwei Li, Jie Du, Qingxun Meng, and Gang Zhang. "Dynamic Continuous Online Compensation Method for Processing Robot Path Based on External Measurement." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220449.

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The absolute positioning accuracy of industrial robots is not in the high level to meet machining precision requirements. To improve the practical application requirements of industrial robots in the field of aerospace manufacturing, an online error compensation method based on the external Guided Motion (GEM) function of the milling robot is proposed in this paper. Using external measuring equipment, an external closed-loop control system of the robot is established, and the error compensation scheme is designed. The precision compensation of the robot’s end position is mainly studied. For the linear and circular motion of the robot, a continuous trajectory piecework compensation method is studied by using a PID control algorithm, which can measure the end position error online. The position errors of the robot are compensated simultaneously in the X, Y, and Z directions. Experiments show that the online error compensation method can improve the absolute accuracy of the robot end.
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Roßmann, Jürgen, Martin Hoppen, and Arno Bücken. "GML-Based Data Management and Semantic World Modelling for a 4D Forest Simulation and Information System." In Geospatial Intelligence, 423–42. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8054-6.ch020.

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Various types of 3D simulation applications benefit from realistic forest models. They range from flight simulators for entertainment to harvester simulators for training and tree growth simulations for research and planning. This paper's 4D forest simulation and information system integrates the necessary methods for data extraction, modelling and management. Using modern methods of semantic world modelling, tree data can efficiently be extracted from remote sensing data. The derived forest models contain position, height, crown volume, type and diameter of each tree. This data is modelled using GML-based data models to assure compatibility and exchangeability. ForestGML is the name of a new schema family developed to provide a common basis for forestry data. A flexible approach for database synchronization is used to manage the data and provide caching, persistence, a central communication hub for change distribution, and a versioning mechanism. Combining various simulation techniques and data versioning, the 4D forest simulation and information system can provide applications with “both directions” of the fourth dimension. This paper outlines the current state, new developments, and integration of tree extraction, data modelling, and data management. It also shows several applications realized with the system.
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Modarres, MohammadReza, and Miguel Almeida. "Application of the Computational Fluid Dynamics in Forest Fires Investigations for Mitigation of the Wildland-Urban Interface Fires’ Risks." In Advances in Forest Fire Research 2022, 533–38. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_83.

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Realistic modeling of the vegetation fires based on reliable data from laboratory experiments is a key factor in the prediction of the fire dynamics ‎behavior and its spread rate in wildlands. A robust understating of the fire behavior in different species can provide a pragmatic insight to take precautionary steps to mitigate the fire risks in Wildland-urban interfaces. Computational Fluid Dynamics (CFD) modeling of ‎wildland fires ‎offers a considerably high load of information needed for engineers and policymakers. This paper addresses the numerical modeling of common Ivy (Hedera helix) and grapevine ‎(Vitis)‎ plants using the fire dynamics ‎simulation for the fire behavior analysis. Other species which authors have conducted experiments are Acacia, Apple tree, Arizona cypress, Bay laurel (Laurus nobilis), Blueberry tree (Prunus Spinosa), Cherry Tree, Fig tree, Gum rockrose (Cistus ladanifer), Hydrangea, Kiwi tree, Leyland cypress, Lindens (Tilia), Loquat (Eriobotrya japonica), Nerium oleander, Olive tree, Pacific madrone (Arbutus menziesii), Rhus typhina (Anacardiaceae), The Holly (Ilex Aquifolium), Thuja occidentalis (white cedar), and Wild Blackberry (Rubus Ulmifolius) shrub, in alphabetical order. The corresponding mathematical modelings of these experiments are being carried out by the authors. The current numerical study was performed using the NIST open-source FDS 6.7.7 code, developed by ‎‎the National Institute of Standards and Technology (NIST) with specific emphasis on the heat release rate from fires in different types of indigenous plants common in the Mediterranean climate, especially in Portugal. The validations of the numerical results are realized based on the observations from the ‎experiments conducted at the Laboratório de Estudos Sobre Incêndios Florestais (LEIF) by the authors. The large-eddy ‎simulation (LES) is used in these sets of simulations to close the turbulence equations in the low-Mach regime. The 2nd order accurate finite difference approximation scheme is used to discretize the governing equations on uniformly spaced three-dimensional staggered grids. The flow obstructions are ‎treated using the simple immersed boundary method. Comparing the results of the FDS with those from the practical experiments, it is concluded that mathematical modeling of the vegetation fires can provide reasonably accurate results based on the fuel’s physical and chemical characteristics along with operating boundary conditions.
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Conference papers on the topic "GMM based scheme"

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Gulati, Nikhil, Rachel Greenstadt, Kapil R. Dandekar, and John M. Walsh. "GMM Based Semi-Supervised Learning for Channel-Based Authentication Scheme." In 2013 IEEE 78th Vehicular Technology Conference (VTC Fall). IEEE, 2013. http://dx.doi.org/10.1109/vtcfall.2013.6692216.

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Song, Yan, and Lirong Dai. "A Sample and Feature Selection Scheme for GMM-SVM Based Language Recognition." In 2008 6th International Symposium on Chinese Spoken Language Processing (ISCSLP). IEEE, 2008. http://dx.doi.org/10.1109/chinsl.2008.ecp.93.

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Kim, Wooil, Jun-Won Suh, and John H. L. Hansen. "An effective feature compensation scheme tightly matched with speech recognizer employing SVM-based GMM generation." In Interspeech 2010. ISCA: ISCA, 2010. http://dx.doi.org/10.21437/interspeech.2010-586.

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Chen, Mengjing, Weiran Shen, Pingzhong Tang, and Song Zuo. "Dispatching Through Pricing: Modeling Ride-Sharing and Designing Dynamic Prices." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/24.

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Over the past few years, ride-sharing has emerged as an effective way to relieve traffic congestion. A key problem for the ride-sharing platforms is to come up with a revenue-optimal (or GMV-optimal) pricing scheme and a vehicle dispatching policy that incorporate geographic and temporal information. In this paper, we aim to tackle this problem via an economic approach. Modeled naively, the underlying optimization problem may be non-convex and thus hard to solve. To this end, we use a so-called ``ironing'' technique to convert the problem into an equivalent convex optimization one via a clean Markov decision process (MDP) formulation, where the states are the driver distributions and the decision variables are the prices for each pair of locations. Our main finding is an efficient algorithm that computes the exact revenue-optimal (or GMV-optimal) randomized pricing scheme, which naturally induces the accompany vehicle dispatching policy. We also conduct empirical evaluations of our solution through real data of a major ride-sharing platform and show its advantages over fixed pricing schemes as well as several prevalent surge-based pricing schemes.
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Qiang, Deng, Xie Dong-liang, Hu Bo, Shi Yan, and Chen Shan-zhi. "An SMDP-based optimal admission control scheme in cognitive radio networks." In 2010 Global Mobile Congress (GMC). IEEE, 2010. http://dx.doi.org/10.1109/gmc.2010.5634619.

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Zhang, Zhengyu, and Ling Qiu. "A Hybrid ARQ scheme employing bit rearrangement based on low-order modulation." In 2010 Global Mobile Congress (GMC). IEEE, 2010. http://dx.doi.org/10.1109/gmc.2010.5634595.

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Liu, Qi, Jian Yuan, Xiuming Shan, Yue Wang, and Wei Su. "Dynamic load balance scheme based on mobility and service awareness in integrated 3G/WLAN networks." In 2010 Global Mobile Congress (GMC). IEEE, 2010. http://dx.doi.org/10.1109/gmc.2010.5634553.

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Miao, Lizhi, Shuliang Zhang, Guonian Lu, Xiaoli Gao, Donglai Jiao, and Jiayan Gan. "Parsing GML data based on integrative GML syntactic and semantic schemas database." In Geoinformatics 2007, edited by Jingming Chen and Yingxia Pu. SPIE, 2007. http://dx.doi.org/10.1117/12.761729.

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Wu, Suwen, and Jinkang Zhu. "A statistic channel information-based relay selection scheme in cooperative networks." In 2009 Global Mobile Congress. IEEE, 2009. http://dx.doi.org/10.1109/gmc.2009.5295859.

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Ren, Shuai, DeJun Mu, Tao Zhang, and Wei Hu. "Study of Reversible Information Hiding Scheme Based on GHM and CBP." In 2009 International Conference on Artificial Intelligence and Computational Intelligence. IEEE, 2009. http://dx.doi.org/10.1109/aici.2009.9.

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Reports on the topic "GMM based scheme"

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Bringué, M., R. A. Fensome, T. P. Poulton, J M Galloway, J. P. Bujak, M L Golding, M. J. Orchard, and G. L. Williams. The 2020 Canada datapack for TimeScale Creator: a new tool for Mesozoic - Cenozoic stratigraphy of the Canadian north. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/326099.

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The Geo-mapping for Energy and Minerals (GEM) program (2010-2020) provided a unique opportunity to advance the current level of understanding of the geological history of the Canadian North. In this contribution, based on the Trans-GEM Event Stratigraphy activity, a compilation of Mesozoic-Cenozoic stratigraphic data from across the GEM program regions and beyond is presented, with a focus on biostratigraphic events, using TimeScale Creator, a JAVA package that facilitates the compilation and comparison of large amounts of stratigraphic data while keeping track of changing absolute ages. The '2020 Canada datapack', which incorporates some information re-evaluated and refined from an earlier datapack, includes schemes using dinoflagellate cysts, spores and pollen, foraminifers and conodonts, and a new synthesis of Canadian Arctic Jurassic ammonite and Buchia bivalve biostratigraphy. This datapack will continue to be augmented after completion of the GEM program and will become a major tool in supporting an understanding of Canada's sedimentary basins, their resource potential and management.
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Murray, Trevor, and Timothy Jacobs. PR-457-16200-R01 Control of Vented Methane Emissions from Integral Compressor Engines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 2018. http://dx.doi.org/10.55274/r0011475.

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At natural gas pipeline compressor stations, methane emissions from compressor and engine crankcases are often vented directly into the atmosphere. There may be advantages to capturing these emissions and using them to offset fuel usage and / or decrease the overall carbon footprint of such a typical compressor station. This study evaluates the feasibility of directing such captured emissions into the intake of the compressor engine and subsequently combusting the methane emissions into carbon dioxide and water. Although seemingly an obvious or trivial solution, there are in fact several challenges and issues that must be considered to evaluate if such a scheme is a reasonable course of action for compressor station methane emissions reduction. The study relies on both extensive literature review and model-based engine simulations to determine the feasibility of rebreathing crankcase gases in pursuit of reducing compressor station methane emissions. The conclusions of the study are limited to the crankcase vent rebreathing into the air intake of large bore, natural gas, 2-stroke engines. The model-based engine simulations require detailed physical geometry of the subject engines as well as knowledge of basic engine operating parameters (e.g., fuel flow, air flow, and fuel composition). The simulation is based on the experimental facility located at Colorado State University, which is a 4-cylinder Cooper-Bessemer GMV-4. One of the important parameters needing to be known is the gas composition of both compressor and engine crankcases. It is extremely difficult to determine the composition of the engine crankcase gases, since the composition depends on a large variety of parameters. For this study, the gases from the compressor crankcase are modeled as methane (i.e., pipeline gas), and the gases from the engine crankcase are modeled as products of combustion with two different levels methane concentration (1500 ppm and 3000 ppm). A sensitivity analysis is performed, and the observed pressure traces from the model-based engine simulation show that the engine performance is not affected by the addition of rebreathed gases. This insensitivity mainly results from the very small rebreathed flow rates compared to the air intake, and the adjustments made on engine parameters, boost pressure and fuel injection rate, to keep trapped equivalence ratio (TER) and the energy delivery rate the same.
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