Journal articles: 'Primitive estimation'

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Hachiuma, Ryo, and Hideo Saito. "Pose Estimation of Primitive-Shaped Objects from a Depth Image Using Superquadric Representation." Applied Sciences 10, no. 16 (August 6, 2020): 5442. http://dx.doi.org/10.3390/app10165442.

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This paper presents a method for estimating the six Degrees of Freedom (6DoF) pose of texture-less primitive-shaped objects from depth images. As the conventional methods for object pose estimation require rich texture or geometric features to the target objects, these methods are not suitable for texture-less and geometrically simple shaped objects. In order to estimate the pose of the primitive-shaped object, the parameters that represent primitive shapes are estimated. However, these methods explicitly limit the number of types of primitive shapes that can be estimated. We employ superquadrics as a primitive shape representation that can represent various types of primitive shapes with only a few parameters. In order to estimate the superquadric parameters of primitive-shaped objects, the point cloud of the object must be segmented from a depth image. It is known that the parameter estimation is sensitive to outliers, which are caused by the miss-segmentation of the depth image. Therefore, we propose a novel estimation method for superquadric parameters that are robust to outliers. In the experiment, we constructed a dataset in which the person grasps and moves the primitive-shaped objects. The experimental results show that our estimation method outperformed three conventional methods and the baseline method.

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LI, Liang, Akira ASANO, Chie MURAKI ASANO, Mitsuji MUNEYASU, and Yoshiko HANADA. "Dual Primitive Estimation of Textures." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E94-A, no. 4 (2011): 1165–69. http://dx.doi.org/10.1587/transfun.e94.a.1165.

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Lee, Sukhan, Kyeong Dae Yoo, Jae Woong Kim, and Moon Ju Lee. "Surface Patch Primitive Based Object Modeling from CAD Data." Applied Mechanics and Materials 162 (March 2012): 179–83. http://dx.doi.org/10.4028/www.scientific.net/amm.162.179.

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For manufacturing automation, for instance, the robotic automation of automobile sub-assembly, CAD data serves as DB offering the geometric information of parts essential for robotic manipulation. However, a direct application of CAD for the robotic manipulation of parts may be of an issue, due to the fact that the particular format of the CAD data available, e.g., STL, does not directly provide certain geometric entities such as surface patch primitives and/or features that are required for robotic manipulation. In this paper, we present a novel method for extracting geometric primitives and/or features, such surface patch primitives as planar, cylindrical, conic, and spherical patches, from the STL format of CAD data, such that an industrial part/object can be represented as a logical sum of these surface patch primitives extracted. This surface patch primitive based modeling makes the automated reasoning involved in the recognition and pose estimation, as well as the grasp planning, of parts/objects easy to be done. The proposed method is applied to various CAD data samples for experimentation: the results demonstrate the reliability as well as the computational efficiency of the proposed method in the extraction of surface patch primitives.

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JENKINS, ODEST CHADWICKE, GERMÁN GONZÁLEZ SERRANO, and MATTHEW M. LOPER. "INTERACTIVE HUMAN POSE AND ACTION RECOGNITION USING DYNAMICAL MOTION PRIMITIVES." International Journal of Humanoid Robotics 04, no. 02 (June 2007): 365–85. http://dx.doi.org/10.1142/s0219843607001060.

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There is currently a division between real-world human performance and the decision making of socially interactive robots. This circumstance is partially due to the difficulty in estimating human cues, such as pose and gesture, from robot sensing. Towards bridging this division, we present a method for kinematic pose estimation and action recognition from monocular robot vision through the use of dynamical human motion vocabularies. Our notion of a motion vocabulary is comprised of movement primitives that structure a human's action space for decision making and predict human movement dynamics. Through prediction, such primitives can be used to both generate motor commands for specific actions and perceive humans performing those actions. In this paper, we focus specifically on the perception of human pose and performed actions using a known vocabulary of primitives. Given image observations over time, each primitive infers pose independently using its expected dynamics in the context of a particle filter. Pose estimates from a set of primitives inferencing in parallel are arbitrated to estimate the action being performed. The efficacy of our approach is demonstrated through interactive-time pose and action recognition over extended motion trials. Results evidence our approach requires small numbers of particles for tracking, is robust to unsegmented multi-action movement, movement speed, camera viewpoint and is able to recover from occlusions.

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Lavva, I., E. Hameiri, and I. Shimshoni. "Robust Methods for Geometric Primitive Recovery and Estimation From Range Images." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 38, no. 3 (June 2008): 826–45. http://dx.doi.org/10.1109/tsmcb.2008.918567.

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Jeon, Myung-Hwan, and Ayoung Kim. "PrimA6D: Rotational Primitive Reconstruction for Enhanced and Robust 6D Pose Estimation." IEEE Robotics and Automation Letters 5, no. 3 (July 2020): 4955–62. http://dx.doi.org/10.1109/lra.2020.3004322.

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Nicolescu, Monica, Odest Chadwicke Jenkins, Adam Olenderski, and Eric Fritzinger. "Learning behavior fusion from demonstration." Interaction Studies 9, no. 2 (May 26, 2008): 319–52. http://dx.doi.org/10.1075/is.9.2.09nic.

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A critical challenge in robot learning from demonstration is the ability to map the behavior of the trainer onto a robot’s existing repertoire of basic/primitive capabilities. In part, this problem is due to the fact that the observed behavior of the teacher may consist of a combination (or superposition) of the robot’s individual primitives. The problem becomes more complex when the task involves temporal sequences of goals. We introduce an autonomous control architecture that allows for learning of hierarchical task representations, in which: (1) every goal is achieved through a linear superposition (or fusion) of robot primitives and (2) sequencing across goals is achieved through arbitration. We treat learning of the appropriate superposition as a state estimation problem over the space of possible linear fusion weights, inferred through a particle filter. We validate our approach in both simulated and real world environments with a Pioneer 3DX mobile robot.

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Torii, Takuya, and Manabu Hashimoto. "Reliable Primitive Approximation for Estimation of Robot Grasping Parameters Using 3D-DNN." Electronic Imaging 2018, no. 9 (January 28, 2018): 301–1. http://dx.doi.org/10.2352/issn.2470-1173.2018.09.iriacv-301.

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Chen, Rongxin, Zongyue Wang, and Yuling Hong. "Pipelined XPath Query Based on Cost Optimization." Scientific Programming 2021 (May 27, 2021): 1–16. http://dx.doi.org/10.1155/2021/5559941.

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XPath query is the key part of XML data processing, and its performance is usually critical for XML applications. In the process of XPath query, there is inherent seriality between query steps, which makes it difficult to parallelize the query effectively as a whole. On the other hand, although XPath query has the characteristics of data stream processing and is suitable for pipeline processing, the data flow of each query step usually varies a lot, which results in limited performance under multithreading conditions. In this paper, we propose a pipelined XPath query method (PXQ) based on cost optimization. This method uses pipelined query primitives to process query steps based on relation index. During pipeline construction, a cost estimation model based on XML statistics is proposed to estimate the cost of the query primitive and provide guidance for the creation of a pipeline phase through the partition of query primitive sequence. The pipeline construction technique makes full use of available worker threads and optimizes the load balance between pipeline stages. The experimental results show that our method can adapt to the multithreaded environment and stream processing scenarios of XPath query, and its performance is better than the existing typical query methods based on data parallelism.

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Kumar, G. P., and U. K. Kumar. "Estimation of Gestational Age from Hand and Foot Length." Medicine, Science and the Law 34, no. 1 (January 1994): 48–50. http://dx.doi.org/10.1177/002580249403400106.

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Abortion, foeticide and infanticide have been practised from time immemorial by both primitive and civilized societies. Establishing the precise duration of gestation is an important point in the total medical evidentiary picture of infanticide. In this study, an attempt has been made to establish the gestational age of the foetus using foot and hand length. This study will be of help in establishing the gestational age when the foetus is fragmented. Results obtained were significant in establishing the gestational age.

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Barari, Ahmad, Hoda A. ElMaraghy, and George K. Knopf. "Search-Guided Sampling to Reduce Uncertainty of Minimum Deviation Zone Estimation." Journal of Computing and Information Science in Engineering 7, no. 4 (August 17, 2007): 360–71. http://dx.doi.org/10.1115/1.2798114.

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Integrating computational tasks in coordinate metrology and its effect on the inspection’s uncertainty is studied. It is shown that implementation of an integrated inspection system is crucial to reduce the uncertainty in minimum deviation zone (MDZ) estimation. An integrated inspection system based on the iterative search procedure and online MDZ estimation is presented. The search procedure uses the Parzen Windows technique to estimate the probability density function of the geometric deviations between the actual and substitute surfaces. The computed probability density function is used to recognize the critical points in the MDZ estimation and to identify portions of the surface that require further iterative measurements until the desired level of convergence is achieved. Reduction of the uncertainty in the MDZ estimation using the developed search method compared to the MDZ estimations using the traditional sampling methods is demonstrated by presenting experiments including both actual and virtual inspection data. The proposed search method can be used for assessing any geometric deviations when no prior assumptions about the fundamental form and distribution of the underlying manufacturing errors are required. The search method can be used to inspect and evaluate both primitive geometric features and complicated sculptured surfaces. Implementation of this method reduces inspection cost as well as the cost of rejecting good parts or accepting bad parts.

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Joe, Hyun-Min, Joonwoo Lee, and Jun-Ho Oh. "Dynamic Nonprehensile Manipulation of a Moving Object Using a Batting Primitive." Applied Sciences 11, no. 9 (April 26, 2021): 3920. http://dx.doi.org/10.3390/app11093920.

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To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved.

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Li, Qi, and Jeffrey M. Wooldridge. "SEMIPARAMETRIC ESTIMATION OF PARTIALLY LINEAR MODELS FOR DEPENDENT DATA WITH GENERATED REGRESSORS." Econometric Theory 18, no. 3 (May 15, 2002): 625–45. http://dx.doi.org/10.1017/s0266466602183034.

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In this paper we consider the problem of estimating a semiparametric partially linear model for dependent data with generated regressors. This type of model comes naturally from various econometric models such as a semiparametric rational expectation model when the surprise term enters the model nonparametrically, or a semiparametric type-3 Tobit model when the error distributions are of unknown forms, or a semiparametric error correction model. Using the nonparametric kernel method and under primitive conditions, we show that the [square root]n-consistent estimation results of the finite-dimensional parameter in a partially linear model can be generalized to the case of generated regressors with weakly dependent data. The regularity conditions we use are quite weak, and they are similar to those used in Robinson (1988, Econometrica 56, 931–954) for independent and observed data.

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Iqbal, Md Tauhid Bin, Mohammad Shoyaib, Byungyong Ryu, M. Abdullah-Al-Wadud, and Oksam Chae. "Directional Age-Primitive Pattern (DAPP) for Human Age Group Recognition and Age Estimation." IEEE Transactions on Information Forensics and Security 12, no. 11 (November 2017): 2505–17. http://dx.doi.org/10.1109/tifs.2017.2695456.

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Le, Thi Lan, Thanh Hai Tran, Hai Vu, Thuy Thi Nguyen, and Van Hung Le. "GCSAC: geometrical constraint sample consensus for primitive shapes estimation in 3D point cloud." International Journal of Computational Vision and Robotics 9, no. 4 (2019): 387. http://dx.doi.org/10.1504/ijcvr.2019.10022863.

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Le, Van Hung, Hai Vu, Thuy Thi Nguyen, Thi Lan Le, and Thanh Hai Tran. "GCSAC: geometrical constraint sample consensus for primitive shapes estimation in 3D point cloud." International Journal of Computational Vision and Robotics 9, no. 4 (2019): 387. http://dx.doi.org/10.1504/ijcvr.2019.101539.

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Liu, Yong, Jingya Zhao, Qinghua Zhu, and Yanqiu Wang. "An Improved Method for Parametric Spatial Spectrum Estimation in Internet of Things." Wireless Communications and Mobile Computing 2021 (May 5, 2021): 1–10. http://dx.doi.org/10.1155/2021/9976751.

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When massive numbers of wireless IoT devices are being deployed, cognitive spectrum management is critical to satisfy the explosive broadband requirements of IoT applications. Heterogeneous the target of the spatial spectrum estimation which is part of array signal processing is to achieve the evaluation of space signal parameters and source location, which result in that the spatial spectrum estimation becomes the most basic content of the array signal processing. It needs a method by which the large dimensional array still has its consistency. Therefore, this paper studies an improved large dimensional array parameterized spatial spectrum estimation method based on Pisarenko method, named G-Pisarenko method. Firstly, an improved estimator about the logarithm of the covariance matrix of a certain bilinear form is analyzed which is based on the theory of large dimension random matrix. We can find out a relatively better method, i.e., MW method. The method will become the primitive method for us to improve. Then, aimed at the relating covariance matrix in MW, we use an improved large dimensional array estimation method which can improve the logarithm of the covariance matrix estimation. Finally, we compare the improved method and the original method by simulation, and it can be seen the clear advantage of G-Pisarenko method when the sample number and observed dimensions are in the same order of magnitude.

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Wang, Guoyu, Zweitze Houkes, Guangrong Ji, Bing Zheng, and Xin Li. "An estimation-based approach for range image segmentation: on the reliability of primitive extraction." Pattern Recognition 36, no. 1 (January 2003): 157–69. http://dx.doi.org/10.1016/s0031-3203(02)00050-x.

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Janakiraman, Sengathir. "An enhanced hybrid Pareto metaheuritic algorithm-based multicast tree estimation for reliable multicast routing in VANETs." APTIKOM Journal on Computer Science and Information Technologies 3, no. 3 (January 23, 2020): 100–105. http://dx.doi.org/10.34306/csit.v3i3.82.

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Prompt and reliable data dissemination among the vehicular nodes of the network is indispensable as its mobility rate and limited coverage characteristics introduce the possibility of frequent topology changes. The effective and efficient sharing of critical information in the event of emergency necessitates either direct interaction or Road Side Units (RSUs)-based vehicular communication in the primitive place. Multicast routing is confirmed to be the significant scheme of data transfer since they establish reliable data dissemination between the source and destination vehicular nodes by estimating an optimal multicast tree. Moreover, QoS-constraint enforced meta-heuristic approaches are considered to be excellent for determining optimal multicast tree under multicasting. An Enhanced Hybrid Pareto Metaheuritic Algorithm-based Multicast Tree Estimation Scheme (EHPMA-MTES) is contributed for reliable multicast routing. The proposed EHPMA-MTES is confirmed to reduce the cost of transmission by 28% through the minimization of the multicast tree count formed during the process of multicast routing.

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Janakiraman, Sengathir. "An enhanced hybrid Pareto metaheuritic algorithm-based multicast tree estimation for reliable multicast routing in VANETs." APTIKOM Journal on Computer Science and Information Technologies 3, no. 3 (November 1, 2018): 100–105. http://dx.doi.org/10.11591/aptikom.j.csit.143.

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Prompt and reliable data dissemination among the vehicular nodes of the network is indispensable as its mobility rate and limited coverage characteristics introduce the possibility of frequent topology changes. The effective and efficient sharing of critical information in the event of emergency necessitates either direct interaction or Road Side Units (RSUs)-based vehicular communication in the primitive place. Multicast routing is confirmed to be the significant scheme of data transfer since they establish reliable data dissemination between the source and destination vehicular nodes by estimating an optimal multicast tree. Moreover, QoS-constraint enforced meta-heuristic approaches are considered to be excellent for determining optimal multicast tree under multicasting. An Enhanced Hybrid Pareto Metaheuritic Algorithm-based Multicast Tree Estimation Scheme (EHPMA-MTES) is contributed for reliable multicast routing. The proposed EHPMA-MTES is confirmed to reduce the cost of transmission by 28% through the minimization of the multicast tree count formed during the process of multicast routing.

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Celik, Ismail, and Gusheng Hu. "Single Grid Error Estimation Using Error Transport Equation." Journal of Fluids Engineering 126, no. 5 (September 1, 2004): 778–90. http://dx.doi.org/10.1115/1.1792254.

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This paper presents an approach to quantify the discretization error as well as other errors related to mesh size using the error transport equation (ETE) technique on a single grid computation. The goal is to develop a generalized algorithm that can be used in conjunction with computational fluid dynamics (CFD) codes to quantify the discretization error in a selected process variable. The focus is on applications where the conservation equations are solved for primitive variables, such as velocity, temperature and concentration, using finite difference and/or finite volume methods. An error transport equation (ETE) is formulated. A generalized source term for the ETE is proposed based on the Taylor series expansion and accessible influence coefficients in the discretized equation. Representative examples, i.e., one-dimensional convection diffusion equation, two-dimensional Poisson equation, two-dimensional convection diffusion equation, and non-linear one-dimensional Burger’s equation are presented to verify this method and elucidate its properties. Discussions are provided to address the significance and possible potential applications of this method to Navier-Stokes solvers.

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Zhou, Zhang, Chen, and Zhu. "Analyzing the Magnesium (Mg) Number of Olivine on the Lunar Surface and Its Geological Significance." Remote Sensing 11, no. 13 (June 28, 2019): 1544. http://dx.doi.org/10.3390/rs11131544.

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Olivine formation is directly related to Mg/Fe content. It is also significant in estimating the geological evolution of the moon. In this study, an estimation model of relative Mg number (Fo#) for lunar olivine was presented through multiple linear regression statistics. Sinus Iridum, the Copernicus Crater, and the pyroclastic deposit in the volcanic vents in the southeast of Orientale Basin were selected as the study areas. Olivine distribution was surveyed, and the relative Fo# calculation of olivine was implemented based on Moon Mineralogy Mapper (M3) data. Results demonstrated that olivine in the crater wall of Sinus Iridum and the Copernicus Crater had relatively high Fo#, which reflected the primitive melt. However, the difference in olivine spectral features between Sinus Iridum and the Copernicus Crater indicated different crystallization modes. The olivine in the pyroclastic deposit in the volcanic vents in the southwest of Orientale Basin also presented high Fo#, which indicated that the olivine was formed via rapid cooling crystallization and was accompanied by volcanic glass substances. As a result, the olivine relative Fo# calculated from the estimation model exhibited an important constraint implication for explanation of its causes.

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Tomita, Taketeru. "Mouth-Size Estimation of a Primitive Lamniform Shark,Protolamna: Low Trophic Position in Lamniform Shark Origin." Paleontological Research 15, no. 2 (June 2011): 68–76. http://dx.doi.org/10.2517/1342-8144-15.2.068.

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Ishikawa, Yuta, Ichiro Takeuchi, and Ryohei Nakano. "Multi-directional search from the primitive initial point for Gaussian mixture estimation using variational Bayes method." Neural Networks 23, no. 3 (April 2010): 356–64. http://dx.doi.org/10.1016/j.neunet.2009.08.003.

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Laurenza, Riccardo, Cosmo Lupo, Gaetana Spedalieri, Samuel L. Braunstein, and Stefano Pirandola. "Channel Simulation in Quantum Metrology." Quantum Measurements and Quantum Metrology 5, no. 1 (March 1, 2018): 1–12. http://dx.doi.org/10.1515/qmetro-2018-0001.

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Abstract In this review we discuss how channel simulation can be used to simplify the most general protocols of quantum parameter estimation, where unlimited entanglement and adaptive joint operations may be employed. Whenever the unknown parameter encoded in a quantum channel is completely transferred in an environmental program state simulating the channel, the optimal adaptive estimation cannot beat the standard quantum limit. In this setting, we elucidate the crucial role of quantum teleportation as a primitive operation which allows one to completely reduce adaptive protocols over suitable teleportation-covariant channels and derive matching upper and lower bounds for parameter estimation. For these channels,wemay express the quantum Cramér Rao bound directly in terms of their Choi matrices. Our review considers both discrete- and continuous-variable systems, also presenting some new results for bosonic Gaussian channels using an alternative sub-optimal simulation. It is an open problem to design simulations for quantum channels that achieve the Heisenberg limit.

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Mao Takongmo, Charles Olivier, and Dalibor Stevanovic. "Selection of the Number of Factors in Presence of Structural Instability: A Monte Carlo study." Articles 91, no. 1-2 (May 20, 2016): 177–233. http://dx.doi.org/10.7202/1036919ar.

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In this paper we study the selection of the number of primitive shocks in exact and approximate factor models in the presence of structural instability. The empirical analysis shows that the estimated number of factors varies substantially across several selection methods and over the last 30 years in standard large macroeconomic and financial panels. Using Monte Carlo simulations, we suggest that the structural instability, expressed as time-varying factor loadings, can alter the estimation of the number of factors and therefore provides an explanation for the empirical findings.

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Takama, Yasufumi, Takuya Tezuka, Hiroki Shibata, and Lieu-Hen Chen. "Estimation of Search Intents from Query to Context Search Engine." Journal of Advanced Computational Intelligence and Intelligent Informatics 24, no. 3 (May 20, 2020): 316–25. http://dx.doi.org/10.20965/jaciii.2020.p0316.

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This paper estimates users’ search intents when using the context search engine (CSE) by analyzing submitted queries. Recently, due to the increase in the amount of information on the Web and the diversification of information needs, the gap between user’s information needs and a basic search function provided by existing web search engines becomes larger. As a solution to this problem, the CSE that limits its tasks to answer questions about temporal trends has been proposed. It provides three primitive search functions, which users can use in accordance with their purposes. Furthermore, if the system can estimate users’ search intents, it can provide more user-friendly services that contribute the improvement of search efficiency. Aiming at estimating users’ search intents only from submitted queries, this paper analyzes the characteristics of queries in terms of typical search intents when using CSE, and defines classification rules. To show the potential use of the estimated search intents, this paper introduces a learning to rank into CSE. Experimental results show that MAP (mean average precision) is improved by learning rank models separately for different search intents.

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Giacovazzo, Carmelo, Dritan Siliqi, and Cristina Fernández-Castaño. "The joint probability distribution function of structure factors with rational indices. IV. The P1 case." Acta Crystallographica Section A Foundations of Crystallography 55, no. 3 (May 1, 1999): 512–24. http://dx.doi.org/10.1107/s0108767398014792.

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The method of the joint probability distribution functions of structure factors has been extended to reflections with rational indices. The most general case, space group P1, has been considered. The positional parameters are the primitive random variables of our probabilistic approach, while the reflection indices are kept fixed. Quite general joint probability distributions have been considered from which conditional distributions have been derived: these proved applicable to the accurate estimation of the real and imaginary parts of a structure factor, given prior information on other structure factors. The method is also discussed in relation to the Hilbert-transform techniques.

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Haley, Patrick J., and Pierre F. J. Lermusiaux. "Multiscale two-way embedding schemes for free-surface primitive equations in the “Multidisciplinary Simulation, Estimation and Assimilation System”." Ocean Dynamics 60, no. 6 (November 11, 2010): 1497–537. http://dx.doi.org/10.1007/s10236-010-0349-4.

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Nekrylov, N., A. A. Korneeva, D. P. Savelyev, and T. N. Antsiferova. "Variations of Source Composition and Melting Degrees of Olivine-Phyric Rocks from Kamchatsky Mys: Results of Geochemical Modeling of Trace Element Contents in Melts." Petrology 29, no. 1 (January 2021): 14–23. http://dx.doi.org/10.1134/s0869591121010045.

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Abstract We conducted the geochemical modeling of trace element contents for primary melts of olivine-phyric rocks from Kamchatsky Mys. This modeling reveals substantial chemical heterogeneity of their source while the average source composition is close to the enriched DMM (E-DMM). The average estimation of the melting degree is in the range from 9.1 ± 3.8% for the model of modal batch melting to 15.4 ± 5.2% for the model of accumulated fractional melting, which is slightly higher than the estimation for primitive mid-ocean ridge basalt (MORB) glasses (7.4 ± 2.2% and 12.5 ± 3.8% respectively). It is in a good agreement with high melting degrees estimated earlier for other rocks of the Kamchatsky Mys ophiolites. Low pressure of mantle melting caused by the elevated speed of decompression relative to the average MORB could explain elevated melting degrees estimated for Kamhcatsky Mys ophiolites as well as their characteristic Sr-anomalies and sulfide saturation on the earliest stages of magmatic evolution.

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Nakagawa, M., K. Akano, T. Kobayashi, and Y. Sekiguchi. "RELATIVE PANORAMIC CAMERA POSITION ESTIMATION FOR IMAGE-BASED VIRTUAL REALITY NETWORKS IN INDOOR ENVIRONMENTS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W4 (September 14, 2017): 349–54. http://dx.doi.org/10.5194/isprs-annals-iv-2-w4-349-2017.

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Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.

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Annan, J. D., D. J. Lunt, J. C. Hargreaves, and P. J. Valdes. "Parameter estimation in an atmospheric GCM using the Ensemble Kalman Filter." Nonlinear Processes in Geophysics 12, no. 3 (February 25, 2005): 363–71. http://dx.doi.org/10.5194/npg-12-363-2005.

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Abstract. We demonstrate the application of an efficient multivariate probabilistic parameter estimation method to a spectral primitive equation atmospheric GCM. The method, which is based on the Ensemble Kalman Filter, is effective at tuning the surface air temperature climatology of the model to both identical twin data and reanalysis data. When 5 parameters were simultaneously tuned to fit the model to reanalysis data, the model errors were reduced by around 35% compared to those given by the default parameter values. However, the precipitation field proved to be insensitive to these parameters and remains rather poor. The model is computationally cheap but chaotic and otherwise realistic, and the success of these experiments suggests that this method should be capable of tuning more sophisticated models, in particular for the purposes of climate hindcasting and prediction. Furthermore, the method is shown to be useful in determining structural deficiencies in the model which can not be improved by tuning, and so can be a useful tool to guide model development. The work presented here is for a limited set of parameters and data, but the scalability of the method is such that it could easily be extended to a more comprehensive parameter set given sufficient observational data to constrain them.

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Johnson, G. David, Hitoshi Ida, Jiro Sakaue, Tetsuya Sado, Takashi Asahida, and Masaki Miya. "A ‘living fossil’ eel (Anguilliformes: Protanguillidae, fam. nov.) from an undersea cave in Palau." Proceedings of the Royal Society B: Biological Sciences 279, no. 1730 (August 17, 2011): 934–43. http://dx.doi.org/10.1098/rspb.2011.1289.

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We report the discovery of an enigmatic, small eel-like fish from a 35 m-deep fringing-reef cave in the western Pacific Ocean Republic of Palau that exhibits an unusual suite of morphological characters. Many of these uniquely characterize the Recent members of the 19 families comprising the elopomorph order Anguilliformes, the true eels. Others are found among anguilliforms only in the Cretaceous fossils, and still others are primitive with respect to both Recent and fossil eels. Thus, morphological evidence explicitly places it as the most basal lineage (i.e. the sister group of extant anguilliforms). Phylogenetic analysis and divergence time estimation based on whole mitogenome sequences from various actinopterygians, including representatives of all eel families, demonstrate that this fish represents one of the most basal, independent lineages of the true eels, with a long evolutionary history comparable to that of the entire Anguilliformes (approx. 200 Myr). Such a long, independent evolutionary history dating back to the early Mesozoic and a retention of primitive morphological features (e.g. the presence of a premaxilla, metapterygoid, free symplectic, gill rakers, pseudobranch and distinct caudal fin rays) warrant recognition of this species as a ‘living fossil’ of the true eels, herein described as Protanguilla palau genus et species nov. in the new family Protanguillidae.

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NOGUCHI, Tatsuya, and Hiromitsu FUJII. "Position and Posture Estimation of Primitive Shapes Using Deep Learning-Based Object Extraction and Point Cloud-Based Face Extraction." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2020 (2020): 2P1—N13. http://dx.doi.org/10.1299/jsmermd.2020.2p1-n13.

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Dick, Miri, and Shaul Hochstein. "Interactions in the Discrimination and Absolute Judgement of Orientation and Length." Perception 17, no. 2 (April 1988): 177–89. http://dx.doi.org/10.1068/p170177.

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An asymmetric model is described for interactions in the perception of two dimensions (length and orientation) of a single visual stimulus. Two methods were used to test these interactions, and models for the interpretation of the possible outcomes of these tests are discussed. A length discrimination task showed facilitation (decreased reaction time) when orientation was covaried with length, and interference (increased reaction time) when random orientation variation was introduced. A smaller effect was seen when length was varied in an orientation discrimination task in a correlated or random fashion. Analysis of sequential effects showed that reaction times are fastest on repetition trials and are slowed by either the need to change the response or the need for additional sensory processing. With the second method, it was found that the amount of information transmitted in the estimation of orientation was not affected by the introduction of the redundant dimension of length, but that there was a significant gain in the amount of information transmitted in the estimation of length by the addition of the redundant dimension of orientation. It is concluded that orientation is probably a perceptual primitive of the visual system whereas length is a computed variable.

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Peng, Xian, Yun’er Chen, Tao Wang, Lei Ding, and Xiaodan Tan. "Noise Attenuation Estimation for Maximum Length Sequences in Deconvolution Process of Auditory Evoked Potentials." Computational and Mathematical Methods in Medicine 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/3927486.

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The use of maximum length sequence (m-sequence) has been found beneficial for recovering both linear and nonlinear components at rapid stimulation. Since m-sequence is fully characterized by a primitive polynomial of different orders, the selection of polynomial order can be problematic in practice. Usually, the m-sequence is repetitively delivered in a looped fashion. Ensemble averaging is carried out as the first step and followed by the cross-correlation analysis to deconvolve linear/nonlinear responses. According to the classical noise reduction property based on additive noise model, theoretical equations have been derived in measuring noise attenuation ratios (NARs) after the averaging and correlation processes in the present study. A computer simulation experiment was conducted to test the derived equations, and a nonlinear deconvolution experiment was also conducted using order 7 and 9 m-sequences to address this issue with real data. Both theoretical and experimental results show that the NAR is essentially independent of the m-sequence order and is decided by the total length of valid data, as well as stimulation rate. The present study offers a guideline for m-sequence selections, which can be used to estimate required recording time and signal-to-noise ratio in designing m-sequence experiments.

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Praet, A., M. A. Barucci, P. H. Hasselmann, K. Kitazato, T. Iwata, M. Matsuoka, D. Domingue, and B. E. Clark. "Hydrogen abundance estimation model and application to (162173) Ryugu." Astronomy & Astrophysics 649 (May 2021): L16. http://dx.doi.org/10.1051/0004-6361/202140900.

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Context. The JAXA asteroid sample return mission Hayabusa2 acquired a huge quantity of data from the asteroid (162173) Ryugu during its 1.5 years in asteroid proximity orbit. On December 5, 2020 (Japan time), Hayabusa brought back to Earth a 5.4 g sample from Ryugu’s surface. Aims. We analyzed the near-infrared spectra of Ryugu, in particular the band at 2.72 μm, with the aim to investigate the hydrogen content of the H2O and OH− groups in hydrated phyllosilicates on Ryugu’s surface. Aims. We applied two different methods, normalized optical path length (NOPL) and effective single-particle absorption thickness (ESPAT), to the 3 μm region absorption band, and we compared the obtained spectral parameters with those obtained from carbonaceous chondrite meteorites whose H content was determined in the laboratory. Methods. We derived an exponential correlation between the selected meteorite H content and its respective ESPAT and NOPL parameters. The average value of the H content obtained on Ryugu’s surface with its relative variations, combining the results obtained with the two methods, is 0.52−0.21+0.16 wt.%. These methods can be applied to other asteroids that exhibit a 3 μm region absorption band to estimate the mean average of H content. Results. The results of the ESPAT and NOPL methods used on the Ryugu spectral data present small variations across Ryugu’s surface and do not show any evident relation with the surface geomorphological structures. Our estimation of the global average H content of Ryugu is in agreement with those of several aqueously altered carbonaceous chondrites measured in the laboratory and is most similar to the H content of heated CM. The study of phyllosilicate H2O and OH− group hydrogen content on Ryugu and the derived method may be applied to other observed primitive asteroids. The obtained results will allow Solar System evolution models to be constrained and will allow the formation and evolution of the Solar System to be better understood.

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Anzian, Kouadio Fabrice, Mykhailo Illich Fyk, Al-Sultan Mohammed Bassam, Mohammed Khaleel Abbood, Haval Mohammed Abdullatif, and Yevhen Alexender Shapchenko. "Analysis of Dynamical Heat Conductivity of the Reservoir and Fluid Evacuation Zone on the Gas Condensate Well Flow Rate." J — Multidisciplinary Scientific Journal 3, no. 1 (March 14, 2020): 124–37. http://dx.doi.org/10.3390/j3010011.

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This study shows that the thermal conductivity of the rock borehole adjacent to the wells varies depending on the operation of the well. This is due to the fact that the actual temperature and temperature difference affect the humidity and other thermal properties of the rocks, which in turn affect the heat transfer coefficient across the section between the moving gas and the rocks. The static temperature field of primitive geothermal gradients acquires changes in a dynamic form. Theoretical consideration of changes in the thermal conductivity of rocks near the face and the wells is proposed to improve the prediction of gas condensate wells production. The result is achieved by introducing the specified equations of the thermal energy balance in the radial filtration and lifting of well products, which contain the coefficients of heat exchange and throttling. The refinement bias estimation of the 10%–15% level of gas condensate well extraction is shown using proposed methodological approach to relatively well-known (traditional in the field development practice) methods for estimating the extraction of a “medium well” from a particular oil and gas field evaluation. The results of this work demonstrate important scientific, applied, educational and methodological significance of using the methodology presented by the authors.

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Menichini, Amilcar. "On the determinants of firm leverage: evidence from a structural estimation." International Journal of Managerial Finance 11, no. 2 (April 7, 2015): 179–97. http://dx.doi.org/10.1108/ijmf-04-2014-0054.

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Purpose – The purpose of this paper is to investigate the phenomena of convergence and stability of leverage reported by Lemmon et al. (2008). Design/methodology/approach – A dynamic trade-off model of the firm was used to simulate investment, leverage, and payout decisions for different types of firms. From an econometric standpoint, the Efficient Method of Moments was used to recover the structural parameters. Findings – The structural model generates a leverage ratio that oscillates around a long-run, time-invariant level and consistently reproduces the convergence and stability of leverage reported by Lemmon et al. (2008). The model also suggests the causes of those observed properties of the data. That is, convergence is due to the mean-reversion of profits while stability is due to the different fundamental characteristics (e.g. capital elasticity, volatility of profits, etc.) of the firm. Practical implications – Determining the optimal capital structure of a firm is a complex problem that has challenged academics and practitioners for a long time. Understanding leverage decisions is of great importance not only for financial managers, but also for investors, such as banks, debt-holders, equity-holders, and other capital providers, who need to understand how firms make capital structure decisions in order to achieve an efficient allocation of funds. Originality/value – The author shows that the firm-specific fixed effects in leverage regressions are not related to the usual determinants (e.g. profitability, market-to-book ratio), but to the primitive characteristics of the firm (e.g. elasticity of capital in the production function, the volatility of profits, the capital depreciation rate, the income tax rate, etc.)

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Wang, Qiying, and Peter C. B. Phillips. "NONPARAMETRIC COINTEGRATING REGRESSION WITH ENDOGENEITY AND LONG MEMORY." Econometric Theory 32, no. 2 (December 18, 2014): 359–401. http://dx.doi.org/10.1017/s0266466614000917.

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This paper explores nonparametric estimation, inference, and specification testing in a nonlinear cointegrating regression model where the structural equation errors are serially dependent and where the regressor is endogenous and may be driven by long memory innovations. Generalizing earlier results of Wang and Phillips (2009a,b,Econometric Theory25, 710–738,Econometrica77, 1901–1948), the conventional nonparametric local level kernel estimator is shown to be consistent and asymptotically (mixed) normal in these cases, thereby opening up inference by conventional nonparametric methods to a wide class of potentially nonlinear cointegrated relations. New results on the consistency of parametric estimates in nonlinear cointegrating regressions are provided, extending earlier research on parametric nonlinear regression and providing primitive conditions for parametric model testing. A model specification test is studied and confirmed to provide a valid mechanism for testing parametric specifications that is robust to endogeneity. But under long memory innovations the test is not pivotal, its convergence rate is parameter dependent, and its limit theory involves the local time of fractional Brownian motion. Simulation results show good performance for the nonparametric kernel estimates in cases of strong endogeneity and long memory, whereas the specification test is shown to be sensitive to the presence of long memory innovations, as predicted by asymptotic theory.

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UNNIKRISHNAN, RANJITH, JEAN-FRANÇOIS LALONDE, NICOLAS VANDAPEL, and MARTIAL HEBERT. "SCALE SELECTION FOR GEOMETRIC FITTING IN NOISY POINT CLOUDS." International Journal of Computational Geometry & Applications 20, no. 05 (October 2010): 543–75. http://dx.doi.org/10.1142/s0218195910003438.

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In recent years, there has been a resurgence in the use of raw point cloud data as the geometric primitive of choice for several modeling tasks such as rendering, editing and compression. Algorithms using this representation often require reliable additional information such as the curve tangent or surface normal at each point. Estimation of these quantities requires the selection of an appropriate scale of analysis to accommodate sensor noise, density variation and sparsity in the data. To this goal, we present a new class of locally semi-parametric estimators that allows analysis of accuracy with finite samples, as well as explicitly addresses the problem of selecting optimal support volume for local fitting. Experiments on synthetic and real data validate the behavior predicted by the model, and show competitive performance and improved stability over leading alternatives that require a preset scale.

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Hemami, Hooshang, and Bostwick F. Wyman. "Rigid Body Dynamics, Constraints, and Inverses." Journal of Applied Mechanics 74, no. 1 (December 19, 2005): 47–56. http://dx.doi.org/10.1115/1.2178359.

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Rigid body dynamics are traditionally formulated by Lagrangian or Newton-Euler methods. A particular state space form using Euler angles and angular velocities expressed in the body coordinate system is employed here to address constrained rigid body dynamics. We study gliding and rolling, and we develop inverse systems for estimation of internal and contact forces of constraint. A primitive approximation of biped locomotion serves as a motivation for this work. A class of constraints is formulated in this state space. Rolling and gliding are common in contact sports, in interaction of humans and robots with their environment where one surface makes contact with another surface, and at skeletal joints in living systems. This formulation of constraints is important for control purposes. The estimation of applied and constraint forces and torques at the joints of natural and robotic systems is a challenge. Direct and indirect measurement methods involving a combination of kinematic data and computation are discussed. The basic methodology is developed for one single rigid body for simplicity, brevity, and precision. Computer simulations are presented to demonstrate the feasibility and effectiveness of the approaches presented. The methodology can be applied to a multilink model of bipedal systems where natural and/or artificial connectors and actuators are modeled. Estimation of the forces is accomplished by the inverse of the nonlinear plant designed by using a robust high gain feedback system. The inverse is shown to be stable, and bounds on the tracking error are developed. Lyapunov stability methods are used to establish global stability of the inverse system.

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Gangadhara Rao, K., Vijayakumari Rodda, and B. Basaveswara Rao. "Qualitative Analysis of Recognition-based Graphical Password Authentication Schemes for Accessing the Cloud." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 2 (August 1, 2017): 507. http://dx.doi.org/10.11591/ijeecs.v7.i2.pp507-513.

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<p>Cloud computing is increasingly becoming popular as many enterprise applications and data are moving into cloud platforms. However, a major barrier for cloud application is real and perceived lack of security. There are many security mechanisms exercised to utilize cloud services. Amongst them the prominent and primitive security mechanism is the Authentication System. Traditional text based passwords are susceptible to threats. Tough passwords are hard to recall and easily recalled passwords are simple and predictable. Graphical passwords are introduced as the better alternative. Two types of graphical passwords are there – recall based and recognition based. This research reviews several Recognition-Based Graphical Password methods and analyses their security based on the estimation criteria. Moreover, the research defines a metric called a 14-point scale that would make it possible for the qualitative analysis of the graphical passwords schemes. </p>

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Quadros, Regis Sperotto de, Fabrício Pereira Harter, Daniela Buske, and Larri Silveira Pereira. "DATA ASSIMILATION BY ENSEMBLE KALMAN FILTER WITH THE LORENZ EQUATIONS." Ciência e Natura 38 (July 20, 2016): 190. http://dx.doi.org/10.5902/2179460x20158.

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Data Assimilation is a procedure to get the initial condition as accurately as possible, through the statistical combination of collected observations and a background field, usually a short-range forecast. In this research a complete assimilation system for the Lorenz equations based on Ensemble Kalman Filter is presented and examined. The Lorenz model is chosen for its simplicity in structure and the dynamic similarities with primitive equations models, such as modern numerical weather forecasting. Based on results, was concluded that, in this implementation, 10 members is the best setting, because there is an overfitting for ensembles with 50 and 100 members. It was also examined if the EnKF is effective to track the control for 20% and 40% of error in the initial conditions. The results show a disagreement between the “truth” and the estimation, especially in the end of integration period, due the chaotic nature of the system. It was also concluded that EnKF have to be performed sufficiently frequently in order to produce desirable results.

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Han, Xu-Wang, Hai-Tao Zheng, Jin-Yuan Chen, and Cong-Zhi Zhao. "Diverse Decoding for Abstractive Document Summarization." Applied Sciences 9, no. 3 (January 23, 2019): 386. http://dx.doi.org/10.3390/app9030386.

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Recently, neural sequence-to-sequence models have made impressive progress in abstractive document summarization. Unfortunately, as neural abstractive summarization research is in a primitive stage, the performance of these models is still far from ideal. In this paper, we propose a novel method called Neural Abstractive Summarization with Diverse Decoding (NASDD). This method augments the standard attentional sequence-to-sequence model in two aspects. First, we introduce a diversity-promoting beam search approach in the decoding process, which alleviates the serious diversity issue caused by standard beam search and hence increases the possibility of generating summary sequences that are more informative. Second, we creatively utilize the attention mechanism combined with the key information of the input document as an estimation of the salient information coverage, which aids in finding the optimal summary sequence. We carry out the experimental evaluation with state-of-the-art methods on the CNN/Daily Mail summarization dataset, and the results demonstrate the superiority of our proposed method.

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Liu, Xingye, Jingye Li, Xiaohong Chen, Lin Zhou, and Kangkang Guo. "Bayesian discriminant analysis of lithofacies integrate the Fisher transformation and the kernel function estimation." Interpretation 5, no. 2 (May 31, 2017): SE1—SE10. http://dx.doi.org/10.1190/int-2016-0025.1.

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The accurate identification of lithofacies is indispensable for reservoir parameter prediction. In recent years, the application of multivariate statistical methods has gained more and more attention in petroleum geology. In terms of the identification for lithofacies, the commonly used multivariate statistical methods include discriminant analysis and cluster analysis. Fisher and Bayesian discriminant analyses are two different discriminant analysis methods, which include intrinsic advantages and disadvantages. Given the discriminant efficiency of different methods, calculation cost, difficulty in the degree of determining the parameters, and the ability to analyze statistical characteristics of data, we put forward a new method combined with seismic information to classify reservoir lithologies and pore fluids. This method integrates the advantages of Fisher discrimination, the kernel function, and Bayesian discrimination. First, we analyze training data and search a projection direction. Then, data are transformed through Fisher transformation according to this direction and different kinds of facies can be distinguished more efficiently by exploiting transformed data than by using primitive data. Subsequently, using the kernel function estimates the conditional probability density function of the transformed variable. A classifier is constructed based on Bayesian theory. Then, the pending data are input to the classifier and the solution whose posteriori probability reaches the maximum is extracted as the predicted result at each grid node. An a posteriori probability distribution of predicted lithofacies can be acquired as well, from which interpreters can evaluate the uncertainty of the results. The ultimate goal of this study is to provide a novel and efficient lithofacies discriminant method. Tests on model and field data indicate that our method can obtain more accurate identification results with less uncertainty compared with conventional Fisher approaches and Bayesian methods.

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Masaki, Y., N. Hanasaki, K. Takahashi, and Y. Hijioka. "Propagation of biases in humidity in the estimation of global irrigational water." Earth System Dynamics Discussions 6, no. 1 (January 26, 2015): 81–132. http://dx.doi.org/10.5194/esdd-6-81-2015.

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Abstract. Future projections on irrigational water under a changing climate are highly dependent on meteorological data derived from general circulation models (GCMs). Since climate projections include biases, bias correction is widely used to adjust meteorological elements, such as the atmospheric temperature and precipitation, but less attention has been paid to biases in humidity. Hence, in many cases, raw GCM outputs have been directly used to analyze the impact of future climate change. In this study, we examined how the biases remaining in the humidity data of five GCMs propagate into the estimation of irrigational water demand and abstraction from rivers using the global hydrological model (GHM) H08. First, to determine the effects of humidity bias across GCMs, we used meteorological data sets to which a state-of-the-art bias correction method was applied except to the humidity. Uncorrected GCM outputs were used for the humidity. We found that differences in the monthly relative humidity of 11.7 to 20.4% RH (percent used as the unit of relative humidity) from observations across the GCMs caused the estimated irrigational water abstraction from rivers to range between 1217.7 and 1341.3 km3 yr−1 for 1971–2000. Differences in humidity also propagate into future projections. Second, sensitivity analysis with hypothetical humidity biases of ±5% RH added homogeneously worldwide revealed the large negative sensitivity of irrigational water abstraction in India and East China, which have high areal fractions of irrigated cropland. Third, we performed another set of simulations with bias-corrected humidity data to examine whether bias correction of the humidity can reduce uncertainties in irrigational water across the GCMs. The results showed that bias correction, even with a primitive methodology that only adjusts the monthly climatological relative humidity, helped reduce uncertainties across the GCMs. Although the GHMs have different sensitivities to atmospheric humidity because of the implementation of different types of potential evapotranspiration formulae, bias correction of the humidity should be included in hydrological analysis, particularly for the evaluation of evapotranspiration and irrigational water.

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Masouleh, Seyedeh Somayyeh Shafiei, and Jalal Javadi Moghaddam. "Evaluation of open-pollinated offspring in Cyclamen persicum using vegetative phenology models in a primitive breeding population." Ornamental Horticulture 27, no. 1 (March 2021): 49–59. http://dx.doi.org/10.1590/2447-536x.v27i1.2148.

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Abstract Cyclamen is commercially cultivated to produce the pot and garden flowering plants by sowing the seeds, and the number of leaves is an important trait for the beginning of the initiations of flower buds and flowering. The yield potential is affected by the life cycle of a plant and the plant breeders can have good decisions making with the prediction of plant phenology. In this study, a polynomial function was proposed for modeling behavior of cyclamen offspring during the vegetative growth. This modeling is based on information on environmental changes and plant morphology up to the flowering stage. For this purpose, 30 pots (individuals) from a 121-individual population, which were the same in the size, were considered for sampling of data. The data were recorded as time series that include temperature (°C), relative humidity (%), leaf width (mm) and number of leaves. The output of this model is the number of leaves and the recorded inputs are the time (growth cycle; days), temperature, relative humidity and leaf width. Using the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm, the constant coefficients of the proposed function (linear model) was calculated to match the input and output values to each other. To illustrate the robustness and efficiency of model, the growth rates of all individuals were compared using this proposed model. The result of root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R 2 ) between the estimated and observed values for each individual showed that 63% of the tested open-pollinated (OP) population is marketable. Therefore, phenology model could be a good estimation of the vigor of the OP population for commercial production. It should be noted that in obtaining the model, only five individuals were used randomly as training data, and the obtained model was fitted to the others as test dataset without changing the coefficients. Furthermore, a Gaussian model of the whole dataset showed that the OP seeds of cyclamen could be utilized to produce the potted flowering cyclamen without any worry about non-uniformity of harvest for the market if the optimum temperature would be adjusted.

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Tobelko, D. P., M. V. Portnyagin, S. P. Krasheninnikov, E. N. Grib, and P. Yu Plechov. "Compositions and formation conditions of primitive magmas of the Karymsky volcanic center, Kamchatka: evidence from melt inclusions and trace-element thermobarometry." Петрология 27, no. 3 (May 19, 2019): 258–81. http://dx.doi.org/10.31857/s0869-5903273258-281.

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This paper reports the results of a study of naturally and experimentally quenched melt inclusions in magnesian olivine (Fo77–89) from a basalt sample from the Karymsky volcanic center, which is located in the middle segment of the Eastern Volcanic Front of Kamchatka. The conditions of parental magma formation were estimated using modern methods of trace-element thermometry. Based on direct H2O measurements in inclusions and thermometry of coexisting olivine and spinel, it was shown that the parent melts contained at least 4.5 wt % H2O and crystallized at a temperature of 1114 ± 27°C and an oxygen fugacity of DQFM = 1.5 ± 0.4. The obtained estimates of H2O content and crystallization temperature are among the first and currently most reliable data for the Eastern Volcanic Front of Kamchatka. The primary melt of the Karymsky volcanic center was derived from peridotitic material and could be produced by ~12–17% melting of an enriched MORB source (E-DMM) at ~1230–1250°C and ~1.5 GPa. Our estimates of mantle melting temperature beneath Kamchatka are slightly lower than values reported previously and up to 50°C lower than the dry peridotite solidus, which indicates the influence of a slab-derived hydrous melt. The combined approach to the estimation of the initial H2O content of melt employed in this study can provide a more reliable data in future investigations, and its application will probably to decrease the existing temperature estimates for the mantle wedge above subduction zones.

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Masaki, Y., N. Hanasaki, K. Takahashi, and Y. Hijioka. "Propagation of biases in humidity in the estimation of global irrigation water." Earth System Dynamics 6, no. 2 (July 20, 2015): 461–84. http://dx.doi.org/10.5194/esd-6-461-2015.

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Abstract. Future projections on irrigation water under a changing climate are highly dependent on meteorological data derived from general circulation models (GCMs). Since climate projections include biases, bias correction is widely used to adjust meteorological elements, such as the atmospheric temperature and precipitation, but less attention has been paid to biases in humidity. Hence, in many cases, uncorrected humidity data have been directly used to analyze the impact of future climate change. In this study, we examined how the biases remaining in the humidity data of five GCMs propagate into the estimation of irrigation water demand and consumption from rivers using the global hydrological model (GHM) H08. First, to determine the effects of humidity bias across GCMs, we ran H08 with GCM-based meteorological forcing data sets distributed by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). A state-of-the-art bias correction method was applied to the data sets without correcting biases in humidity. Differences in the monthly relative humidity amounted to 11.7 to 20.4 % RH (percentage relative humidity) across the GCMs and propagated into differences in the estimated irrigation water demand, resulting in a range between 1152.6 and 1435.5 km3 yr−1 for 1971–2000. Differences in humidity also propagated into future projections. Second, sensitivity analysis with hypothetical humidity biases of ±5 % RH added homogeneously worldwide revealed the large negative sensitivity of irrigation water abstraction in India and East China, which are heavily irrigated. Third, we performed another set of simulations with bias-corrected humidity data to examine whether bias correction of the humidity can reduce uncertainties in irrigation water across the GCMs. The results showed that bias correction, even with a primitive methodology that only adjusts the monthly climatological relative humidity, helped reduce uncertainties across the GCMs: by using bias-corrected humidity data, the uncertainty ranges of irrigation water demand across the five GCMs were successfully reduced from 282.9 to 167.0 km3 yr−1 for the present period, and from 381.1 to 214.8 km3 yr−1 for the future period (RCP8.5, 2070–2099). Although different GHMs have different sensitivities to atmospheric humidity because different types of potential evapotranspiration formulae are implemented in them, bias correction of the humidity should be applied to forcing data, particularly for the evaluation of evapotranspiration and irrigation water.

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Journal articles on the topic 'Primitive estimation'

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